Method for monitoring a storage space and electronic device

Abstract

The application provides a storage space monitoring method and an electronic device, and relates to the technical field of terminal devices. The method is applied to an electronic device, the electronic device comprises a nonvolatile memory, and the storage space monitoring method corresponding to the nonvolatile memory comprises the following steps: when the electronic device is in a powered-on state, monitoring the storage space at a preset frequency to obtain target monitoring data; performing storage occupancy analysis processing on the target monitoring data; if the result of the storage occupancy analysis processing indicates that the storage space has abnormal occupancy, generating a warning instruction for indicating storage abnormality. The embodiment of the application is active and independent monitoring of the storage space, abnormal occupancy in the storage space is captured by analyzing and managing the target monitoring data obtained from the storage space, the influence of abnormal occupancy on the electronic device is reduced, and the experience of a user is improved.

Description

Technical Field

[0001] This application relates to the technical field of terminal devices, and more particularly to a method and electronic device for monitoring storage space. Background Technology

[0002] As technology continues to advance, the functions of electronic devices are constantly increasing. During the use of electronic devices, system failures and application anomalies may occur, which may cause temporary and abnormal occupation of storage space.

[0003] The storage space usage in electronic devices has a significant impact on hardware performance. In related technologies, electronic devices typically monitor storage space only when relevant controls in applications with system-level permissions are triggered. In other words, storage space monitoring may only be triggered when abnormal storage space usage occurs, leading to storage space approaching saturation or becoming insufficient. However, by this time, the electronic device may have already experienced slower operation, or even lag or crashes.

[0004] Therefore, in order to ensure that electronic devices can operate efficiently and stably, there is an urgent need for a method to monitor the storage space in electronic devices. Summary of the Invention

[0005] This application provides a method and electronic device for monitoring storage space, which can actively monitor the storage space in the electronic device, detect changes in the storage space in advance, and improve the control over the storage space.

[0006] Firstly, a method for monitoring storage space is provided, applied to an electronic device, the electronic device including a non-volatile memory; the method for monitoring storage space includes: during the power-on process of the electronic device, acquiring target monitoring data, the target monitoring data being data acquired when monitoring the storage space at a preset frequency, and the storage space being a storage area corresponding to the non-volatile memory; performing storage occupancy analysis processing on the target monitoring data to determine whether there is abnormal occupancy of the storage space; if there is abnormal occupancy of the storage space, generating a warning instruction to indicate the storage abnormality.

[0007] Abnormal usage refers to the temporary and unreasonable use of storage space in the event of system failure, application failure, or other circumstances.

[0008] The storage space monitoring method provided in this application embodiment allows for proactive monitoring of the storage space at a preset frequency when the electronic device is powered on, acquiring relevant target monitoring data within the storage space. Furthermore, the target monitoring data undergoes storage occupancy analysis, and when abnormal occupancy is detected, a warning instruction indicating storage anomaly is generated, enabling the electronic device to display a corresponding storage anomaly warning. This application embodiment provides proactive and independent monitoring of the storage space, enabling early detection of changes in storage space, capturing abnormal occupancy, improving control over the storage space, reducing the impact of abnormal occupancy on the operation of the electronic device, and enhancing the stability and user experience of the electronic device.

[0009] It should be understood that proactive monitoring of storage space can include one or more of the following monitoring methods: real-time monitoring and periodic monitoring. Among them, real-time monitoring can more accurately and immediately reflect the real-time dynamic changes of storage space; periodic monitoring can provide a more macroscopic and phased reflection of the storage space status.

[0010] In one possible implementation, the target monitoring data includes first monitoring data; acquiring the target monitoring data includes: monitoring the storage space at a preset first frequency to acquire N sets of storage data groups; wherein each storage data group includes corresponding target data, the target data being the top M data in terms of storage capacity when the storage space is monitored once, and N and M being positive integers greater than 1; and determining the first monitoring data based on the continuously acquired N sets of storage data groups.

[0011] It should be understood that, under the premise of ensuring the normal operation of electronic devices, the storage space is actively monitored according to the larger frequency that can be used, and the first monitoring data is obtained.

[0012] To improve the processing efficiency of the first monitoring data, the storage data group in the first monitoring data is the data at the top of the list after the storage capacity of the single monitoring storage space is sorted in descending order, thus reducing the amount of monitoring data; at the same time, the storage data group acquired multiple times will also be used as the first monitoring data to facilitate the improvement of the efficiency of subsequent storage occupancy analysis.

[0013] In one possible implementation, the storage occupancy analysis of the target monitoring data includes: analyzing the first data to be detected in the first monitoring data to determine whether the rate of change of the first data to be detected is greater than a preset first threshold or less than a preset second threshold, wherein the first data to be detected is data involved in the storage data group in the first monitoring data; if the rate of change of the first data to be detected is greater than the preset first threshold, and the rate of change of the first data to be detected is less than the preset second threshold within a preset time period, it is determined that there is abnormal occupancy of storage space.

[0014] It should be understood that the first monitoring data includes multiple storage data groups. The target data in each storage data group is dynamically changing. Therefore, there may be the same data or different data in each storage data group. Therefore, all the data involved in each storage data group is called the first monitoring data for easy description and understanding.

[0015] Furthermore, regarding abnormal storage space usage, abnormal storage capacity usage often occurs in pairs, with the rate of change of the first data to be detected surging and then plummeting within a short period of time. Therefore, by analyzing the rate of change of the first data to be detected, if the rate of change of the first data to be detected is greater than a preset first threshold, or if the rate of change of the first data to be detected is less than a preset second threshold within a preset time period, it can be determined that there is abnormal storage space usage, thereby improving the real-time performance and accuracy of monitoring.

[0016] It should also be understood that if the rate of change of the first data to be detected surges in a short period of time, the surge in usage can be recorded first, and the storage space usage can be allowed to decrease sharply within a preset time period.

[0017] In one possible implementation, the storage occupancy analysis of the target monitoring data includes: analyzing the first data to be detected in the first monitoring data to determine whether the rate of change of the first data to be detected is greater than a preset first threshold, wherein the first data to be detected is data involved in the storage data group in the first monitoring data; and if the rate of change of the first data to be detected is greater than the preset first threshold, determining that there is abnormal occupancy of storage space.

[0018] The rate of change of the first data to be detected is determined by the first data to be detected involved in the first monitoring data.

[0019] It should be understood that for abnormal storage space usage, especially a surge in storage capacity usage, the criteria for determining the rate of change corresponding to the surge in usage can be improved, making the monitoring and identification capabilities more accurate and stable when facing complex and ever-changing storage environments.

[0020] In one possible implementation, the target monitoring data includes second monitoring data; acquiring the target monitoring data includes: recording data in the storage space based on a preset time to obtain point data; acquiring the point data based on a preset second frequency to obtain second monitoring data, wherein the preset second frequency is less than the preset first frequency.

[0021] It should be understood that the second monitoring data is used to analyze the impact of user habits on the storage capacity of the storage space; specifically, by recording all data related to operating system data and application data in the storage space, the user's usage habits at a specific time are obtained, and these data are actively monitored based on a preset second frequency to achieve regular monitoring of the storage space.

[0022] In one possible implementation, the storage occupancy analysis of the target monitoring data includes: analyzing the second monitoring data based on a preset first model to determine whether the second monitoring data conforms to the user's usage habits; if the output of the preset first model indicates that there is second data to be detected in the second monitoring data that does not conform to the user's usage habits, it is determined that there is abnormal storage space occupancy.

[0023] The first preset model is built based on the usage habits of electronic device users and the corresponding storage space usage. It is used to learn and analyze user habits. Through long-term learning, the first preset model can understand the user's usage habits of various applications and the storage space usage corresponding to these habits. Therefore, the first preset model can be used to analyze the second monitoring data to determine whether there is any second data to be detected that does not conform to the user's system usage. In other words, by analyzing usage habits, it is helpful to identify abnormal storage space usage.

[0024] In one possible implementation, the storage occupancy analysis of the target monitoring data includes: analyzing the second monitoring data based on a preset first major model to determine whether the second monitoring data conforms to the user's usage habits; sending the second monitoring data to the cloud side so that the cloud side can analyze the second monitoring data based on the preset second major model and feed back the results output by the preset second major model to the electronic device; when the results output by the preset first major model indicate that the second monitoring data does not conform to the user's usage habits, and when the results output by the preset second major model indicate that the second data does not conform to the user group's usage habits, it is determined that there is abnormal storage space occupancy.

[0025] It should be understood that different users may have different usage habits. By setting up a second preset model on the cloud side to analyze the usage habits of the user group, and combining the results with the results on the edge side, the accuracy of monitoring storage space by using usage habits can be improved.

[0026] In one possible implementation, the target monitoring data includes first monitoring data and second monitoring data. The result of the storage occupancy analysis is determined by the first analysis result and the second analysis result. If the result of the storage occupancy analysis indicates abnormal storage space occupancy, generating an alert instruction to indicate storage anomaly includes: generating an alert instruction when at least one of the first analysis result and the second analysis result indicates abnormal storage space occupancy; wherein, the first analysis result is the result obtained after analyzing the first monitoring data; and the second analysis result is the result obtained after analyzing the second monitoring data based on a preset first large model, or a preset first large model and a preset second large model.

[0027] The storage space monitoring method provided in this application embodiment actively monitors and periodically detects the storage space in real time when the electronic device is powered on. It analyzes abnormal occupancy in the storage space from multiple perspectives, thereby improving the accuracy of storage space monitoring. Furthermore, through various active detection methods for the storage space, it can quickly and accurately grasp changes in the storage space, capture abnormal occupancy in the storage space, improve control over the storage space, reduce the impact of abnormal occupancy on the operation of the electronic device, and improve the stability and user experience of the electronic device.

[0028] In one possible implementation, the electronic device includes a storage performance monitoring module and an intelligent analysis module. The method further includes: the storage performance monitoring module acquiring first monitoring data; sending the first monitoring data to the intelligent analysis module; the intelligent analysis module analyzing the first monitoring data to obtain a corresponding first analysis result; and generating a warning instruction based on the first analysis result indicating abnormal storage space occupancy.

[0029] The storage space monitoring method provided in this application embodiment is executed by the storage performance monitoring module and the intelligent analysis module in the electronic device. It should be understood that the storage performance monitoring module can view and retrieve data from the non-volatile memory in the hardware through the storage access interface in the framework layer. When the electronic device is powered on, it can actively monitor the storage space in real time, and can promptly control changes in the storage space and capture abnormal occupancy in the storage space.

[0030] In one possible implementation, the electronic device includes a data maintenance testing module and an intelligent analysis module. The method further includes: the data maintenance testing module acquiring second monitoring data; sending the second monitoring data to the intelligent analysis module; the intelligent analysis module analyzing the second monitoring data to obtain a corresponding second analysis result; and generating a warning instruction based on the second analysis result indicating abnormal storage space occupancy.

[0031] The storage space monitoring method provided in this application embodiment is executed by the data maintenance test module and the intelligent analysis module in the electronic device. It should be understood that the data maintenance test module can view and retrieve data from the non-volatile memory in the hardware through the storage access interface in the framework layer. When the electronic device is powered on, it can actively and periodically detect the storage space, accurately control the changes in the storage space, and capture abnormal occupancy in the storage space.

[0032] In one possible implementation, the electronic device includes a storage performance monitoring module, a data maintenance testing module, and an intelligent analysis module. The method further includes: the storage performance monitoring module acquiring first monitoring data; the data maintenance testing module acquiring second monitoring data; sending the first and second monitoring data to the intelligent analysis module; the intelligent analysis module analyzing the first and second monitoring data to obtain corresponding first and second analysis results; at least one of the first and second analysis results indicates abnormal storage space occupancy, and generating a warning instruction.

[0033] The storage space monitoring method provided in this application embodiment is executed by the storage performance monitoring module, data maintenance testing module, and intelligent analysis module in the electronic device. It should be understood that the storage performance monitoring module and data maintenance testing module can view and retrieve data from the non-volatile memory in the hardware through the storage access interface in the framework layer. When the electronic device is powered on, it actively monitors and periodically detects the storage space, analyzes abnormal occupancy in the storage space from multiple perspectives, and can quickly and accurately control changes in the storage space and capture abnormal occupancy in the storage space.

[0034] In one possible implementation, the target monitoring data includes operating system data and application data in the storage space, or the target monitoring data includes application data in the storage space.

[0035] The possibility of abnormal data occupancy in storage space is relatively small. Therefore, in order to improve the effective monitoring of storage space, it is necessary to accurately grasp the details of storage space occupancy for operating system data and application data in storage space.

[0036] It should also be understood that in some electronic devices, the operating system data cannot be modified. In this case, only the application data can be analyzed to accurately grasp the details of storage space usage.

[0037] In a second aspect, an electronic device is provided, comprising a processor and a memory, the memory for storing computer programs, and the processor for retrieving and running the computer programs from the memory, such that the electronic device performs any of the methods in the first aspect.

[0038] Thirdly, a storage space monitoring device is provided, including a unit for performing any of the methods in the first aspect.

[0039] Fourthly, a computer-readable storage medium is provided, which stores a computer program that, when executed, causes any of the storage space monitoring methods described in the first aspect to be performed.

[0040] Fifthly, a computer program product is provided, comprising a computer program that, when executed, causes any of the storage space monitoring methods described in the first aspect to be performed.

[0041] It is understandable that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0042] Figure 1 This diagram illustrates how a mobile phone displays details of its storage space usage.

[0043] Figure 2 This diagram illustrates yet another mobile phone displaying details of its storage space usage;

[0044] Figure 3 A hardware structure diagram of an electronic device provided in an embodiment of this application is shown;

[0045] Figure 4 A schematic diagram of the system architecture of an electronic device according to an embodiment of this application is shown;

[0046] Figure 5 A schematic diagram of a process in which an application triggers monitoring of storage space is shown;

[0047] Figure 6 A flowchart illustrating a storage space monitoring method provided in some embodiments of this application is shown;

[0048] Figure 7 This application provides schematic diagrams illustrating visual warnings in the presentation of storage anomaly warnings according to some embodiments;

[0049] Figure 8 A flowchart illustrating a storage space monitoring method provided in other embodiments of this application is shown;

[0050] Figure 9 This illustration shows a schematic diagram of the structure of the first monitoring data in an embodiment of this application;

[0051] Figure 10 A schematic diagram of the first monitoring data update process in an embodiment of this application is shown;

[0052] Figure 11 yes Figure 9 A schematic diagram illustrating the detailed information of each stored data group in the first monitoring data;

[0053] Figure 12 A schematic diagram illustrating detailed information of each stored data group in the first monitoring data provided in other embodiments of this application is shown;

[0054] Figure 13 A flowchart illustrating a storage space monitoring method provided in other embodiments of this application is shown;

[0055] Figure 14 This illustration shows a schematic diagram of the structure of the second monitoring data in an embodiment of this application;

[0056] Figure 15 A flowchart illustrating a storage space monitoring method provided in other embodiments of this application is shown;

[0057] Figure 16 A flowchart illustrating a storage space monitoring method provided in other embodiments of this application is shown;

[0058] Figure 17 A flowchart illustrating a storage space monitoring method provided in other embodiments of this application is shown;

[0059] Figure 18 A schematic diagram of a data maintenance testing module in an electronic device provided in an embodiment of this application is shown;

[0060] Figure 19 This illustration shows a schematic diagram of a smart analysis module in an electronic device provided in an embodiment of this application.

[0061] Figure 20 A schematic diagram of the process for triggering storage space monitoring in an electronic device is shown;

[0062] Figure 21 A schematic diagram of a storage space monitoring device provided in an embodiment of this application is shown. Detailed Implementation

[0063] The technical solutions of the embodiments of this application will be described below with reference to the accompanying drawings. In the description of the embodiments of this application, unless otherwise stated, " / " means "or," for example, A / B can mean A or B; "and / or" in this text is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Furthermore, in the description of the embodiments of this application, "multiple" refers to two or more than two.

[0064] Hereinafter, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include one or more of that feature.

[0065] Specific details, such as particular system architectures and techniques, are set forth for illustrative purposes and not for limitation, to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application can be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods are omitted to avoid unnecessary detail that could obscure the description of this application.

[0066] With the continuous advancement of technology, the amount of data involved in electronic devices is constantly increasing, leading to a growing demand for storage space. This storage space is primarily used to store operating systems (such as Android or Linux), applications, and user data (such as pictures, videos, audio, documents, text messages, contact information, and call logs).

[0067] Operating systems improve user experience by adding new features, optimizing existing features, and fixing vulnerabilities. However, the addition of new features and the optimization of existing features all lead to a gradual increase in the storage space occupied by the operating system.

[0068] Application developers typically update their applications regularly to fix bugs, add new features, or improve performance. Updated applications include new code and resource files (such as icons, audio, and animations). All of these contribute to a gradual increase in storage space usage. Furthermore, some applications continuously generate data during use, such as cached data, configuration data, and log data, further increasing the storage space required.

[0069] The storage space occupied by electronic devices is closely related to hardware performance. Excessive storage space utilization can severely restrict their operating efficiency and have a significant impact on hardware performance. However, as electronic devices are used for longer periods, their storage space gradually fills with various types of data, which can lead to storage space saturation or insufficiency, thereby affecting the user experience of the electronic devices.

[0070] It should also be understood that during the use of electronic devices, abnormal storage space usage may occur due to system failures, application anomalies, and other issues. For example, corrupted or incorrectly updated system files may lead to an accumulation of corresponding temporary or erroneous files; program design flaws may cause uncontrolled caching, resulting in applications using storage space far exceeding normal requirements; the generation of a large number of duplicate files or incorrect storage settings may also cause unreasonable storage space usage.

[0071] Taking application exceptions as an example, due to errors in the application's code or other unknown reasons, there may be situations where storage space is excessively used or insufficient. For instance, if application C experiences a large amount of storage usage in a short period of time, the electronic device may initially have plenty of available storage space, but after a few minutes, hours, or even more than ten hours, the storage space may become insufficient. This abnormal use of storage space affects the user experience.

[0072] It should also be understood that the abnormal storage usage of the applications in the above examples is often phased and short-lived. Taking application C as an example, its storage usage may increase sharply in a short period of time, from a few GB to hundreds of GB. However, the monitoring mechanisms currently used by electronic devices are user-triggered and are not sensitive enough to the electronic devices themselves. In other words, there are no relevant checking programs or mechanisms in the electronic devices to detect such abnormal usage in time. Often, by the time the user realizes that the storage space is insufficient and triggers the monitoring operation of the storage space through the above settings, application C may have already released the abnormally occupied storage space. At this time, the user cannot determine which application is abnormal and causes the storage space resources to be occupied.

[0073] In related technologies, electronic devices are unable to detect storage anomalies in the storage space in a timely manner when faced with normal data accumulation and abnormal storage occupancy, resulting in poor sensitivity of electronic devices to such problems.

[0074] Currently, the usage of storage space in electronic devices can be viewed through the relevant interface in the settings application. The following example, using a mobile phone as an example, illustrates the usage of storage space in related technologies with accompanying diagrams.

[0075] Figure 1 This diagram illustrates how a mobile phone displays details of its storage space usage. On the phone's main screen 20, the user accesses settings by clicking the icon of the settings application 201, as shown below. Figure 1As shown in (a); entering the settings interface 21 of the settings application allows for personalized settings of many functions of the phone, including network and connection settings (such as Wireless Local Area Network (WLAN), Bluetooth settings, mobile network settings, etc.), device management (such as display, sound, notifications, desktop personalization and storage, etc.), and system and application-related settings (such as system updates, application list, application permissions, etc.). Users can select according to their needs. In this application scenario, the user clicks the storage control 211, such as... Figure 1 As shown in (b); upon entering storage interface 22, storage interface 22 displays the total storage capacity of the phone, the currently used storage capacity, and the remaining storage capacity; storage interface 22 also displays the storage capacity and diagrams corresponding to each category, as shown in... Figure 1 As shown in (c), the categories involved include images, videos, audio, documents, compressed files, installation packages, applications, system data, and other corresponding storage capacities. "Others" can refer to logs, system resources, etc. At this point, users can get a rough idea of ​​the storage usage of various data types. If users want to further understand the usage of each application, they can click the cleanup and acceleration control 221 in the storage interface 22, such as... Figure 1 As shown in (c); upon entering scan interface 23, information about the storage space, the types of data that can be cleaned, and the capacity will be displayed, such as... Figure 1 As shown in (d) in the diagram; that is, the monitoring of storage space is triggered by the user's click operations in the relevant interfaces of the settings application 201.

[0076] When a user discovers a storage anomaly on their phone, they can check it through the settings application. In this scenario... Figure 2 This illustration shows another way a mobile phone displays details of its storage space usage. In the settings application, if the user clicks the "Clean Up" control 231 corresponding to the "App Data" option under the "Recommended Cleanup" section in the scan interface 23, as shown... Figure 2 As shown in (a), this will trigger monitoring of storage space, and then, in the next level interface, namely the cleanup interface 24, the data that can be cleaned up in each application will be displayed, such as... Figure 2 As shown in (b); if the user clicks the application control 232 under the special cleaning item in the scanning interface 25, such as Figure 2 As shown in (c), this will also trigger storage space monitoring. The next level interface, display interface 26, will show data on the storage capacity used by each application, such as... Figure 2 As shown in (d) in the figure.

[0077] Among them, the scanning interface 25 is the interface after sliding the scanning interface 23.

[0078] At this time, the data for each application provided in the relevant interface of the settings application are all normal. Users cannot understand which specific application is abnormal or which type of data is abnormal through the data displayed in the settings application.

[0079] It should be understood that data monitoring of storage space can be triggered by controls in multiple interfaces of the settings application. The data about storage space presented in the relevant interfaces of the settings application is obtained and displayed based on the specific business needs of the settings application.

[0080] Therefore, in related technologies, users actively trigger the monitoring of storage space through application settings, which cannot display the actual storage space data to users in a timely manner. In other words, it does not support automatic monitoring of storage space, and thus cannot avoid situations where storage space occupancy tends to be saturated or insufficient.

[0081] It should also be understood that in related technologies, the information involved in the storage space is sensitive information. Therefore, only applications with system-level privileges can initiate calls. For example, the settings application in the above example has system-level privileges.

[0082] Applications with system-level privileges can modify various system parameters, such as network settings, display settings, and application management. These privileges allow them to operate at a deep system level, such as triggering monitoring of storage space through controls in the settings interface or storage interface of an application. Currently, storage space in the hardware can be viewed and data retrieved through the storage access interface in the application framework layer of electronic devices. After obtaining the storage data group returned by the kernel layer at the application framework layer, the storage data group is processed according to the application's business needs for convenient data display.

[0083] In other words, current monitoring of storage space is triggered by users through relevant controls in applications with system-level permissions. Therefore, the monitoring of storage space is only triggered by applications with system-level permissions when the user becomes aware of storage space abnormalities.

[0084] In view of this, embodiments of this application provide a method for monitoring storage space and an electronic device. The method is applied to an electronic device, which includes a non-volatile memory (NVMemory). The method for monitoring the storage space corresponding to the NVMemory includes: monitoring the storage space at a preset frequency while the electronic device is powered on to obtain target monitoring data; performing storage occupancy analysis on the target monitoring data; and generating a warning instruction to indicate abnormal storage occupancy if the result of the storage occupancy analysis indicates abnormal storage occupancy. This embodiment of the application provides proactive and independent monitoring of the storage space. By analyzing and managing the target monitoring data obtained from the storage space, abnormal occupancy in the storage space is captured, reducing the impact of abnormal occupancy on the electronic device and thereby improving the user experience.

[0085] The following description, in conjunction with the accompanying drawings, describes the electronic device to which the storage space monitoring method provided in the embodiments of this application is applied. The electronic device may be a terminal device such as a mobile phone, tablet computer, wearable device, in-vehicle electronic device, laptop computer, personal digital assistant (PDA), etc. The embodiments of this application do not impose any special limitations on the specific form of the electronic device.

[0086] Figure 3 A hardware structure diagram of an electronic device provided in an embodiment of this application is shown. Figure 3 As shown, the electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a speaker 170A, a receiver (i.e., earpiece) 170B, a microphone 170C, a headphone jack 170D, a sensor module 180, buttons 190, a motor 191, an indicator 192, a camera 193, a display screen 194, and a subscriber identification module (SIM) card interface 195, etc. The sensor module 180 may include a pressure sensor 180A, a gyroscope sensor 180B, a barometric pressure sensor 180C, a magnetic sensor 180D, an accelerometer sensor 180E, a distance sensor 180F, a proximity sensor 180G, a fingerprint sensor 180H, a temperature sensor 180J, a touch sensor 180K, an ambient light sensor 180L, a bone conduction sensor 180M, etc.

[0087] It should be noted that, Figure 3The connection relationships between the modules shown are merely illustrative and do not constitute a limitation on the connection relationships between the modules in the electronic device 100. In other embodiments of this application, the electronic device 100 may include more than Figure 3 The components shown may include more or fewer components, or the electronic device 100 may include... Figure 3 The components shown may be a combination of certain components, or the electronic device 100 may include... Figure 3 Sub-components of some of the components shown. Figure 3 The components shown can be implemented in hardware, software, or a combination of software and hardware.

[0088] Processor 110 may include one or more processing units, such as: application processor (AP), modem processor, graphics processing unit (GPU), image signal processor (ISP), controller, memory, video codec, digital signal processor (DSP), baseband processor, and / or neural network processing unit (NPU), etc. Different processing units may be independent devices or integrated into one or more processors.

[0089] The controller can be the nerve center and command center of the electronic device 100. The controller can generate operation control signals according to the instruction opcode and timing signals to complete the control of fetching and executing instructions.

[0090] The processor 110 may also include a memory for storing instructions and data. In some embodiments, the memory in the processor 110 is a cache memory. This memory can store instructions or data that the processor 110 has just used or that are used repeatedly. If the processor 110 needs to use the instruction or data again, it can retrieve it directly from this memory. This avoids repeated accesses, reduces the waiting time of the processor 110, and thus improves the efficiency of the system.

[0091] In some embodiments, the processor 110 may include one or more interfaces, such as an inter-integrated circuit (I2C) interface, an inter-integrated circuit sound (I2S) interface, a pulse code modulation (PCM) interface, a universal asynchronous receiver / transmitter (UART) interface, a mobile industry processor interface (MIPI), a general-purpose input / output (GPIO) interface, a subscriber identity module (SIM) interface, and / or a universal serial bus (USB) interface, etc.

[0092] It is understood that the interface connection relationships between the modules illustrated in the embodiments of this application are merely illustrative and do not constitute a structural limitation on the electronic device 100. In other embodiments of this application, the electronic device 100 may also employ different interface connection methods or combinations of multiple interface connection methods as described in the above embodiments.

[0093] Internal memory 121 can be used to store computer-executable program code; computer-executable program code includes instructions. Processor 110 executes various functional applications and data processing of electronic device 100 by running the instructions stored in internal memory 121.

[0094] It should be understood that internal memory 121 may include high-speed random-access memory (RAM) and non-volatile memory (NVM).

[0095] Among them, high-speed random access memory (RAM) is a type of computer memory. In electronic devices, RAM is used to temporarily store running programs and data during operation. For example, when you open a mobile application, the application's code and related data are loaded into RAM so that the processor can quickly read and process this information to ensure the smooth operation of the application.

[0096] Non-volatile memory (NVMemory) is a type of memory that retains stored data even when power is off. NVOCCs inside electronic devices primarily include flash memory and / or read-only memory (ROM). Flash memory, a type of NVOCC, uses floating-gate transistors to store electrical charges, representing the 0 and 1 states of data. This storage method allows data to be preserved even without a power supply. The storage space described in the embodiments of this application refers to the storage area corresponding to the NVOCC.

[0097] Non-volatile memory (NVH) is used to store operating systems, applications, user data, and other data. Storage capacities are available in various sizes, including 32GB, 64GB, 128GB, 256GB, and 1TB.

[0098] The storage space in this embodiment can also be referred to as internal memory, which typically refers to the area inside an electronic device that stores data in the form of flash memory. Flash memory is a non-volatile memory; the stored data is not lost even when the device is powered off. It records data by controlling the state of internal transistors through electrical signals.

[0099] ROM is used to store fixed programs and data. However, with the continuous evolution of technology, ROM has been redefined in the field of electronic devices. It is no longer limited to read-only but has read and write capabilities, becoming a key area for storing the operating system, applications, and user data of electronic devices. In the daily use of electronic devices, users can install new applications, delete / store various files, and perform other operations on the ROM. Therefore, storage space can, to some extent, be understood as the storage area corresponding to ROM.

[0100] The external storage interface 120 can be used to connect external storage cards, such as SD cards and microSD cards, to expand the storage capacity of the electronic device 100. The external storage card communicates with the processor 110 through the external storage interface 120 to perform data storage functions, such as storing pictures, music, videos, and files on the external storage card.

[0101] In some examples, external non-volatile memory (i.e., external memory cards) can be connected to the electronic device via external memory interface 120 to provide additional storage expansion capabilities. In this example, the non-volatile memory can also consist of internal non-volatile memory and external non-volatile memory. The internal non-volatile memory is used to store operating system data, application data, and user data, etc.; the external non-volatile memory is generally used to store user data, such as pictures, videos, and files.

[0102] Non-volatile memory can also be Universal Flash Storage (UFS). UFS is commonly used in flash storage in consumer electronic devices such as digital cameras and mobile phones, and features high-speed data transfer and stability.

[0103] The charging management module 140 is used to receive charging input from the charger. The charger can be a wireless charger or a wired charger.

[0104] The wireless communication function of electronic device 100 can be realized through antenna 1, antenna 2, mobile communication module 150, wireless communication module 160, modem processor and baseband processor, etc.

[0105] Electronic device 100 implements display functions through a GPU, a display screen 194, and an application processor. The GPU is a microprocessor for image processing, connected to the display screen 194 and the application processor. The GPU is used to perform mathematical and geometric calculations and for graphics rendering. Processor 110 may include one or more GPUs, which execute program instructions to generate or modify display information.

[0106] Display screen 194 is used to display images, videos, etc. Display screen 194 includes a display panel. The display panel can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active-matrix organic light-emitting diode (AMOLED), a flexible light-emitting diode (FLED), a Mini LED, a MicroLED, a Micro-OLED, a quantum dot light-emitting diode (QLED), etc.

[0107] Electronic device 100 can implement audio functions, such as music playback and recording, through audio module 170, speaker 170A, microphone 170C and application processor.

[0108] Electronic device 100 can monitor the user's physiological indicators, movement status and environmental information through various sensors in sensor module 180, so as to provide the user with exercise assistance and convenient interactive experience.

[0109] Pressure sensor 180A is used to sense pressure signals and convert them into electrical signals. In some embodiments, pressure sensor 180A may be disposed on display screen 194. When a touch operation is applied to display screen 194, electronic device 100 detects the intensity of the touch operation based on pressure sensor 180A. Electronic device 100 may also calculate the touch position based on the detection signal from pressure sensor 180A. In some embodiments, touch operations applied to the same touch position but with different touch operation intensities may correspond to different operation instructions, such as clicking on controls in the interface displayed on display screen 194.

[0110] Touch sensor 180K, also known as a "touch panel," can be located on display screen 194. The touch sensor 180K and display screen 194 together form a touchscreen, also known as a "touch screen." Touch sensor 180K detects touch operations applied to or near it. Touch sensor 180K can transmit the detected touch operation to the application processor to determine the type of touch event. Visual output related to the touch operation can be provided through display screen 194. In other embodiments, touch sensor 180K may also be located on the surface of electronic device 100, in a different position than display screen 194. For example, swiping up or down on the interface presented on display screen 194.

[0111] The electronic device 100 runs an operating system, such as Linux, Unix, Android, iOS, or Windows. Applications can be installed and run on the operating system.

[0112] The operating system of electronic device 100 can adopt a layered architecture, event-driven architecture, microkernel architecture, microservice architecture, or cloud architecture. This application embodiment uses the Android operating system as an example to exemplify the system architecture of electronic device 100.

[0113] It should be noted that although the embodiments of this application are described using the Android operating system as an example, the basic principles are also applicable to electronic devices 100 with other operating systems.

[0114] Figure 4A schematic diagram of the system architecture of an electronic device according to an embodiment of this application is shown, such as... Figure 4 As shown, the software system of electronic device 100 can be divided into several layers, each with a clear role and division of labor. Layers communicate with each other through software interfaces. In some embodiments, the Android operating system is divided into three layers, from top to bottom: Applications, Application Framework, System Libraries and Android Runtime, and Kernel.

[0115] The application layer can include a series of applications, such as settings applications, gallery applications, camera applications, instant messaging applications, calling applications, video applications, map applications, and music applications (applications can be simply referred to as apps).

[0116] The application framework layer, also known as the framework layer, provides application programming interfaces (APIs) and programming frameworks for applications within the application layer. Through these APIs, applications can call corresponding functions in the underlying layers below the application framework layer without needing to delve into the details of those layers.

[0117] In this embodiment, the application framework layer may further include a storage performance monitoring module, a data maintenance testing module, and a storage access interface.

[0118] The storage performance monitoring module is used to manage the storage performance of the storage space in real time. It can monitor and store the data in the storage space that are arranged in descending order of storage capacity according to the time dimension of real-time monitoring.

[0119] The data maintenance and testing module is used to periodically manage the storage performance of the storage space. It can track the usage of the storage space according to the time dimension of periodic monitoring and obtain corresponding log files.

[0120] Furthermore, the storage access interface can access relevant data information in the storage space. Because the storage space of electronic devices contains sensitive information, such as user privacy data and system configuration files, access permissions for the storage access interface are restricted to ensure security and prevent information leakage and malicious tampering. Access permissions for the storage access interface are restricted to applications with system-level privileges; this secure and stable mechanism, through permission management, ensures that the sensitive information involved in the storage access interface will not be obtained or misused by unauthorized applications.

[0121] Some applications on electronic devices have system-level permissions, such as settings applications. Figure 5 This diagram illustrates a process where an application triggers storage space monitoring. Figure 5 As shown, the process includes the following:

[0122] S310, Applications with system-level privileges trigger the function of monitoring storage space.

[0123] Users trigger storage space monitoring by manipulating relevant controls in applications with system-level permissions; these relevant controls serve as the entry point for storage space monitoring.

[0124] Taking the settings application described above as an example, clicking on the storage control, cleanup acceleration control, and cleanup removal control in the settings application all serve as entry points for triggering storage space monitoring.

[0125] S320: Obtain data from the storage space through the storage access interface in the Framework layer.

[0126] Once the storage space monitoring function is triggered, the storage access interface in the Framework layer will be invoked. This storage access interface provides a unified query function for storage space. After the storage access interface is invoked, an instruction to obtain storage space usage data will be sent to the lower kernel layer. This instruction is intended to allow the kernel layer to sort out and provide feedback on detailed information about storage space usage in memory related to storage space, including the space capacity occupied by each partition and different files.

[0127] The detailed feedback can be a storage table containing overall data on the storage space occupied by applications currently installed on the electronic device, such as package name and corresponding storage partition (i.e., memory address), and there may be a mapping relationship between package name and storage partition; it should be understood that the package name is a unique identifier for the application, used by the system to identify the application.

[0128] S330: Store and process the data in the storage space.

[0129] The application framework layer further stores and processes the data in the storage table, converting the memory addresses in the storage table to generate a mapping table with a one-to-one correspondence between memory addresses, package names, and software installation paths. Based on this, storage space usage can be more intuitively determined through the software installation path, applications can be bound to package names, and data can be categorized. The processed data is then returned to the application layer, where the storage space usage is displayed and used according to the application's business requirements.

[0130] In other words, the relevant technology sets some controls in the application as function entry points, obtains data in the storage space through the storage access interface in the Framework layer, and stores and processes the data based on the business requirements of the application.

[0131] The system libraries and the Android runtime together can be referred to as the system runtime layer. The system libraries connect the application framework layer and the kernel layer; applications execute within the Android runtime.

[0132] The system library may include multiple functional modules. In this embodiment, the system library may also include a smart analysis module. The smart analysis module is used to analyze data monitored in real time by the storage performance monitoring module and data monitored periodically by the data maintenance and testing module, thereby realizing proactive monitoring of storage space, anticipating changes in storage space, and improving control over storage space.

[0133] The kernel layer is used to allocate and manage all hardware and software resources in the operating system. It is a software component and a fundamental and core part of the operating system. The kernel layer acts as the layer between the hardware and software in electronic devices, and at a minimum, it includes touch drivers, display drivers, graphics processing drivers, audio drivers, and sensor drivers.

[0134] It should be noted that the kernel layer differs depending on the operating system. For example, when the operating system is Linux or Android, the kernel layer is the Linux kernel layer.

[0135] It should be noted that the electronic device mentioned in the embodiments of this application may include more or fewer modules of the above-mentioned electronic device.

[0136] The following is combined with Figures 6 to 20 The method for monitoring storage space provided in the embodiments of this application will be described in detail.

[0137] It should be noted that the execution subject of the storage space monitoring method provided in this application embodiment can be the aforementioned electronic device (such as a mobile phone, tablet computer, etc.), or a functional module or functional entity in the electronic device that can implement the method. Furthermore, the solution can be implemented through hardware and / or software, or a combination thereof. The specific implementation can be determined according to actual usage requirements, and this application embodiment does not impose any restrictions on this.

[0138] It should also be noted that the methods in the following embodiments can all be implemented in electronic devices having the above-described hardware structure and system architecture. The hardware structure diagram of the electronic device can be as follows: Figure 3 As shown, the system architecture diagram of an electronic device can be as follows: Figure 4As shown, the embodiments of this application are not limited to this. For ease of explanation, the embodiments of this application all take a mobile phone as an example.

[0139] Figure 6 The following is a flowchart illustrating a storage space monitoring method provided in some embodiments of this application, such as... Figure 6 As shown in the embodiments of this application, the method for monitoring storage space includes the following steps:

[0140] S410, Obtain target monitoring data.

[0141] Among them, the target monitoring data is the data obtained when monitoring the storage space at a preset frequency.

[0142] It should be understood that electronic devices include non-volatile memory, and the storage space described in the embodiments of this application refers to the storage area corresponding to the non-volatile memory.

[0143] The data types in storage space are diverse. Taking a mobile phone as an example, the data in the storage space can include operating system data, application data, and user data. For instance, each application currently installed on the phone has corresponding application data stored in the storage space. In this case, the target monitoring data can include operating system data, application data, and user data.

[0144] User data mainly refers to photos and videos taken by users through cameras, as well as downloaded documents. Users have a clear awareness of the storage space occupied by this type of data, and the possibility of abnormal storage space occupation by this type of data is relatively small. Therefore, in order to improve the effective monitoring of storage space, the target monitoring data can refer to operating system data and application data; by comprehensively monitoring the operating system data and application data in the storage space, the details of storage space occupation can be accurately grasped.

[0145] Applications in electronic devices are the carriers that implement various specific functions. They meet the diverse needs of users for electronic devices, so the performance of application operation directly affects the user experience. In addition, application data has a significant impact on storage space. Therefore, in some examples, the target monitoring data may only include application data in the storage space.

[0146] It should also be understood that the acquired target monitoring data varies significantly depending on the preset frequency. For example, when the preset frequency is high, such as above the first threshold, the corresponding target monitoring data can more accurately and timely reflect the real-time dynamic changes in storage space. Conversely, if the preset frequency is low, such as below the second threshold, the acquired target monitoring data tends to present a more macroscopic and phased view of the storage space status.

[0147] In other words, by adjusting the preset frequency, real-time monitoring and / or periodic monitoring of storage space can be achieved. The monitoring data of these two monitoring methods have different focuses. Therefore, one type of monitoring data can be selected for analysis, or both types of monitoring data can be analyzed.

[0148] It should be noted that the target monitoring data is acquired when the electronic device is powered on. When powered on, the user can interact with the electronic device in various forms. This interaction can be proactive, such as through touch operation, voice commands, or button input, or passive, such as running silently in the background according to presets, processing information, or providing timely feedback to the user. As long as there is information exchange, command transmission, and function triggering between the user and the electronic device, it means that the electronic device is powered on.

[0149] In other words, when electronic devices are in low-power modes such as standby or sleep, they will also monitor the storage space and obtain target monitoring data while performing background tasks.

[0150] For example, instant messaging applications on mobile phones are used for chatting, and camera applications are used for taking pictures; reading applications on tablets are used for reading e-books; fitness tracking applications on smart bracelets record the user's steps and distance in the background; and in-vehicle electronic devices monitor tire pressure data and remaining battery power in the background. All of these electronic devices are powered on.

[0151] S420. Perform storage occupancy analysis on the target monitoring data to determine whether there is abnormal storage space occupancy.

[0152] It should be understood that storage occupancy analysis is used to determine whether there is abnormal occupancy of storage space. In this way, it can effectively reduce the impact of abnormal occupancy on the operation of electronic devices, especially when abnormal occupancy leads to storage space saturation or insufficiency, which increases the impact on electronic devices.

[0153] Among them, by analyzing the storage usage of the real-time monitoring target data and understanding the changing trend of the first monitoring data, it can be determined whether there is a large amount of storage space being occupied in a short period of time; if there is a large amount of storage space being occupied in a short period of time, it indicates that there is abnormal storage space usage.

[0154] Furthermore, by analyzing the storage occupancy of regularly monitored target data, it is possible to obtain feedback on user habits corresponding to the storage capacity of various data storage in the storage space when users use electronic devices. In this way, it can be determined whether there are any changes in the data in the storage space that are inconsistent with user habits; if they are inconsistent with user habits, it indicates that there is abnormal storage space occupancy.

[0155] To improve the effectiveness of storage space monitoring, storage usage analysis can be performed on both real-time and periodically monitored target data. If real-time monitored target data shows a large amount of storage space usage in a short period of time, and / or periodically monitored target data does not conform to user habits, it can be determined that there is abnormal storage space usage.

[0156] S430. If there is abnormal use of storage space, generate a warning command to indicate the storage abnormality.

[0157] When storage usage analysis indicates abnormal storage space usage, it may affect the normal operation of electronic devices. In particular, when abnormal usage leads to near-saturation or insufficient storage space, it can cause lag and other issues, impacting the user experience. Therefore, warning commands to indicate storage anomalies, such as pop-up commands, notification bar commands, prompt commands, and voice commands, are used to display storage anomaly warnings on electronic devices.

[0158] It should also be understood that a storage anomaly warning can be presented on the electronic device based on an alert command. The way to present a storage anomaly warning on the electronic device may include at least one of the following: visual warning, auditory warning, and vibration warning. The embodiments of this application do not limit the way the storage anomaly warning is presented.

[0159] Among them, visual alerts can remind users through pop-ups, notification bars, specific patterns or markers. When the storage usage analysis results indicate abnormal storage space usage, a window will pop up on the screen to inform the user of the abnormal usage problem with eye-catching text or a combination of text and icons.

[0160] Figure 7 The illustration shows a visual warning diagram in the presentation of storage anomaly warning provided in some embodiments of this application, such as... Figure 7 As shown in (a), it is presented in the form of a pop-up window 261, which displays "Application XX was detected to be using resources abnormally," as shown in the image. Figure 7 As shown in (b) above, it is presented in the form of notification bar 262, as follows. Figure 7 As shown in (c), a specific pattern, such as pattern 263, is used to present a warning. This example allows users to intuitively understand which application caused the storage error.

[0161] In visual alerts, controls for clearing anomalies can also be added (264), allowing users to directly perform cleanup operations on abnormal usage, such as... Figure 7 As shown in (d) in the figure.

[0162] Auditory alerts can remind users through voice prompts and tones. When storage usage analysis indicates abnormal storage space usage, the alert can be triggered by a voice message or a special sound effect. During the auditory alert process, users can be guided to clear the abnormality through voice interaction.

[0163] In some embodiments, the priority of the warning instruction can be increased to ensure that the corresponding storage anomaly warning can be seen or noticed by the user in a timely manner.

[0164] The storage space monitoring method provided in this application is applied to an electronic device, which includes a non-volatile memory. The method for monitoring the storage space corresponding to the non-volatile memory includes: monitoring the storage space at a preset frequency when the electronic device is powered on to obtain target monitoring data; performing storage occupancy analysis on the target monitoring data; and generating a warning command to indicate storage anomalies if the result of the storage occupancy analysis indicates abnormal storage space occupancy. This application embodiment provides active and independent monitoring of the storage space. By analyzing and managing the target monitoring data obtained from the storage space, it captures abnormal occupancy in the storage space, reduces the impact of abnormal occupancy on the electronic device, and thus improves the user experience.

[0165] It should be understood that the storage space monitoring method provided in this application embodiment adds an active monitoring method for storage space. Compared with the passive monitoring of storage space by applications with system-level permissions in related technologies, it can control changes in storage space in advance, improve the control over storage space, reduce the impact of abnormal occupation on the operation of electronic devices, and improve the stability and user experience of electronic devices.

[0166] It should be noted that in the storage space monitoring method provided in this application embodiment, real-time monitoring and / or periodic monitoring of the storage space can be achieved by adjusting the preset frequency.

[0167] In one possible scenario, when the preset frequency is high, the corresponding target monitoring data can more accurately and promptly reflect the real-time dynamic changes of the storage space. To improve the monitoring capability of the storage space, the target monitoring data includes first monitoring data, which is data obtained from the storage space at a preset first frequency. Figure 8 The following are schematic flowcharts illustrating storage space monitoring methods provided in other embodiments of this application, such as... Figure 8 As shown in the embodiments of this application, the method for monitoring storage space includes the following steps:

[0168] S510, the first monitoring data obtained.

[0169] The first monitoring data is the data obtained when monitoring the storage space at a preset first frequency.

[0170] It should be understood that the preset first frequency is a relatively high frequency used to ensure the normal operation of electronic devices. For example, the preset first frequency may be once every 2 minutes, once every 3 minutes, once every 5 minutes, or once every 10 minutes. In other words, when monitoring the storage space according to the preset first frequency, the target monitoring data obtained is the first monitoring data. The first monitoring data is real-time monitoring data, which reflects the real-time dynamic changes of the storage space in a timely manner.

[0171] It should be noted that during the monitoring process, the storage space is continuously monitored at a preset first frequency. The first monitoring data can be the monitoring data obtained in a single instance during the monitoring of the storage space.

[0172] In order to quickly analyze the changing trend of various data storage capacity in the storage space, the first monitoring data is multiple and continuous data obtained during the monitoring of the storage space. That is, the first monitoring data includes multiple sets of storage data. At this time, the acquisition of the first monitoring data includes the following processes (1) and (2):

[0173] (1) Obtain the storage data group of the storage space.

[0174] Among them, the storage data group is a single data acquisition obtained by monitoring the storage space at a preset first frequency. The target data in each storage data group can be operating system data and application data, or it can be application data only.

[0175] It should be understood that the embodiments of this application analyze whether there is abnormal occupancy in the storage space by monitoring the storage capacity of various types of data. Therefore, in order to improve the data analysis capability and processing efficiency, the target data in the storage data group can be the top M data in terms of storage control volume among the various types of data obtained in one monitoring, where M is a positive integer greater than 1. That is, the data located in the top M positions according to the descending order of storage capacity, for example, the top 5 or top 10. By analyzing the data with higher storage capacity in the storage space, the complexity of the overall data (i.e., the storage data group) is reduced, thereby analyzing the occupancy in the storage space more efficiently and accurately.

[0176] For example, the data in the mobile phone's storage space includes operating system data, application U data, application V data, application W data, application X data, application Y data, etc. The corresponding storage capacity of each type of data during a monitoring process is shown in the table below:

[0177] Table 1. Detailed information on various types of data in the storage space.

[0178]

[0179] The storage data group consists of the top 5 data items arranged in descending order of storage capacity. For the storage data group obtained in this monitoring, it includes data for application X, application V, operating system, application U, and application Z. For example, the application data in the storage data group may include the application package name and the corresponding storage capacity.

[0180] It should be understood that operating system data consists of multiple data components, such as operating system code data, configuration data, driver data, system architecture data, etc.

[0181] It should be understood that a storage data group is the data that is listed first in descending order of storage capacity. It is related to the storage capacity of various types of data in the storage space. Therefore, a storage data group may include application data and operating system data, or it may only include application data.

[0182] (2) Based on the time of acquisition of the storage data group, determine the first monitoring data corresponding to the N storage data groups.

[0183] Where N is a positive integer greater than 1.

[0184] To analyze the changing trend of the first monitoring data, N sets of data are stored in a fixed stack as the first monitoring data. Each set of first monitoring data refers to N sets of data in the fixed stack. By analyzing the N sets of data in the fixed stack, the changing trend of the first monitoring data can be obtained.

[0185] It should be understood that the size of the fixed stack is preset at creation and will not change. If the size of the fixed stack is N, the first monitoring data includes N sets of stored data groups.

[0186] For example, the fixed stack size is 4, meaning the first monitoring data includes four sets of stored data. Figure 9 This illustration shows a structural diagram of the first monitoring data in an embodiment of this application. The stored data groups are acquired at a preset first frequency of once every 2 minutes, and four stored data groups constitute one set of first monitoring data; as shown Figure 9 As shown, the first monitoring data 30 includes storage data group 1 acquired at 17:12, storage data group 2 acquired at 17:14, storage data group 3 acquired at 17:16, and storage data group 4 acquired at 17:18. Each storage data group includes data in the storage space that are arranged in descending order of storage capacity and are at the top.

[0187] The data in the fixed stack (i.e., the storage data group) follows a top-in, bottom-out processing method. This method is used to update the first monitoring data. Therefore, the first monitoring data is updated as new storage data groups are continuously stored and old storage data groups are discarded. Figure 10 This illustration shows a schematic diagram of the first monitoring data update process in an embodiment of this application, such as... Figure 10 As shown in (a), the stored data group 5, acquired at 17:20, is input from the top of the fixed stack, and the earliest stored data group 1, which was pushed onto the stack, is discarded from the bottom of the stack, as follows. Figure 10 As shown in (b) in the figure, new first monitoring data 31 is formed.

[0188] like Figure 8 As shown, after acquiring the first monitoring data, the first monitoring data is analyzed, and the following steps are executed: S520, determine whether the first data to be detected in the first monitoring data shows a surge trend and / or a sharp decrease trend.

[0189] The first data to be detected refers to the data involved in all stored data groups in the first monitoring data.

[0190] Figure 11 yes Figure 9 A schematic diagram illustrating the detailed information of each stored data group in the first monitoring data, as shown below. Figure 11 As shown, in the first monitoring data, each storage data group includes the first 5 pieces of data to be detected, arranged in descending order of storage capacity. The first pieces of data to be detected involved in the first monitoring data are: data of application K, data of application A, data of application J, data of application E, data of application X, data of application C, and data of application O.

[0191] It should be understood that the first data to be detected in the first monitoring data is dynamically changing. Some first data to be detected may appear in every storage data group, while others may appear in only some storage data groups. Therefore, it is necessary to analyze all the first data to be detected involved in the first monitoring data.

[0192] By analyzing the rate of change of each first data to be detected involved in the first monitoring data, it can be determined whether the first data to be detected shows a surge trend and / or a sharp decrease trend, and the first analysis result can be obtained.

[0193] Specifically, if the rate of change of the first data to be detected meets a preset first condition, it is determined that the storage capacity of the first data to be detected shows a surge trend; if the rate of change of the first data to be detected meets a preset second condition, it is determined that the storage capacity of the first data to be detected shows a sharp decrease trend.

[0194] The first and second preset conditions can be set by adjusting the thresholds. The thresholds can be set according to actual needs to accurately control the triggering criteria and determination range of the first and second preset conditions. To meet the first preset condition, the threshold must be greater than the first preset threshold, and to meet the second preset condition, the threshold must be less than the second preset threshold. In addition, the first preset threshold must be greater than the second preset threshold.

[0195] When the rate of change of the first data to be detected is greater than a preset first threshold, it is determined that the storage capacity of the first data to be detected is showing a surge trend; when the rate of change of the first data to be detected is less than a preset second threshold, it is determined that the storage capacity of the first data to be detected is showing a sharp decrease trend.

[0196] If the rate of change of the first data to be detected is greater than a preset first threshold, and the rate of change of the first data to be detected is less than a preset second threshold within a preset time period, it is determined that there is abnormal occupancy of storage space.

[0197] For example, by referring to Figure 11 Analysis of the first monitoring data shows that the storage capacity of the data of application C, application X, and application O has a change rate. When the change rate of the first data to be detected corresponding to application C is greater than the preset first threshold, it is determined that the storage capacity of the data of application C has a surge trend.

[0198] For example, the first condition is that the change rate is greater than 60%, and the second condition is that the change rate is less than -60%. If the change rate of the first data to be detected is 83%, which is greater than 60%, then the storage capacity of the first data to be detected is determined to have a surge trend. If the change rate of the first data to be detected is 56%, which is less than 60% and greater than -60%, then the storage capacity of the first data to be detected is a normal change, without a surge trend or a sharp decrease trend. If the change rate of the first data to be detected is -61%, which is less than -60%, then the storage capacity of the first data to be detected shows a sharp decrease trend.

[0199] It should be understood that when there is a sudden surge in the first data to be detected, there may be an anomaly in the storage usage of the first data to be detected, and this surge in the data can be recorded.

[0200] S530. If the rate of change of the first data to be detected meets a preset first condition, and the rate of change of the first data to be detected meets a preset second condition within a preset time period, it is determined that there is abnormal occupancy of storage space.

[0201] Among them, the rate of change of the first data to be detected meeting the preset first condition indicates that the first data to be detected shows a surge in change trend, and the rate of change of the first data to be detected meeting the preset second condition indicates that the first data to be detected shows a sharp decrease in change trend.

[0202] In other words, if the first data to be detected shows a surge in change and then a sharp decrease in change within a preset time period, the first analysis result indicates that there is abnormal storage space usage.

[0203] It should be understood that the first monitoring data is dynamically changing. By analyzing the constantly updated first monitoring data, the changing trends of each first data to be detected in the first monitoring data can be monitored.

[0204] It should also be understood that if the confirmed abnormal occupancy is caused by the first data to be detected, A, the data information of the abnormal occupancy can be determined through the first data to be detected, such as the package name of the application in the first data to be detected.

[0205] S540: Based on abnormal storage space usage, generate a warning command to indicate storage abnormalities.

[0206] S550: Displays storage anomaly warnings on electronic devices based on alert commands.

[0207] Storage anomaly alerts are displayed as pop-up windows. For example, during the phone's boot process, if application C is detected to be abnormally occupying storage space, a pop-up window will appear on the phone's current display screen, stating: "Application C has been detected to be abnormally occupying storage space for XX minutes."

[0208] It should be understood that the currently displayed interface can be the main interface, the application interface, or the standby screen. If the currently displayed interface is the standby screen, the phone may also emit a notification sound.

[0209] For details on the implementation of steps 540 and 550, please refer to the detailed description of step 430 above, which will not be repeated here.

[0210] While ensuring the normal operation of electronic devices, the storage space is actively monitored at the highest possible frequency, i.e., the preset first frequency, to obtain the first monitoring data. The first monitoring data includes multiple storage data groups, and the data in each storage data group may be the same or different. Therefore, all the data involved in each storage data group is called the first monitoring data for easy description and understanding.

[0211] Furthermore, since the first data to be detected is dynamically changing, and abnormal storage space occupancy often results in a surge or sharp decrease in storage capacity usage, the changes in the first data to be detected can be analyzed to determine whether there is a surge or sharp decrease trend in the first data to be detected, and the trend of the first data to be detected can be used to determine whether there is abnormal storage space occupancy, thereby improving the real-time performance and accuracy of monitoring.

[0212] It should be noted that whether the first data to be detected shows a surge or a sharp decrease is determined by whether the rate of change of the first data to be detected meets a preset first condition or a preset second condition. In other words, adjusting the threshold in the preset first condition and the preset second condition will affect the determination result. Therefore, in some embodiments, it can be determined that there is an anomaly in the storage space even if the data in the first monitoring data only shows a surge trend.

[0213] It should also be understood that operating system data and application data in storage space are different categories of data. Therefore, in order to better identify the changing trends of various types of data, when each storage data group of the first monitoring data includes only application data, the application data is stored in a fixed stack; while when each storage data group of the first monitoring data includes both operating system data and application data, the operating system data and application data can be stored in different fixed stacks to obtain the first monitoring data, which facilitates subsequent data analysis.

[0214] In other words, when the storage data groups of the first monitoring data include operating system data and application data, there is a first fixed stack and a second fixed stack, wherein the first fixed stack is used to store application data and the second fixed stack is used to store operating system data.

[0215] Figure 12 This illustration shows a schematic diagram illustrating the detailed information of each stored data group in the first monitoring data provided in other embodiments of this application, such as... Figure 12 As shown, each storage data group in the first monitoring data includes operating system data and application data. Each storage data group in the first monitoring data includes the first five pieces of data to be detected, arranged in descending order of storage capacity. The first pieces of data to be detected in the first monitoring data include: data from application K, application A, application J, application E, application X, application C, and operating system data. To better analyze the application data and operating system data, the application data is stored in the first fixed stack 32, and the operating system data is stored in the second fixed stack 33.

[0216] At this point, after obtaining the storage data group of the storage space in step 511 of obtaining the first monitoring data, the following is also included: if the storage data group includes application data and operating system data, the application data is stored in the first fixed stack and the operating system data is stored in the second fixed stack to obtain the first monitoring data, wherein the first monitoring data includes the data corresponding to the first fixed stack and the data corresponding to the second fixed stack.

[0217] Application data and operating system data are stored in different fixed stacks. To analyze the first monitoring data in step 520, the application data in the first fixed stack and the operating system data in the second fixed stack need to be analyzed separately.

[0218] It should be understood that the determination criteria differ when determining the rate of change of application data in the first fixed stack or the rate of change of operating system data in the second fixed stack.

[0219] If the rate of change of application data in the first fixed stack meets the preset third condition, then it is determined that the storage capacity of application data in the first fixed stack shows a surge trend; if the rate of change of application data in the first fixed stack meets the preset fourth condition, then it is determined that the storage capacity of application data in the first fixed stack shows a sharp decrease trend.

[0220] If the rate of change of the operating system data in the second fixed stack meets the preset fifth condition, then it is determined that the storage capacity of the operating system data in the second fixed stack shows a surge trend; if the rate of change of the operating system data in the second fixed stack meets the preset sixth condition, then it is determined that the storage capacity of the operating system data in the second fixed stack shows a sharp decrease trend.

[0221] The preset third, fourth, fifth, and sixth conditions can be set by adjusting the thresholds. The thresholds can be set according to actual needs to accurately control the triggering criteria and determination range of the preset third, fourth, fifth, and sixth conditions. The threshold in the preset third condition is greater than the threshold in the preset fourth condition, and the threshold in the preset fifth condition is greater than the threshold in the preset sixth condition.

[0222] For example, the third preset condition is that the transformation rate is greater than 65%, and the fourth preset condition is that the transformation rate is less than -55%. If the change rate of the application data in the first fixed stack is 70%, the third preset condition is met, and the storage capacity of the application data in the first fixed stack shows a surge trend. If the change rate of the application data in the first fixed stack is -60%, the fourth preset condition is met, and the storage capacity of the application data in the first fixed stack shows a sharp decrease trend.

[0223] The fifth preset condition is that the change rate is greater than 50%, and the sixth preset condition is that the change rate is less than -50%. If the change rate of the operating system data in the second fixed stack is 51%, the fifth preset condition is met, and the storage capacity of the operating system data in the second fixed stack shows a surge trend. If the change rate of the operating system data in the second fixed stack is -53%, the sixth preset condition is met, and the storage capacity of the operating system data in the second fixed stack shows a sharp decrease trend.

[0224] In this embodiment, the operating system data and application data in the storage space are stored in different fixed stacks, which makes it easier to analyze the operating system data and application data separately and better identify the changing trends of various types of data.

[0225] In another possible scenario, when the preset frequency is low, the corresponding target monitoring data tends to present a more macroscopic and phased storage space status. In order to improve the overall monitoring capability of the storage space, Figure 13 The following are schematic flowcharts illustrating storage space monitoring methods provided in other embodiments of this application, such as... Figure 13 As shown in the embodiments of this application, the method for monitoring storage space includes the following steps:

[0226] S610, the second monitoring data obtained.

[0227] The second monitoring data is the data obtained when monitoring the storage space at a preset second frequency, and the preset second frequency is less than the preset first frequency. For example, the preset second frequency is once every 12 hours, once a day, once every 2 days, etc.

[0228] It should be understood that when the storage space is monitored at a preset second frequency, the target monitoring data obtained is the second monitoring data; the second monitoring data is data that is periodically monitored and obtained by monitoring the storage space at fixed time intervals; by using the second monitoring data to reflect the status of the storage space in stages, we can understand the user's usage habits of the storage space during the use of electronic devices.

[0229] It should be noted that the second monitoring data is a complete dataset, containing all data records within the corresponding range. It is a complete collection with no missing or incomplete data. It should be understood that the information in the second monitoring data is more detailed and comprehensive than that in the first monitoring data. The second monitoring data includes data related to the operating system and all applications installed on the electronic devices.

[0230] The second monitoring data may include one or more point data, which are data obtained by recording the data stored in the storage space at preset times. At this time, the obtained point data can be stored in the form of a document. At preset times, such as 9:00 am and 9:00 pm every day, data collection and recording work is carried out on the operating system data and application data in the storage space at fixed and regular time points.

[0231] For example, the second monitoring data is acquired once a day at a preset second frequency, i.e., daily statistics. At 12 noon every day, detailed information of operating system data and application data in the storage space is acquired to form a daily statistical file, i.e., the second monitoring data. Figure 14 A schematic diagram of the structure of the second monitoring data in an embodiment of this application is shown, as follows: Figure 14 As shown, this second monitoring data was acquired on October 25, 2024, and includes data on all applications and the operating system in the storage space. Each data point displays detailed information, including at least the package name and storage capacity.

[0232] S620: Analyze the second monitoring data based on the preset first model to determine whether the second data to be detected conforms to the user's usage habits.

[0233] The second data to be detected refers to the point data involved in the second monitoring data.

[0234] The first pre-defined model is the large model on the electronic device side (i.e., the terminal side). The first pre-defined model is built based on the usage habits of electronic device users (i.e., users) and the corresponding storage space usage. The first pre-defined model learns and analyzes the user's usage habits, such as which applications the user likes to use, and the storage capacity of the operating system and each application in the storage space during the use of the electronic device.

[0235] It should be understood that the default primary model on the electronic device side will deeply analyze the user's own behavior and storage characteristics. Therefore, the default primary model is a precise model that is closely integrated with the user's actual usage.

[0236] It should also be understood that during the power-on process of electronic devices, as the second monitoring data is continuously acquired, the preset first model will also be continuously optimized based on the second monitoring data.

[0237] Specifically, the acquired second monitoring data is imported into the preset first model. The preset first model can then process the input data based on its complex computing logic and intelligent analysis capabilities, thereby accurately determining whether the second data to be detected conforms to the user's usage habits and outputting a definite result.

[0238] It should also be understood that during the daily use of electronic devices, the applications installed on them are in a dynamic state of change. They are added as users need and operate, or uninstalled for various reasons. Therefore, when a new application appears, the first model will rely on its own learning mechanism to learn and master the usage habits of the new application.

[0239] Therefore, when entirely new data appears in the second monitoring data, it does not immediately determine whether this new data conforms to the user's usage habits. Instead, it allows sufficient time for the first preset model to fully learn and summarize the usage habits of the application associated with the new data. Then, it accurately determines whether the new data conforms to the user's habits.

[0240] S641. If the output of the first model indicates that the second monitoring data contains second data to be detected that does not conform to the user's usage habits, it is determined that there is abnormal storage space usage.

[0241] The output of the first preset model indicates that the second data to be tested does not conform to the user's usage habits, which can determine that there is an anomaly in the storage space; the output of the first preset model also includes specific information about the corresponding data, such as the application package name, storage capacity, date, etc.

[0242] It should also be understood that the second piece of data to be detected that does not conform to the user's usage habits can be one or more pieces of data. For example, there may be an anomaly in the storage capacity of one or more applications.

[0243] S650: Based on abnormal storage space usage, generate warning commands to indicate storage abnormalities.

[0244] S660: Displays storage anomaly warnings on electronic devices based on alert commands.

[0245] For details on the implementation of steps 650 and 660, please refer to the detailed description of step 430 above, which will not be repeated here.

[0246] This application embodiment can learn about users' usage habits of various applications and the storage space usage corresponding to these usage habits through long-term learning of a preset first large model. Therefore, the second monitoring data can be analyzed by the preset first large model to determine whether there is any second data to be detected in the second monitoring data that does not conform to the user's system usage. In other words, the analysis of usage habits helps to identify abnormal storage space usage.

[0247] The above embodiments analyze the second monitoring data using a preset first major model, which is based on the specific user's usage habits. However, different users have different usage habits for their electronic devices. In other words, the preset first major model may have different usage habits for the same application for different users' electronic devices. If storage usage analysis is performed solely based on the preset first major model of the electronic device (i.e., the terminal side), misjudgments may occur.

[0248] For example, for user A's electronic device, the storage capacity corresponding to the usage habits of application C in the preset first model is between 5GB and 8GB; for user B's electronic device, the storage capacity corresponding to the usage habits of application C in the preset first model is between 10GB and 30GB.

[0249] If the storage capacity of application C is detected to be 19GB, for user A's electronic device, the first preset model determines that the storage capacity corresponding to application C exceeds the storage capacity corresponding to the user's usage habits, indicating abnormal usage; while for user B's electronic device, the first preset model determines that the storage capacity corresponding to application C does not exceed the storage capacity corresponding to the user's usage habits, indicating no abnormal usage.

[0250] Although User A's electronic device detected abnormal storage usage of 19GB for application C using the preset first model, this storage capacity is still within the normal range. Therefore, to improve the accuracy of the second monitoring data analysis based on user habits, corresponding usage habit analysis can also be added on the cloud side. Figure 15 The following are schematic flowcharts illustrating storage space monitoring methods provided in other embodiments of this application, such as... Figure 15 As shown in the embodiments of this application, the method for monitoring storage space further includes the following steps:

[0251] S610, the second monitoring data obtained.

[0252] S620: Analyze the second monitoring data based on the preset first model to determine whether the second data to be detected conforms to the user's usage habits.

[0253] S630: Send the second monitoring data to the cloud side so that the cloud side can analyze the second monitoring data based on the preset second major model and feed back the results output by the preset second major model to the electronic device.

[0254] The second major model is a cloud-based model. This model is built on the cloud side based on the usage habits of the entire user group and their corresponding storage space usage. By learning and analyzing the usage habits of the entire user group, this model provides a broader range of usage guidelines.

[0255] The cloud can be configured with a database that collects a very large amount of sample data about the entire user group. The number of sample data can be tens of thousands or even more. This sample data includes the storage capacity occupied by applications and the storage capacity occupied by the operating system. For example, the storage capacity occupied by instant messaging applications is usually in the range of 15GB to 50GB according to user habits.

[0256] It should be understood that the second and first preset models are two independent models, and there is no data interaction or mutual learning between them.

[0257] In some embodiments, the preset second model can also perform classification analysis for different electronic device models. For example, for the user group of model X, application A corresponds to a first range of storage space; for the user group of model Y, application A corresponds to a second range of storage space. It should be understood that these two ranges may be similar or may have significant differences.

[0258] It should be understood that the cloud-based preset second model will deeply analyze the behavior and storage characteristics of its entire user group. Therefore, the preset second model may differ from a user's actual usage. However, the preset second model can provide the storage space usage range corresponding to all possible and reasonable usage habits for each user's second monitoring data.

[0259] It should also be understood that different types of devices under the same category of electronic devices will continuously send their secondary monitoring data to the cloud. In the case of mobile phones, there are various brands and models of terminal devices. Each terminal device will send the secondary monitoring data it acquires to the cloud, so that the preset secondary model will be continuously optimized based on the received secondary monitoring data.

[0260] Specifically, the second monitoring data acquired by electronic device A is sent to the cloud. The cloud then processes the input data using the complex computational logic and intelligent analysis capabilities of the pre-set second model, thereby accurately determining whether the second data to be detected conforms to the user group's usage habits, outputting the determination result, and feeding the determination result back to the electronic device.

[0261] S642. If the results of the first preset model and the second preset model both indicate that the second data to be detected does not conform to usage habits, it is determined that there is abnormal storage space usage.

[0262] It should be understood that the second analysis result is determined by the outputs of the first and second preset major models. Therefore, if both the outputs of the first and second preset major models indicate that the second data to be tested does not conform to usage habits, the resulting second analysis result indicates abnormal storage space usage.

[0263] If one or more data points in the second monitoring data do not conform to the user group's usage habits and exceed the range corresponding to the storage capacity of the application used by a typical user, it indicates abnormal use of storage space, and outputs specific information about the corresponding data, such as the application's package name, storage capacity, date, etc.

[0264] The results output by the first preset model indicate that the first data to be tested does not conform to the user's usage habits, and the results output by the second preset model indicate that the second data to be tested does not conform to the user group's usage habits. Furthermore, the first and second data to be tested correspond to the same application or operating system, which indicates that there is an anomaly in the storage space. The results output by the first preset model also include specific information about the corresponding data, such as the application's package name, storage capacity, and date.

[0265] S650: Based on abnormal storage space usage, generate warning commands to indicate storage abnormalities.

[0266] S660: Displays storage anomaly warnings on electronic devices based on alert commands.

[0267] Storage anomaly warnings are presented in the form of pop-up windows. For example, during the phone's boot process, if the monitoring method of this embodiment detects that application C is abnormally occupying storage space, a pop-up window will appear on the current display screen, displaying: "Application C has abnormally occupied storage space on XX date".

[0268] For details on the implementation of steps 650 and 660, please refer to the detailed description of step 430 above, which will not be repeated here.

[0269] This application embodiment sets up a preset second model on the cloud side to analyze the usage habits of the user group, and integrates the results with the results on the terminal side. This improves the accuracy of the analysis of the second monitoring data and enhances the user experience, even when there are differences in the usage habits of different users, or even large differences.

[0270] In another possible scenario, to improve the monitoring capability of storage space, the storage space monitoring method provided in this application embodiment can simultaneously perform real-time monitoring and periodic monitoring of the storage space. The target monitoring data includes first monitoring data and second monitoring data, wherein the first monitoring data is data obtained from the storage space at a preset first frequency; the second monitoring data is data obtained from the storage space at a preset second frequency; and the preset first frequency is greater than the preset second frequency. Figure 16 The following are schematic flowcharts illustrating storage space monitoring methods provided in other embodiments of this application, such as... Figure 16 As shown, Figure 8 and Figure 15 The monitoring methods are combined.

[0271] exist Figure 8 Step 520 analyzes the first monitoring data and determines whether the first data to be detected in the first monitoring data shows a surge trend and / or a sharp decrease trend, and then obtains the first analysis result.

[0272] exist Figure 15 Step 620 analyzes the second monitoring data based on a preset first large model; and step 630, after the cloud side analyzes the second monitoring data based on a preset second large model, obtains the second analysis result.

[0273] Then, after the above steps, perform the following:

[0274] S710. At least one of the first analysis result and the second analysis result indicates that there is abnormal storage space usage, and a warning instruction is generated to indicate the storage abnormality.

[0275] In other words, if the first data to be detected shows a surge in change and then a sharp decrease in change within a preset time period, the first analysis result indicates abnormal storage space usage. Similarly, if the results from both the preset first and second largest models indicate that the second data to be detected does not conform to usage habits, the second analysis result indicates abnormal storage space usage.

[0276] Furthermore, a warning instruction will be generated if either the first analysis result indicates abnormal storage space usage, or the second analysis result indicates abnormal storage space usage, or if both the first and second analysis results indicate abnormal storage space usage.

[0277] It should be noted that the warning instructions may differ under different circumstances, so that users can distinguish the reasons for abnormal usage.

[0278] S720: Displays storage anomaly warnings on electronic devices based on alert commands.

[0279] If a storage anomaly warning is displayed as a pop-up window, for example, during the phone's boot process, if the monitoring method of this embodiment detects that application C is abnormally occupying storage space, a pop-up window will appear on the current display interface, displaying a specific pattern, such as an exclamation mark, and a warning message, such as "Application C is abnormally occupying storage space".

[0280] The storage space monitoring method provided in this application embodiment actively monitors and periodically detects the storage space in real time when the electronic device is powered on. It analyzes abnormal occupancy in the storage space from multiple perspectives, thereby improving the accuracy of storage space monitoring. Furthermore, through various active detection methods for the storage space, it can quickly and accurately grasp changes in the storage space, capture abnormal occupancy in the storage space, improve control over the storage space, reduce the impact of abnormal occupancy on the operation of the electronic device, and improve the stability and user experience of the electronic device.

[0281] In one possible scenario, the system architecture of electronic devices is as follows: Figure 3 As shown, this includes a storage performance monitoring module, a data maintenance testing module, and a smart analysis module. When the electronic device is in use, the storage performance monitoring module monitors the storage space in real time, and the data maintenance testing module monitors the storage space periodically. The first monitoring data obtained from real-time monitoring and the second monitoring data obtained from periodic monitoring are then transmitted to the smart analysis module. The smart analysis module performs storage occupancy analysis on the first monitoring data to obtain a first analysis result; the smart analysis module also performs storage occupancy analysis on the second monitoring data to obtain a second analysis result. If at least one of the first and second analysis results indicates abnormal storage space occupancy, a warning command indicating a storage anomaly is generated. The following describes... Figure 17 The embodiments shown will be described in detail.

[0282] Figure 17 The following are schematic flowcharts illustrating storage space monitoring methods provided in other embodiments of this application, such as... Figure 17 As shown, the monitoring method for this storage space includes the following steps:

[0283] The S810 storage performance monitoring module monitors the storage space and obtains the first monitoring data.

[0284] It should be understood that the storage performance monitoring module is used to manage and control the storage performance of the storage space in real time. Specifically, it can view and retrieve data from the non-volatile memory in the hardware through the storage access interface in the framework layer, thereby obtaining data in the storage space; then, it monitors and stores the data in the storage space that is sorted in descending order of storage capacity, thus obtaining the first monitoring data.

[0285] The storage performance monitoring module, also known as the power-saving wizard, is a module used to optimize the performance of electronic devices. It focuses on optimizing CPU scheduling, memory management, software resource management, and application management to solve problems such as disordered operation caused by resource misuse and contention, unreleased associated startups, and frequent wake-ups; as well as the accumulation and expansion of data cache and useless temporary files, and the accumulation of file system fragmentation, thereby improving the overall performance of electronic devices.

[0286] To ensure the performance of electronic devices, the Power Saving Wizard implements multi-dimensional control measures: In CPU scheduling, it isolates foreground and background processes through physical cores, accurately identifies background processes and assigns them to corresponding background task groups, allowing foreground operations such as launching and scrolling to immediately increase their operating frequency, ensuring a good user experience; in memory management, it ensures that the system has a certain amount of free memory; in software resource management, it reduces the load on the system server from background applications by using ordered broadcast proxies to target timeout applications and classifies applications according to broadcast rate, ensuring the responsiveness of foreground software resources; in application management, it prevents the wrong killing of system services and identifies malicious behavior of applications that affect system performance by controlling the launch of applications, reducing the impact of background processes on foreground performance and comprehensively improving overall performance.

[0287] In this embodiment, the power-saving tool adds control over the storage capacity usage in the storage space, and can obtain and update the first monitoring data of the storage space in real time, which facilitates the electronic device to actively monitor the storage space.

[0288] In some embodiments, "power saving wizard" can refer to software in an electronic device.

[0289] The S820 data maintenance test module monitors the storage space and obtains the second monitoring data.

[0290] It should be understood that the data maintenance and testing module is used to periodically manage the storage performance of the storage space. Specifically, it can access the non-volatile memory in the hardware through the storage access interface in the framework layer to view and retrieve data, thereby obtaining data from the storage space. Furthermore, it can track storage space usage according to a periodic monitoring time dimension. That is, at pre-set time intervals, it collects and records operating system data and application data from the storage space. For example, if the preset second frequency is once a day (i.e., daily statistics), detailed information on operating system data and application data from the storage space is obtained at fixed and regular times of 9:00 AM and 9:00 PM every day, forming a daily record file, which is the second monitoring data. This second monitoring data is then sent to the cloud. It should be understood that the second monitoring data is complete data, including data corresponding to the operating system and all applications installed on the electronic device.

[0291] Among them, data logging is a method of data collection and recording. In scenarios where storage space is monitored regularly, data logging acts like fixed checkpoints set on a timeline, recording various relevant data in the storage space.

[0292] It should be understood that the second monitoring data is usually stored and transmitted in the form of a file, and this file may also be encrypted.

[0293] Figure 18 This illustration shows a schematic diagram of a data maintenance testing module in an electronic device according to an embodiment of this application. The data maintenance testing module is used for fault diagnosis and statistics in the electronic device, and it provides functions such as data acquisition and uploading. Figure 18 As shown, the data maintenance test module includes an end-side (electronic device) and a cloud-side (server). The end-side sends the acquired second monitoring data to the cloud-side, which facilitates the analysis of the second monitoring data by the preset first large model in the end-side and the preset second large model in the cloud-side.

[0294] In some embodiments, the data maintenance test module may refer to Hiview in an electronic device.

[0295] like Figure 17 As shown, it also includes: S830, transmitting the first monitoring data and the second monitoring data to the intelligent analysis module respectively, and the intelligent analysis module analyzes the first monitoring data and the second monitoring data respectively to obtain the first analysis result and the second analysis result.

[0296] The intelligent analysis module performs storage occupancy analysis on the first monitoring data, that is, it analyzes the first monitoring data to determine whether the first data to be detected in the first monitoring data shows a surge trend and / or a sharp decrease trend, and then obtains the first analysis result.

[0297] If the first data to be detected first shows a surge in change, and then shows a sharp decrease in change within a preset time period, the first analysis result indicates that there is abnormal storage space usage.

[0298] In addition, the intelligent analysis module performs storage occupancy analysis on the second monitoring data, that is, it analyzes the second monitoring data through the preset first major model and the preset second major model; then, based on the output results of the preset first major model and the preset second major model, it obtains the second analysis result.

[0299] If the results of the first preset model and the second preset model both indicate that the second data to be detected does not conform to usage habits, the second analysis result indicates that there is abnormal storage space usage.

[0300] Figure 19 This illustration shows a schematic diagram of a smart analysis module in an electronic device provided in an embodiment of this application, such as... Figure 19 As shown, the intelligent analysis module in the electronic device analyzes the first monitoring data and the second monitoring data, and the cloud side also analyzes the second monitoring data.

[0301] Large models are set up on both the electronic device and the cloud side, namely, a first preset large model is set on the electronic device and a second preset large model is set on the cloud side.

[0302] The intelligent analysis module is used to analyze the first monitoring data to determine whether the first data to be detected in the first monitoring data shows a surge trend and / or a sharp decline trend.

[0303] The intelligent analysis module is used to analyze the second monitoring data. It analyzes the second monitoring data through a preset first major model and a preset second major model. Based on the preset first major model, it outputs whether the second monitoring data conforms to the user's usage habits, and based on the preset second major model, it outputs whether the second monitoring data conforms to the user group's usage habits.

[0304] like Figure 17 As shown, it also includes: S840, at least one of the first analysis result and the second analysis result indicates that there is abnormal storage space occupation, and generates a warning instruction to indicate storage abnormality.

[0305] The warning command is used to present a storage anomaly alert on electronic devices.

[0306] It should be understood that if either the first analysis result or the second analysis result indicates abnormal storage space usage, or if both the first analysis result and the second analysis result indicate abnormal storage space usage, a warning instruction to indicate storage anomaly will be generated.

[0307] It should be understood that in some embodiments, the storage space can also be actively monitored by the storage performance monitoring module and the intelligent analysis module in the electronic device, or the storage space can be actively monitored by the data maintenance and testing module and the intelligent analysis module in the electronic device. For details, please refer to the detailed description in the above method embodiments, which will not be repeated here.

[0308] The storage space monitoring method provided in this application embodiment is executed by the storage performance monitoring module, data maintenance testing module, and intelligent analysis module in the electronic device. It should be understood that the storage performance monitoring module and data maintenance testing module can view and retrieve data from the non-volatile memory in the hardware through the storage access interface in the framework layer. When the electronic device is powered on, it actively monitors and periodically detects the storage space, analyzes abnormal occupancy in the storage space from multiple perspectives, and can quickly and accurately control changes in the storage space and capture abnormal occupancy in the storage space.

[0309] It should be understood that the storage space monitoring method provided in this application, while retaining the passive monitoring of storage space through system-level permission applications in related technologies, adds an active monitoring method for storage space. Figure 20 The diagram illustrates the process of triggering storage space monitoring in an electronic device, such as... Figure 20 As shown, in Figure 5Based on the system-level permission application triggering the storage space monitoring function entry shown in step 310, additional function entry points for real-time and periodic monitoring of storage space have been added, namely the real-time monitoring function of the storage performance monitoring module and the periodic monitoring function of the data maintenance testing module; during the power-on process of electronic devices, the storage space monitoring method also includes the following steps:

[0310] S910, storage performance monitoring module real-time monitoring function.

[0311] Among them, the storage performance monitoring module is the functional entry point for real-time monitoring in active monitoring. The storage performance monitoring module obtains the first monitoring data through the storage access interface based on a preset first frequency.

[0312] The S920 data maintenance test module has a periodic monitoring function.

[0313] The data maintenance testing module serves as the entry point for periodic monitoring within the proactive monitoring process. Based on a preset second frequency, the data maintenance testing module retrieves second monitoring data through the storage access interface.

[0314] Then, the data obtained by the storage performance monitoring module and the data maintenance test module are input into the intelligent analysis module, and the S930 and the intelligent analysis module perform storage occupancy analysis.

[0315] The intelligent analysis module analyzes the first monitoring data and the second monitoring data to obtain the corresponding first analysis result and / or second analysis result, which is the result of storage occupancy analysis and processing.

[0316] In the intelligent analysis module, if at least one of the first analysis result and the second analysis result indicates abnormal storage space usage, a warning instruction is generated to indicate the storage abnormality.

[0317] S940: Displays a storage anomaly warning on electronic devices.

[0318] Compared to the passive monitoring of storage space by applications with system-level permissions in related technologies, the embodiments of this application add active monitoring of storage space through storage performance monitoring module and data maintenance testing module, that is, real-time monitoring and periodic monitoring of storage space; it can control changes in storage space in advance, improve control over storage space, reduce the impact of abnormal occupation on the operation of electronic devices, and improve the stability of electronic devices and user experience.

[0319] It should be noted that in the embodiments of this application, "greater than" can be replaced with "greater than or equal to", "less than or equal to" can be replaced with "less than", or "greater than or equal to" can be replaced with "greater than", and "less than" can be replaced with "less than or equal to".

[0320] It should be understood that the sequence numbers of the processes in the above embodiments do not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention. The various embodiments described herein can be independent solutions or combinations based on internal logic, and all such solutions fall within the protection scope of this application.

[0321] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0322] It should also be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowchart may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0323] This application embodiment can divide an electronic device into functional modules based on the above method example. For example, each function can be divided into its own functional modules, or two or more functions can be integrated into one processing module. The integrated modules can be implemented in hardware or as software functional modules. It should be noted that the module division in this application embodiment is illustrative and only represents one logical functional division. In actual implementation, other feasible division methods may exist. The following description uses the division of functional modules according to each function as an example.

[0324] Figure 21 A schematic diagram of a storage space monitoring device provided in an embodiment of this application is shown. This device 50 can be used to perform the actions performed by the electronic device in the above method embodiments. For example... Figure 21 As shown, the device 50 includes a monitoring unit 51, an analysis unit 52, and a presentation unit 53.

[0325] The monitoring unit 51 is used to acquire target monitoring data, which is the data acquired when monitoring the storage space corresponding to the non-volatile memory at a preset frequency; wherein, the target monitoring data includes first monitoring data acquired in real time and second monitoring data acquired in periodic monitoring.

[0326] The analysis unit 52 is used to perform storage occupancy analysis on the target monitoring data, thereby determining whether there is abnormal storage space occupancy and obtaining the results of the storage occupancy analysis. The analysis unit 52 is also used to generate warning instructions to indicate storage abnormality based on the results of the storage occupancy analysis.

[0327] The presentation unit 53 is used to present a storage anomaly warning on the electronic device based on the warning command.

[0328] The storage space monitoring device provided in this application embodiment is used to execute the storage space monitoring method of the above embodiment. The technical principle and technical effect are similar, and will not be described again here.

[0329] It should be noted that the monitoring device 50 for the storage space of the aforementioned application is embodied in the form of a functional unit. The term "unit" here can be implemented in software and / or hardware, without specific limitations.

[0330] This application provides a computer program product that, when run on an electronic device, causes the electronic device to execute the technical solutions described in the above embodiments. Its implementation principle and technical effects are similar to those of the related embodiments described above, and will not be repeated here.

[0331] This application provides a readable storage medium containing instructions that, when executed by an electronic device, cause the electronic device to perform the technical solutions described in the above embodiments. The implementation principle and technical effects are similar and will not be repeated here.

[0332] The computer-readable storage medium and computer program product are used to execute the corresponding methods provided above. Therefore, the beneficial effects they can achieve can be referred to the beneficial effects of the corresponding methods provided above, and will not be repeated here.

[0333] It should be understood that the term "embodiment" used throughout the specification means that a specific feature, structure, or characteristic related to an embodiment is included in at least one embodiment of this application. Therefore, various embodiments throughout the specification do not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. It should be understood that in the various embodiments of this application, the sequence numbers of the above processes do not imply a sequential order of execution; the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0334] It should also be understood that in this application, “when…”, “if” and “if” all refer to the electronic device making a corresponding processing under certain objective circumstances, and are not limited to a specific time, nor do they require the electronic device to perform a specific action, nor do they imply any other limitations.

[0335] Those skilled in the art will understand that the various numerical designations such as "first," "second," etc., involved in this application are merely for the convenience of description and are not intended to limit the scope of the embodiments of this application, nor do they indicate the order of sequence.

[0336] In this application, the use of singular pronouns to denote "one or more" rather than "one and only one," unless otherwise specified. In this application, unless otherwise specified, "at least one" is intended to mean "one or more," and "more than" is intended to mean "two or more."

[0337] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can represent three cases: A exists alone, A and B exist simultaneously, and B exists alone. Here, A can be singular or plural, and B can be singular or plural.

[0338] In this document, the terms "at least one of..." or "at least one of..." refer to all or any combination of the listed items. For example, "at least one of A, B, and C" can mean: A exists alone, B exists alone, C exists alone, A and B exist simultaneously, B and C exist simultaneously, and A, B, and C exist simultaneously. A can be singular or plural, B can be singular or plural, and C can be singular or plural.

[0339] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0340] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0341] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0342] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0343] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0344] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0345] The same or similar parts between the various embodiments in this application can be referred to mutually. In the various embodiments of this application, and in the various implementation methods / methods / implementations within each embodiment, unless otherwise specified or logically conflicting, the terminology and / or descriptions between different embodiments and between the various implementation methods / methods / implementations within each embodiment are consistent and can be mutually referenced. The technical features in different embodiments and the various implementation methods / methods / implementations within each embodiment can be combined according to their inherent logical relationships to form new embodiments, implementation methods, methods, or implementation approaches. The above embodiments of this application do not constitute a limitation on the scope of protection of this application.

[0346] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims. In conclusion, the above are merely preferred embodiments of the technical solution of this application and are not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for monitoring storage space, characterized in that, Applied to electronic devices, the electronic devices including non-volatile memory; The method for monitoring the storage space includes: Acquire target monitoring data, wherein the target monitoring data is data acquired when monitoring the storage space at a preset frequency, and the storage space is the storage area corresponding to the non-volatile memory; The target monitoring data is analyzed for storage usage to determine whether there is any abnormal usage of the storage space. If the storage space is abnormally occupied, a warning command is generated to indicate the storage abnormality.

2. The method for monitoring storage space according to claim 1, characterized in that, The target monitoring data includes first monitoring data; acquiring the target monitoring data includes: The storage space is monitored at a preset first frequency to obtain N sets of storage data groups; wherein, each storage data group includes corresponding target data, and the target data is the data with the top M storage capacities when the storage space is monitored once, where N and M are positive integers greater than 1; The first monitoring data is determined based on the N sets of stored data acquired continuously.

3. The method for monitoring storage space according to claim 2, characterized in that, The storage occupancy analysis of the target monitoring data includes: Analyze the first data to be detected in the first monitoring data to determine whether the rate of change of the first data to be detected is greater than a preset first threshold or less than a preset second threshold. The first data to be detected is the data involved in the stored data group in the first monitoring data. If the rate of change of the first data to be detected is greater than the preset first threshold, and the rate of change of the first data to be detected is less than the preset second threshold within a preset time period, it is determined that there is abnormal occupancy of the storage space.

4. The method for monitoring storage space according to claim 2, characterized in that, The storage occupancy analysis of the target monitoring data includes: Analyze the first data to be detected in the first monitoring data to determine whether the rate of change of the first data to be detected is greater than a preset first threshold. The first data to be detected is the data involved in the stored data group in the first monitoring data. If the rate of change of the first data to be detected is greater than the preset first threshold, it is determined that the storage space is abnormally occupied.

5. The method for monitoring storage space according to claim 1, characterized in that, The target monitoring data includes second monitoring data; acquiring the target monitoring data includes: Data in the storage space is recorded based on a preset time to obtain point data, and the point data is stored. The data points are collected at a preset second frequency to obtain the second monitoring data, wherein the preset second frequency is less than the preset first frequency.

6. The method for monitoring storage space according to claim 5, characterized in that, The storage occupancy analysis of the target monitoring data includes: The second monitoring data is analyzed based on the first preset model to determine whether the second monitoring data conforms to the user's usage habits; If the result output by the preset first large model indicates that there is second data to be detected in the second monitoring data that does not conform to the user's usage habits, it is determined that the storage space is abnormally occupied.

7. The method for monitoring storage space according to claim 5, characterized in that, The storage occupancy analysis of the target monitoring data includes: The second monitoring data is analyzed based on the first preset model to determine whether the second monitoring data conforms to the user's usage habits; The second monitoring data is sent to the cloud side, so that the cloud side can analyze the second monitoring data based on the preset second major model, and feed back the results output by the preset second major model to the electronic device; When the results output by the preset first large model indicate that there is second data to be detected in the second monitoring data that does not conform to the user's usage habits, and the results output by the preset second large model indicate that the second data to be detected does not conform to the user group's usage habits, it is determined that there is abnormal usage of the storage space.

8. The method for monitoring storage space according to any one of claims 1 to 7, characterized in that, The target monitoring data includes first monitoring data and second monitoring data, and the result of the storage occupancy analysis is determined by the first analysis result and the second analysis result; If the storage space is abnormally occupied, the generated warning instruction to indicate the storage abnormality includes: The warning instruction is generated when at least one of the first and second analysis results indicates that the storage space is abnormally occupied. The first analysis result is the result obtained after analyzing the first monitoring data; The second analysis result is obtained by analyzing the second monitoring data based on a preset first major model, or by the preset first major model and the preset second major model.

9. The method for monitoring storage space according to any one of claims 1 to 8, characterized in that, The electronic device includes a storage performance monitoring module and an intelligent analysis module, and the method further includes: The storage performance monitoring module acquires the first monitoring data; The first monitoring data is sent to the intelligent analysis module; The intelligent analysis module analyzes the first monitoring data to obtain the corresponding first analysis result; The warning instruction is generated when the first analysis result indicates that the storage space is abnormally occupied.

10. The method for monitoring storage space according to any one of claims 1 to 9, characterized in that, The electronic device includes a data maintenance testing module and an intelligent analysis module, and the method further includes: The data maintenance test module acquires the second monitoring data; The second monitoring data is sent to the intelligent analysis module; The intelligent analysis module analyzes the second monitoring data to obtain the corresponding second analysis result; The second analysis result indicates that the storage space is abnormally occupied, and the warning instruction is generated.

11. The method for monitoring storage space according to any one of claims 1 to 10, characterized in that, The electronic device includes a storage performance monitoring module, a data maintenance testing module, and an intelligent analysis module; the method further includes: The storage performance monitoring module acquires the first monitoring data; The data maintenance test module acquires the second monitoring data; The first monitoring data and the second monitoring data are sent to the intelligent analysis module; The intelligent analysis module analyzes the first monitoring data and the second monitoring data to obtain corresponding first analysis results and second analysis results; If at least one of the first analysis results and the second analysis result indicates that the storage space is abnormally occupied, the warning instruction is generated.

12. The method for monitoring storage space according to any one of claims 1 to 11, characterized in that, The target monitoring data includes operating system data and application data in the storage space.

13. The method for monitoring storage space according to any one of claims 1 to 11, characterized in that, The target monitoring data includes application data in the storage space.

14. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory being used to store a computer program, and the processor being used to call and run the computer program from the memory, causing the electronic device to perform the method of any one of claims 1 to 13.

15. A computer program product, characterized in that, The computer program product includes a computer program that, when run, causes the method as described in any one of claims 1 to 13 to be performed.

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