Network quality evaluation method and device, electronic equipment, storage medium and program product

Abstract

The present disclosure relates to a network quality evaluation method and device, electronic equipment, storage medium and program product. The method comprises: reading, at a current time, a system-level network signal and original weak network identification information newly obtained by a terminal, wherein the system-level network signal is obtained based on a bottom-layer network signal output by a predetermined interface of the terminal, and the system-level network signal comprises information indicating whether a network accessed by the terminal is a weak network and a weak network duration when the network accessed by the terminal is a weak network, the predetermined interface is a standardized interface built in an operating system of the terminal and opened by a manufacturer, and the original weak network identification information is obtained by evaluating the network based on network attribute information of an application layer of the terminal; and in response to the system-level network signal indicating that the network is a weak network and the current time falling within the weak network duration, the original weak network identification information is modified by a preset attenuation coefficient to obtain modified weak network identification information of the terminal at the current time.

Description

Technical Field

[0001] This disclosure relates to the field of communications, and more particularly to a network quality assessment method and apparatus, electronic equipment, storage medium, and program product. Background Technology

[0002] In the field of mobile network optimization, it is often necessary to assess whether the currently accessed network is weak in order to assist in the optimization of strategies for various business scenarios. The accuracy of weak network indicators has always been a challenge for various businesses. In actual business strategy optimization, the strategy often has a negative effect due to inaccurate weak network identification. Therefore, improving the accuracy of weak network identification has become a problem that needs to be solved. Summary of the Invention

[0003] This disclosure provides a network quality assessment method and apparatus, electronic device, storage medium, and program product to at least solve the problem of inaccurate identification of weak networks in related technologies.

[0004] According to a first aspect of the present disclosure, a network quality assessment method is provided, comprising: reading the latest system-level network signal and existing weak network identification information acquired by the terminal at the current moment, wherein the system-level network signal is acquired based on the underlying network signal output by a predetermined interface of the terminal, and the system-level network signal includes information indicating whether the network accessed by the terminal is a weak network and the duration of the weak network when the network accessed by the terminal is a weak network, the predetermined interface is a standardized interface built into the terminal's operating system and opened by the manufacturer, and the existing weak network identification information is obtained by evaluating the network based on the network attribute information of the terminal's application layer; in response to the system-level network signal indicating that the network is a weak network and the current moment falls within the duration of the weak network, correcting the existing weak network identification information by a preset attenuation coefficient to obtain the corrected weak network identification information of the terminal at the current moment.

[0005] Optionally, system-level network signals are obtained in the following ways: establishing a unified interface protocol, wherein the unified interface protocol specifies the method for obtaining system-level network signals based on the underlying network signals output from a predetermined interface of any terminal; and obtaining system-level network signals through the method for obtaining system-level network signals for terminals specified in the unified interface protocol.

[0006] Optionally, the system-level network signal is acquired through the method for acquiring system-level network signals for the terminal as agreed in the unified interface protocol, including: extracting the system-level network signal from the underlying network signal in response to the underlying network signal directly output by the predetermined interface including the system-level network signal; determining whether the network accessed by the terminal is a weak network by comparing the predetermined network signal in the underlying network signal with a preset threshold in response to the underlying network signal directly output by the predetermined interface not including the system-level network signal; and determining the duration of the weak network as a preset duration in response to the information indicating that the network accessed by the terminal is a weak network.

[0007] Optionally, the original weak network identification information is corrected by a preset attenuation coefficient to obtain the corrected weak network identification information of the terminal at the current moment, including: multiplying the preset attenuation coefficient by the original weak network identification information to obtain the corrected weak network identification information of the terminal at the current moment.

[0008] Optionally, after correcting the original weak network identification information by a preset attenuation coefficient to obtain the corrected weak network identification information of the terminal at the current moment, the method further includes: in response to the corrected weak network identification information being less than a preset weak network threshold, determining that the network accessed by the terminal at the current moment is a weak network.

[0009] Optionally, the preset attenuation coefficient is the optimal attenuation coefficient obtained through randomized controlled experiments.

[0010] According to a second aspect of the present disclosure, a network quality assessment apparatus is provided, comprising: a reading unit configured to read, at the current moment, the latest system-level network signal and the original weak network identification information acquired by the terminal, wherein the system-level network signal is acquired based on the underlying network signal output by a predetermined interface of the terminal, and the system-level network signal includes information indicating whether the network accessed by the terminal is a weak network and the duration of the weak network when the network accessed by the terminal is a weak network, the predetermined interface is a standardized interface built into the terminal's operating system and opened by the manufacturer, and the original weak network identification information is obtained by evaluating the network based on the network attribute information of the terminal's application layer; and a correction unit configured to, in response to the system-level network signal indicating that the network is a weak network and the current moment falls within the duration of the weak network, correct the original weak network identification information by a preset attenuation coefficient to obtain the corrected weak network identification information of the terminal at the current moment.

[0011] Optionally, the network quality assessment device further includes: an acquisition unit configured to acquire system-level network signals by: establishing a unified interface protocol, wherein the unified interface protocol specifies the method for acquiring system-level network signals based on the underlying network signals output from a predetermined interface of any terminal; and acquiring system-level network signals by means of acquiring system-level network signals for terminals as specified in the unified interface protocol.

[0012] Optionally, the acquisition unit is further configured to: extract system-level network signals from the underlying network signals in response to the underlying network signals directly output by the predetermined interface including system-level network signals; determine whether the network accessed by the terminal is a weak network by comparing the predetermined network signals in the underlying network signals with a preset threshold in response to the underlying network signals directly output by the predetermined interface not including system-level network signals; and determine the duration of the weak network as a preset duration in response to the information indicating that the network accessed by the terminal is a weak network.

[0013] Optionally, the correction unit is also configured to multiply a preset attenuation coefficient by the original weak network identification information to obtain the corrected weak network identification information of the terminal at the current moment.

[0014] Optionally, the correction unit is further configured to, after correcting the original weak network identification information by a preset attenuation coefficient to obtain the corrected weak network identification information of the terminal at the current moment, determine that the network accessed by the terminal at the current moment is a weak network in response to the fact that the corrected weak network identification information is less than a preset weak network threshold.

[0015] Optionally, the aforementioned preset attenuation coefficient is the optimal attenuation coefficient obtained through a randomized controlled experiment.

[0016] According to a third aspect of the present disclosure, an electronic device is provided, comprising: at least one processor; and at least one memory storing computer-executable instructions, wherein the computer-executable instructions, when executed by the at least one processor, cause the at least one processor to perform the network quality assessment method as described above.

[0017] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided that, when instructions in the computer-readable storage medium are executed by at least one processor, causes at least one processor to perform the network quality assessment method as described above.

[0018] According to a fifth aspect of the present disclosure, a computer program product is provided, including computer instructions that, when executed by a processor, implement the network quality assessment method as described above.

[0019] The technical solutions provided by the embodiments of this disclosure bring at least the following beneficial effects: According to the network quality assessment method, apparatus, electronic device, storage medium, and program product disclosed herein, based on the assessment of whether the network is weak using application-layer network attribute information, a second assessment of whether the network is weak is conducted by combining system-level network signals obtained from the terminal's underlying network signals (i.e., information indicating whether the network accessed by the terminal is a weak network and the duration of the weak network when the network accessed by the terminal is a weak network). If the second assessment result indicates a weak network, the original weak network identification result is corrected by a preset attenuation coefficient, thereby improving the accuracy of weak network identification. Therefore, this disclosure solves the problem of inaccurate weak network identification in related technologies.

[0020] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0021] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.

[0022] Figure 1 This is a flowchart illustrating a network quality assessment method according to exemplary embodiments of the present disclosure; Figure 2 This is a system flowchart illustrating a network quality assessment according to an exemplary embodiment of the present disclosure; Figure 3 This is a block diagram illustrating a network quality assessment apparatus according to exemplary embodiments of the present disclosure; Figure 4 This is a diagram illustrating a computing environment coupled to a user interface according to exemplary embodiments of the present disclosure. Detailed Implementation

[0023] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0024] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following examples do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0025] It should be noted that the phrase "at least one of several items" in this disclosure refers to three parallel cases: "any one of the several items", "a combination of any number of the several items", and "all of the several items". For example, "including at least one of A and B" includes the following three parallel cases: (1) including A; (2) including B; (3) including A and B. Another example is "performing at least one of step one and step two", which means the following three parallel cases: (1) performing step one; (2) performing step two; (3) performing both step one and step two.

[0026] Currently, network attribute information from the application layer of the terminal is often used to directly assess whether the network accessed by the terminal is weak. The network attribute information used can be round-trip time (RTT), download speed, packet loss rate, etc.

[0027] However, the network connection status of a terminal is generally either a Wi-Fi connection or a mobile network connection. Therefore, as a business application layer, network attribute information (such as RTT, download speed, packet loss rate, etc.) is actually the final result of the comprehensive performance of the terminal system layer's network indicators. If the underlying network indicators of the terminal system layer cannot be perceived, it will generally lead to two problems: 1) When the underlying network indicators of the terminal system layer change, the business application layer often has not yet perceived it, resulting in insufficient timeliness; 2) It is impossible to assess how long the current weak network will last, because the business application layer can only see the final result.

[0028] To address the aforementioned issues, this disclosure provides a network quality assessment method. Building upon the assessment of network weakness using historical network attributes from the application layer, this method further enhances the accuracy of weak network identification by incorporating system-level network signals acquired from the terminal's underlying network signals. Specifically, based on the original weak network identification information determined by application layer network attribute information, a second assessment of network weakness is conducted by combining system-level network signals acquired from the terminal's underlying network signals (i.e., information indicating whether the network accessed by the terminal is weak and the duration of the weak network when the accessed network is weak). If the second assessment indicates a weak network, the original weak network identification result is corrected using a preset attenuation coefficient, thereby improving the accuracy of weak network identification.

[0029] The network quality assessment method and apparatus, electronic device, storage medium, and program product according to exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings.

[0030] Figure 1 This is a flowchart illustrating a network quality assessment method according to exemplary embodiments of the present disclosure, such as... Figure 1 As shown, the network quality assessment method includes the following steps: In step S101, the latest system-level network signal and the original weak network identification information acquired by the terminal are read at the current time. The system-level network signal is acquired based on the underlying network signal output by the terminal's predetermined interface, and the system-level network signal includes information indicating whether the network accessed by the terminal is a weak network and the duration of the weak network when the network accessed by the terminal is a weak network. The predetermined interface is a standardized interface built into the terminal's operating system and opened by the manufacturer. The original weak network identification information is obtained by evaluating the network based on the network attribute information of the terminal's application layer.

[0031] In step S102, in response to the system-level network signal indicating that the network is a weak network and the current time falls within the duration of the weak network, the original weak network identification information is corrected by a preset attenuation coefficient to obtain the corrected weak network identification information of the terminal at the current time.

[0032] As an example, the aforementioned underlying network signals are signals output from standardized interfaces built into the terminal's operating system and provided by the manufacturer. Specifically, the terminal's baseband chip is responsible for core communication processing tasks such as demodulation and decoding of wireless signals, generating the most basic communication signal data. This raw signal data is then encapsulated, de-identified, and subject to access control through the terminal's operating system's communication protocol stack and underlying system services, ultimately being provided to upper-layer applications in a standardized interface format. Therefore, the underlying network signals in this embodiment (i.e., the underlying signal data provided by the manufacturer that can be obtained) are the result after being relayed and output by the operating system, that is, signals output by standardized interfaces.

[0033] As an example, the network attribute information mentioned above may include, but is not limited to, RTT, download speed, packet loss rate, etc. For example, taking download speed as a network attribute, if the download speed at the current moment reaches 1MB / s, the network's evaluation result at the current moment (i.e., the original weak network identification information) is 100 points; if the download speed at the current moment is 150KB / s, after linear mapping, the network's evaluation result at the current moment is 150 / 1024, approximately 14.6 points. If only this evaluation result is relied upon for weak network identification, then if the network's evaluation result at the current moment is lower than a certain score (such as 20 points), it can be identified as a weak network, and thus the network at the current moment will be evaluated and identified as a weak network.

[0034] As an example, taking the application's background processing module as the executor, the aforementioned weak network identification information can be periodically acquired and stored by the background processing module at a predetermined cycle, or it can be acquired and stored based on an acquisition request. This information can then be directly retrieved when needed. This disclosure does not limit this approach. Similarly, the aforementioned system-level network signal can also be periodically acquired and stored by the background processing module at a predetermined cycle. The difference is that the system-level network signal can also be obtained after the terminal becomes aware of changes in the original communication signal data, outputting the underlying network signal through a standardized interface, and obtaining the system-level network signal based on this underlying network signal. This system-level network signal is then communicated to the background processing module, which receives and stores it. This system-level network signal can then be directly retrieved when needed. This disclosure does not limit this approach either.

[0035] As an example, this assumes that the original weak network identification information has a score of 0-100, and the most recently acquired original weak network identification information at the current moment is 24. Based on the original evaluation strategy that considers a score below 20 as a weak network, the network currently accessed by the terminal would not be judged as a weak network. However, this embodiment also considers system-level network signals. Here, it is assumed that the system-level network signal acquired 3 seconds ago is a weak network with a duration of 5 seconds. If the current moment is still within the weak network duration, then the current moment is considered to have hit a system-level network signal. At this point, a preset attenuation coefficient is applied to correct the original weak network identification information to obtain the terminal's corrected weak network identification information at the current moment. Based on this corrected weak network identification information, it is then determined whether the network currently accessed by the terminal is a weak network.

[0036] It should be noted that if the duration of the weak network does not fall within the system-level network signal at the current moment, it is determined that the system-level network signal has not been hit at the current moment, and there is no need to correct the original weak network identification information.

[0037] According to an exemplary embodiment of this disclosure, the system-level network signal in step S101 above can be obtained in the following way: establishing a unified interface protocol, wherein the unified interface protocol specifies the method for obtaining system-level network signals based on the underlying network signals output by a predetermined interface of any terminal; and obtaining system-level network signals through the method for obtaining system-level network signals for terminals specified in the unified interface protocol.

[0038] This embodiment establishes a unified interface protocol for terminals, facilitating the overlay of system-level network signals on top of existing ones, thus avoiding inconsistencies in the capabilities and interfaces provided by different terminal manufacturers.

[0039] As an example, the method for obtaining system-level network signals from the underlying network signals output by a predetermined interface of the terminal can be agreed in advance. For example, if the underlying network signals output by the predetermined interface directly contain system-level network signals, it can be agreed to directly extract the system-level network signals. If the underlying network signals output by the predetermined interface do not directly contain system-level network signals, the system-level network signals can be obtained from the predetermined network signals in the underlying network signals through key threshold checkpoint mapping. The specific acquisition method is not limited in this disclosure.

[0040] According to an exemplary embodiment of this disclosure, the acquisition of system-level network signals through the method of acquiring system-level network signals for the terminal as agreed in the unified interface protocol may include: extracting system-level network signals from the underlying network signals in response to the underlying network signals directly output by the predetermined interface including system-level network signals; determining whether the network accessed by the terminal is a weak network by comparing the predetermined network signals in the underlying network signals with a preset threshold in response to the underlying network signals directly output by the predetermined interface not including system-level network signals; and determining the duration of the weak network as a preset duration in response to the information indicating that the network accessed by the terminal is a weak network.

[0041] In this embodiment, for cases where direct output of system-level network signals is not supported, parameter consistency can be ensured through key threshold mapping.

[0042] As an example, for some terminals that do not support direct output of system-level network signals, system-level network signals can be obtained through key threshold mapping. For instance, some terminals' underlying network signals only contain a network signal strength (e.g., strength 1-5). In this case, it can be agreed that when the network signal strength is <2, the information indicating whether the network accessed by the terminal is a weak network is "weak network," and the default duration of the weak network is agreed to be 15 seconds. Then, the final mapped system-level network signal will be: weak network, duration 15 seconds.

[0043] It should be noted that the default duration of the weak network can be determined based on randomized controlled experiments or experience, and this disclosure does not limit it.

[0044] According to an exemplary embodiment of this disclosure, the step S102 above, which corrects the original weak network identification information by a preset attenuation coefficient to obtain the corrected weak network identification information of the terminal at the current moment, may include: multiplying the preset attenuation coefficient by the original weak network identification information to obtain the corrected weak network identification information of the terminal at the current moment.

[0045] This embodiment allows for convenient and quick correction of existing weak network identification information.

[0046] As an example, assuming the original weak network identification information is 24 and the preset attenuation coefficient is 0.8, the corrected weak network identification information is 24 × 0.8 = 19.2.

[0047] According to an exemplary embodiment of this disclosure, the preset attenuation coefficient in step S102 above can be the optimal attenuation coefficient obtained through a randomized controlled experiment. Through this embodiment, the optimal attenuation coefficient can be determined using a randomized controlled experiment.

[0048] As an example, after obtaining the system-level network signal, if the indication information in the system-level network signal indicates a weak network, an online randomized controlled experiment (A / B experiment) can be conducted for the system-level network signal. That is, the original weak network identification information is multiplied by different attenuation coefficients to obtain multiple different corrected weak network identification information. Then, the attenuation coefficient corresponding to the corrected weak network identification information with the highest accuracy is determined as the optimal attenuation coefficient for the system-level network signal.

[0049] It should be noted that randomized controlled experiments (A / B experiments) can also be performed in advance for the same terminal from each manufacturer to obtain the optimal attenuation coefficient for that terminal from that manufacturer, and then uniformly applied to the network quality assessment of that terminal from that manufacturer. This disclosure does not limit this.

[0050] It should be noted that the original weak network identification information can also be modified in other ways. For example, the attenuation coefficient can be subtracted from the original weak network identification. The specific method can be determined based on the method of obtaining the attenuation coefficient. In this case, a randomized controlled experiment needs to be conducted by subtracting the attenuation coefficient. The present disclosure does not limit this.

[0051] According to an exemplary embodiment of this disclosure, in step S102 above, the original weak network identification information is corrected by a preset attenuation coefficient to obtain the corrected weak network identification information of the terminal at the current moment. In response to the fact that the corrected weak network identification information is less than the preset weak network threshold, the network accessed by the terminal at the current moment is determined to be a weak network.

[0052] By using the corrected weak network identification information to determine whether a network is weak, a relatively accurate weak network result can be obtained.

[0053] As an example, suppose the corrected weak network identification information is 19.2, which is less than the preset weak network threshold of 20. Therefore, after optimization, the network accessed by the terminal at the current moment is determined to be a weak network.

[0054] To better understand this disclosure, the following is in conjunction with... Figure 2 Provide a systematic explanation.

[0055] Figure 2This demonstrates a system process for network quality assessment, such as... Figure 2 As shown, before implementing this system flow, a unified interface protocol for terminals needs to be established in advance, agreeing to obtain two key indicators from the terminal side: whether the network is weak and the duration of the weak network. For example, for some terminals that do not directly output these two indicators, it is agreed that these two key indicators can be converted through key threshold mapping.

[0056] Then, the system process of this embodiment can be started at any time, and the system process includes the following steps: Step 1: Obtain the most recently acquired weak network identification information at the current time. Assume that the original weak network identification information is 24.

[0057] Step 2: Obtain the system-level network signal (also known as the vendor-side weak network signal) through the unified interface layer (i.e., the unified interface protocol). Assume that the system-level network signal obtained 3 seconds ago is the most recent system-level network signal, and that this system-level network signal is a weak network with a duration of 5 seconds.

[0058] It should be noted that after obtaining the system-level network signal, if the indication information in the system-level network signal indicates a weak network, an online randomized controlled experiment (AB experiment) is conducted for the system-level network signal. That is, the original weak network identification information is multiplied by different attenuation coefficients to obtain multiple different corrected weak network identification information. Then, the attenuation coefficient corresponding to the corrected weak network identification information with the highest accuracy is determined as the optimal attenuation coefficient for the system-level network signal.

[0059] Step 3: Determine whether the current moment matches the system-level network signal, i.e., whether the current moment falls within the weak network duration of the system-level network signal. If the current moment falls within the weak network duration of the system-level network signal, then the current moment matches the system-level network signal, and proceed to Step 4. If the current moment does not fall within the weak network duration of the system-level network signal, then the current moment does not match the system-level network signal, and there is no need to correct the original weak network identification information, proceed to Step 5.

[0060] Step 4 applies the optimal attenuation coefficient to the original weak network identification information, that is, multiplies the original weak network identification information by the attenuation coefficient to obtain the corrected weak network identification information as 24×0.8=19.2, so as to re-evaluate whether it is a weak network.

[0061] Step 5: If the duration of the weak network signal falls within the system-level network signal at the current moment, determine whether it is a weak network based on the corrected weak network identification information and the preset weak network threshold (assumed to be 20). For example, if 19.2 < 20, then after optimization, the network accessed by the terminal at the current moment is determined to be a weak network, proceeding to step 6. Alternatively, if the corrected weak network identification information is not less than 20, then the network accessed by the terminal at the current moment can be determined to be not a weak network, proceeding to step 7. If the duration of the weak network signal does not fall within the system-level network signal at the current moment, determine whether it is a weak network based on the original weak network identification information and the preset weak network threshold (assumed to be 20).

[0062] Step 6: The network that the terminal is currently connected to is a weak network.

[0063] Step 7: The network that the terminal is currently connected to is not a weak network.

[0064] This embodiment improves the accuracy of weak network identification by comprehensively optimizing the calculation of the original weak network index by combining the system-level network signal of the terminal. Furthermore, after implementing this embodiment, the accuracy of weak network identification is improved on terminals from different manufacturers, with an average improvement of about 5%.

[0065] Figure 3 This is a block diagram illustrating a network quality assessment apparatus according to exemplary embodiments of the present disclosure. (Refer to...) Figure 3 The device includes a reading unit 30 and a correction unit 32.

[0066] The reading unit 30 is configured to read the latest system-level network signal and the original weak network identification information acquired by the terminal at the current moment. The system-level network signal is obtained from the underlying network signal output by the terminal's predetermined interface, and the system-level network signal includes information indicating whether the network accessed by the terminal is a weak network and the duration of the weak network when the network accessed by the terminal is a weak network. The predetermined interface is a standardized interface built into the terminal's operating system and opened by the manufacturer. The original weak network identification information is obtained by evaluating the network based on the network attribute information of the terminal's application layer. The correction unit 32 is configured to, in response to the system-level network signal indicating that the network is a weak network and the current moment falls within the duration of the weak network, correct the original weak network identification information by a preset attenuation coefficient to obtain the corrected weak network identification information of the terminal at the current moment.

[0067] According to an exemplary embodiment of this disclosure, the network quality assessment apparatus further includes: an acquisition unit configured to acquire system-level network signals by: establishing a unified interface protocol, wherein the unified interface protocol specifies a method for acquiring system-level network signals based on the underlying network signals output from a predetermined interface of any terminal; and acquiring system-level network signals by means of acquiring system-level network signals for terminals as specified in the unified interface protocol.

[0068] According to an exemplary embodiment of this disclosure, the acquisition unit is further configured to: extract system-level network signals from the underlying network signals in response to the underlying network signals directly output by the predetermined interface including system-level network signals; determine whether the network accessed by the terminal is a weak network by comparing the predetermined network signals in the underlying network signals with a preset threshold in response to the underlying network signals directly output by the predetermined interface not including system-level network signals; and determine the duration of the weak network as a preset duration in response to the information indicating that the network accessed by the terminal is a weak network.

[0069] According to an exemplary embodiment of this disclosure, the correction unit 32 is further configured to multiply a preset attenuation coefficient by the original weak network identification information to obtain the corrected weak network identification information of the terminal at the current moment.

[0070] According to an exemplary embodiment of this disclosure, the correction unit 32 is further configured to, after correcting the original weak network identification information by a preset attenuation coefficient to obtain the corrected weak network identification information of the terminal at the current moment, determine that the network accessed by the terminal at the current moment is a weak network in response to the fact that the corrected weak network identification information is less than a preset weak network threshold.

[0071] According to an exemplary embodiment of this disclosure, the aforementioned preset attenuation coefficient is the optimal attenuation coefficient obtained through a randomized controlled experiment.

[0072] Figure 4 A computing environment 410 coupled to a user interface 450 is shown. The computing environment 410 may be part of a data processing server. The computing environment 410 includes a processor 420, memory 430, and input / output (I / O) interface 440.

[0073] Processor 420 typically controls the overall operation of computing environment 410, such as operations associated with display, data acquisition, data communication, and image processing. Processor 420 may include one or more processors for executing instructions to perform all or some of the steps in the methods described above. Furthermore, processor 420 may include one or more modules that facilitate interaction between processor 420 and other components. The processor may be a central processing unit (CPU), microprocessor, microcontroller, graphics processing unit (GPU), etc.

[0074] Memory 430 is configured to store various types of data to support the operation of computing environment 410. Memory 430 may include predefined software 432. Examples of such data include instructions for any application or method operating on computing environment 410, video datasets, image data, etc. Memory 430 can be implemented using any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0075] I / O interface 440 provides an interface between processor 420 and peripheral interface modules (such as keyboard, click wheel, buttons, etc.). Buttons may include, but are not limited to, home button, start scan button, and stop scan button.

[0076] In an embodiment, the computing environment 410 may be implemented by one or more ASICs, DSPs, digital signal processing devices (DSPDs), programmable logic devices (PLDs), FPGAs, GPUs, controllers, microcontrollers, microprocessors, or other electronic components for performing the methods described above.

[0077] According to embodiments of the present disclosure, an electronic device may be provided, the electronic device including at least one memory and at least one processor, the at least one memory storing a set of computer-executable instructions, which, when executed by the at least one processor, performs a network quality assessment method according to embodiments of the present disclosure.

[0078] As an example, the electronic device can be a PC, tablet, personal digital assistant, smartphone, or other device capable of executing the aforementioned set of instructions. Here, the electronic device 1000 is not necessarily a single electronic device, but can be any collection of devices or circuits capable of executing the aforementioned instructions (or instruction sets) individually or in combination. The electronic device can also be part of an integrated control system or system manager, or can be configured to interconnect with a portable electronic device locally or remotely (e.g., via wireless transmission) through an interface.

[0079] In addition, electronic devices may include video displays (such as liquid crystal displays) and user interaction interfaces (such as keyboards, mice, touch input devices, etc.). All components of the electronic device may be interconnected via buses and / or networks.

[0080] According to embodiments of this disclosure, a computer-readable storage medium may also be provided, wherein when instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor causes the processor to perform the network quality assessment method of the embodiments of this disclosure. Examples of computer-readable storage media include: read-only memory (ROM), random access programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), random access memory (RAM), dynamic random access memory (DRAM), static random access memory (SRAM), flash memory, non-volatile memory, CD-ROM, CD-R, CD+R, CD-RW, CD+RW, DVD-ROM, DVD-R, DVD+R, DVD-RW, DVD+RW, DVD-RAM, BD-ROM, BD-R, BD-R, BD-R The computer program in the aforementioned computer-readable storage medium can run in an environment deployed in computer devices such as clients, hosts, agents, and servers. Furthermore, in one example, the computer program and any associated data, data files, and data structures are distributed across a networked computer system, allowing the computer program and any associated data, data files, and data structures to be stored, accessed, and executed in a distributed manner through one or more processors or computers.

[0081] According to embodiments of this disclosure, a computer program product is also provided, including computer instructions that, when executed by a processor, implement the network quality assessment method described above. In embodiments, a computer program product is also provided that includes, for example, a plurality of programs stored in a memory 430, which can be executed by a processor 420 in a computing environment 410 to perform the above-described method. For example, the computer program product may include a non-transitory computer-readable storage medium.

[0082] Unless otherwise specifically stated, the order of steps in the method according to this disclosure is intended to be illustrative only, and the steps of the method according to this disclosure are not limited to the specific order described above, but may be changed according to actual circumstances. Furthermore, at least one step in the method according to this disclosure may be adjusted, combined, or omitted as needed.

[0083] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.

[0084] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A network quality assessment method, characterized in that, include: The system reads the latest system-level network signal and the original weak network identification information acquired by the terminal at the current moment. The system-level network signal is acquired based on the underlying network signal output by the terminal's predetermined interface, and the system-level network signal includes information indicating whether the network accessed by the terminal is a weak network and the duration of the weak network when the network accessed by the terminal is a weak network. The predetermined interface is a standardized interface built into the terminal's operating system and opened by the manufacturer. The original weak network identification information is obtained by evaluating the network based on the network attribute information of the terminal's application layer. In response to the system-level network signal indicating that the network is weak and the current time falls within the duration of the weak network, the original weak network identification information is corrected by a preset attenuation coefficient to obtain the corrected weak network identification information of the terminal at the current time.

2. The network quality assessment method as described in claim 1, characterized in that, The system-level network signal is obtained in the following manner: A unified interface protocol is established, wherein the unified interface protocol specifies the method for obtaining the system-level network signal based on the underlying network signal output from a predetermined interface of any terminal; The system-level network signal is obtained through the method for obtaining the system-level network signal for the terminal as agreed in the unified interface protocol.

3. The network quality assessment method as described in claim 2, characterized in that, The method of obtaining the system-level network signal through the unified interface protocol for the terminal includes: In response to the underlying network signals directly output by the predetermined interface, including the system-level network signals, the system-level network signals are extracted from the underlying network signals; Since the underlying network signal directly output by the predetermined interface does not include the system-level network signal, the information indicating whether the network accessed by the terminal is a weak network is determined by comparing the predetermined network signal in the underlying network signal with a preset threshold. In response to the information indicating that the network accessed by the terminal is a weak network, the duration of the weak network is determined to be a preset duration.

4. The network quality assessment method as described in claim 1, characterized in that, The step of correcting the original weak network identification information by a preset attenuation coefficient to obtain the corrected weak network identification information of the terminal at the current time includes: The preset attenuation coefficient is multiplied by the original weak network identification information to obtain the corrected weak network identification information of the terminal at the current time.

5. The network quality assessment method as described in claim 1, characterized in that, After correcting the original weak network identification information using a preset attenuation coefficient to obtain the corrected weak network identification information of the terminal at the current moment, the method further includes: If the corrected weak network identification information is less than a preset weak network threshold, the network accessed by the terminal at the current time is determined to be a weak network.

6. The network quality assessment method as described in claim 1, characterized in that, The preset attenuation coefficient is the optimal attenuation coefficient obtained through randomized controlled experiments.

7. A network quality assessment device, characterized in that, include: The reading unit is configured to read the latest system-level network signal and the original weak network identification information acquired by the terminal at the current moment. The system-level network signal is acquired based on the underlying network signal output by a predetermined interface of the terminal, and the system-level network signal includes information indicating whether the network accessed by the terminal is a weak network and the duration of the weak network when the network accessed by the terminal is a weak network. The predetermined interface is a standardized interface built into the terminal's operating system and opened by the manufacturer. The original weak network identification information is obtained by evaluating the network based on the network attribute information of the terminal's application layer. The correction unit is configured to, in response to the system-level network signal indicating that the network is a weak network and the current time falls within the duration of the weak network, correct the original weak network identification information by using a preset attenuation coefficient to obtain the corrected weak network identification information of the terminal at the current time.

8. An electronic device, characterized in that, include: At least one processor; At least one memory that stores computer-executable instructions. The computer-executable instructions, when executed by the at least one processor, cause the at least one processor to perform the network quality assessment method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, When the instructions in the computer-readable storage medium are executed by at least one processor, the at least one processor causes the network quality assessment method as described in any one of claims 1 to 6.

10. A computer program product comprising computer instructions, characterized in that, When the computer instructions are executed by the processor, they implement the network quality assessment method as described in any one of claims 1 to 6.

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