Device server adaptive capacity expansion method and system, terminal device and medium

Abstract

The invention discloses an equipment server self-adaptive capacity expansion method and system, terminal equipment and a medium, and the method comprises the steps: obtaining the registration number of current equipment and the use data of an equipment server, and determining the capacity data of the equipment server based on the registration number of the current equipment and the use data of the equipment server; determining a capacity expansion strategy based on the capacity data; and executing an expansion operation on the equipment server based on the expansion strategy, and updating the registration number of the current equipment in the equipment server after the expansion operation is executed. According to the invention, the capacity analysis of the device server and the automatic capacity expansion of the device server can be realized, the adaptability and performance of the system can be improved, and the stable control of the registration number of the devices can be maintained.

Description

Technical Field

[0001] The present invention relates to the field of capacity expansion technology, and in particular to a device server adaptive capacity expansion method, system, terminal device and medium. Background Art

[0002] In modern IoT and smart device applications, the control of the number of registered devices is an important issue. Traditional methods for controlling the number of registered devices are usually based on fixed rules or strategies, which cannot automatically adapt to changes in the number of devices, resulting in unstable performance when the number of devices fluctuates greatly.

[0003] The traditional fixed registration quantity control method may cause the following problems:

[0004] 1. Too many or too few devices will affect the operating efficiency and stability of the system, and it will not be able to flexibly respond to changes in the number of devices;

[0005] 2. The control rules for the number of registered devices are not intelligent and flexible enough, and cannot be adjusted in time according to actual conditions;

[0006] 3. When the system capacity is insufficient or there are too many device connection requests, system performance may be degraded or service may be interrupted.

[0007] Therefore, the prior art still needs to be improved and enhanced. Summary of the invention

[0008] The technical problem to be solved by the present invention is to provide a device server adaptive capacity expansion method, system, terminal device and medium in view of the above-mentioned defects of the prior art, aiming to solve the problem in the prior art that the system capacity cannot automatically adapt to the change in the number of devices.

[0009] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows:

[0010] In a first aspect, the present invention provides a method for adaptively expanding capacity of a device server, wherein the method comprises:

[0011] Acquire the current number of registered devices and usage data of the device server, and determine the capacity data of the device server based on the current number of registered devices and the usage data of the device server;

[0012] Determining a capacity expansion strategy based on the capacity data;

[0013] An expansion operation is performed on the device server based on the expansion strategy, and after the expansion operation is completed, the current number of registered devices in the device server is updated.

[0014] In one implementation, determining the capacity data of the device server based on the current number of registered devices and the usage data of the device server includes:

[0015] Based on the current number of registered devices, determine the number of registered devices per unit time;

[0016] Determine the CPU usage rate of the device server per unit time based on the usage data of the device server;

[0017] Based on the number of device registrations within the unit time and the CPU usage rate of the device server within the unit time, capacity data of the device server is determined.

[0018] In one implementation, determining the capacity data of the device server based on the number of device registrations within the unit time and the CPU usage rate of the device server within the unit time includes:

[0019] The CPU usage rate of the device server per unit time is divided by the number of device registrations per unit time to obtain the capacity data of the device server.

[0020] In one implementation, determining a capacity expansion strategy based on the capacity data includes:

[0021] Get the preset trigger threshold;

[0022] If the capacity data is greater than the trigger threshold, the capacity expansion strategy is determined based on the current number of registered devices.

[0023] In one implementation, the trigger threshold is set as follows:

[0024] Acquire historical data of the device server, wherein the historical data includes device registration historical data and historical usage data of the device server;

[0025] The trigger threshold is set based on the correspondence between the device registration history data and the historical usage data of the device server.

[0026] In one implementation, the method further includes:

[0027] When the capacity data is greater than the trigger threshold, an early warning mechanism is triggered, and an emergency treatment plan is determined based on the early warning mechanism.

[0028] In one implementation, the method further includes:

[0029] The updated number of registered devices is obtained, and the trigger threshold and the expansion strategy are adjusted based on the updated number of registered devices.

[0030] In a second aspect, an embodiment of the present invention further provides a device server adaptive capacity expansion system, wherein the system includes:

[0031] A capacity data analysis module, used to obtain the current number of registered devices and usage data of the device server, and determine the capacity data of the device server based on the current number of registered devices and the usage data of the device server;

[0032] A capacity expansion strategy determination module, used to determine a capacity expansion strategy based on the capacity data;

[0033] The capacity expansion operation execution module is used to execute the capacity expansion operation on the device server based on the capacity expansion strategy, and update the current number of device registrations in the device server after the capacity expansion operation is completed.

[0034] In a third aspect, an embodiment of the present invention further provides a terminal device, wherein the terminal device includes a memory, a processor, and a device server adaptive capacity expansion program stored in the memory and executable on the processor, and when the processor executes the device server adaptive capacity expansion program, the steps of the device server adaptive capacity expansion method of any one of the above-mentioned schemes are implemented.

[0035] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein a device server adaptive capacity expansion program is stored on the computer-readable storage medium, and when the device server adaptive capacity expansion program is executed by a processor, the steps of the device server adaptive capacity expansion method described in any one of the above schemes are implemented.

[0036] Beneficial effects: The present invention provides a method for adaptive capacity expansion of a device server. Compared with the prior art, the method first obtains the current number of registered devices and the usage data of the device server, and determines the capacity data of the device server based on the current number of registered devices and the usage data of the device server. Then, based on the capacity data, a capacity expansion strategy is determined. Finally, based on the capacity expansion strategy, a capacity expansion operation is performed on the device server, and after the capacity expansion operation is completed, the current number of registered devices in the device server is updated. The present invention can realize capacity analysis of the device server and automatic capacity expansion of the device server, which is beneficial to improving the adaptability and performance of the system and maintaining stable control of the number of registered devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 The present invention provides a flowchart of a specific implementation of the method for adaptively expanding the capacity of a device server according to an embodiment of the present invention.

[0038] Figure 2A schematic diagram of an application scenario architecture of the device server adaptive capacity expansion method provided in an embodiment of the present invention.

[0039] Figure 3 A schematic diagram of an application scenario of the device server adaptive capacity expansion device provided in an embodiment of the present invention.

[0040] Figure 4 It is a principle block diagram of a device server adaptive capacity expansion device provided by an embodiment of the present invention.

[0041] Figure 5 It is a block diagram of the internal structure principle of the intelligent terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solution and effect of the present invention clearer and more specific, the present invention is further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0043] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations or steps, nor must they be executed in the order described. For example, some operations or steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0044] It should be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0045] It should be understood that, in order to clearly describe the technical solutions of the embodiments of the present invention, in the embodiments of the present invention, words such as "first" and "second" are used to distinguish between identical or similar items with substantially identical functions and effects. For example, the first control information and the second control information are only used to distinguish different control information, and their order is not limited.

[0046] Those skilled in the art can understand that the words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not necessarily limit the differences.

[0047] It should be further understood that the term “and / or” used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0048] In the prior art, the device registration quantity control method is usually based on fixed rules or strategies. Too many or too few devices will affect the operating efficiency and stability of the system, and it is not possible to flexibly respond to changes in the number of devices. In addition, the control rules for the number of device registrations are not intelligent and flexible enough, and cannot be adjusted in a timely manner according to actual conditions. When the system capacity is insufficient or there are too many device connection requests, it may cause system performance degradation or service interruption.

[0049] In order to solve the problems of the prior art, the present invention provides a device server adaptive expansion method, which can realize capacity analysis of the device server and automatic expansion of the device server, which is beneficial to improving the adaptability and performance of the system and maintaining stable control of the number of registered devices.

[0050] For example, Figure 2 As shown, the application scenario of the adaptive expansion method for device servers includes intelligent devices, device servers, monitoring servers, and expansion servers. Specifically, the intelligent device is connected to the device server by registration, and the monitoring server monitors the number of intelligent devices connected to the device server, the usage data of the device server, and other data, and judges the existing usage capacity data of the device server based on the initial threshold set by the operation and maintenance personnel. If the corresponding threshold is reached, a message is sent to the expansion server, and the expansion server performs corresponding expansion operations on the device server. In this way, by setting the monitoring server to monitor the device server and setting the expansion server to expand the device server, the automatic expansion of the device server is realized, which solves the problem of unstable performance caused by large fluctuations in the number of devices in the system.

[0051] Exemplary Methods

[0052] This embodiment provides a device server adaptive expansion method, such as Figure 1 As shown, the specific steps include:

[0053] Step S100: Acquire the current number of registered devices and usage data of the device server, and determine the capacity data of the device server based on the current number of registered devices and the usage data of the device server.

[0054] In this embodiment, the number of device registrations is specifically the number of IoT smart devices that are connected to the device server for the first time and register the devices, that is, the device registration is the first time the device is connected to the device server and the relevant information is registered. The specific implementation method of obtaining the current number of device registrations is to track the current number of device registrations in real time through a monitoring system, and record the number of device registrations in the device server. The monitoring system can be a device management system, which monitors the currently connected smart devices and the newly connected and registered smart devices through the relevant interfaces of the device server. The monitoring system can also be a physical monitoring system including sensors, specifically, through sensors such as video signals, infrared signals, and temperature signals, to actually monitor the smart devices in a limited area. The monitoring system can also be a separate monitoring server for monitoring the relevant data of the device server. Further, in the database of the device server, a device information table is set to store the relevant information of the registered devices, such as the unique identification of the device, the registration time, the connection status, etc. By querying and counting the table, the number of currently connected devices can be obtained.

[0055] The usage data of the device server includes but is not limited to the CPU usage rate, memory usage rate, network bandwidth usage rate, number of network connections, storage hardware capacity usage rate, and storage hardware input and output rate of the device server. Specifically, the above-mentioned device server usage data is obtained through the device server's own monitoring software or external auxiliary monitoring hardware. Similarly, the usage data of the device server will also be stored in the device server for subsequent expansion logic judgment.

[0056] In one implementation, determining the capacity data of the device server based on the current number of registered devices and the usage data of the device server specifically includes the following steps:

[0057] Step S110: determining the number of device registrations per unit time based on the current number of device registrations;

[0058] Step S120: determining the CPU usage rate of the device server per unit time based on the usage data of the device server;

[0059] Step S130: Determine the capacity data of the device server based on the number of device registrations within the unit time and the CPU usage rate of the device server within the unit time.

[0060] In this embodiment, the unit time can be divided into milliseconds, seconds, minutes, hours, days, etc. based on the actual processing capacity of the device server. Preferably, based on the frequency of device registration and connection in the application scenario, the unit time can be set to the minute level, specifically 1 minute. The unit time is set to the minute level, which is more commonly used in server resource monitoring and can be well adapted to the CPU usage, memory usage, etc. of the monitoring device server in this technical solution. Minute-level monitoring and collection data can not only reflect the general trend of resource usage, but also will not cause a large amount of data redundancy and storage pressure due to too frequent collection.

[0061] The capacity data is used to determine whether the device server is still capable of supporting its continued registration of devices. The capacity data can be a hardware indicator or a software indicator. Specifically, the capacity data can be the maximum number of network interface connections that the device server can accommodate. For example, the maximum number of network interface connections supported by a device server is 10. Then, when the device server has connected 10 IoT smart devices, new devices can no longer be connected to the device server by registration. The capacity data can also be the maximum number of registered devices that the CPU performance of the device server can handle. When the number of registered devices of the device server exceeds this value, the CPU performance has reached a bottleneck and cannot process the data information exchange requests of the connected devices. At this time, even if the device server can continue to register devices, the performance of the device server will drop drastically, and even the connected devices will fail to respond and cause disconnection. Similarly, the capacity data can also be the maximum number of registered devices affected by the above-mentioned other performance indicators.

[0062] In one implementation, determining the capacity data of the device server based on the number of device registrations per unit time and the CPU usage rate of the device server per unit time comprises the following steps:

[0063] Step S131: Divide the CPU usage rate of the device server per unit time by the number of device registrations per unit time to obtain capacity data of the device server.

[0064] In this embodiment, the capacity data of the device server is different from the above definition. It is the pressure level of the device server when registering a new device, which is used to reflect whether the capacity of the device registered and connected by the device server has reached saturation. Specifically, in a unit time, such as the minute-level unit time set above, that is, within one minute, the average CPU usage is divided by the number of newly registered devices in this minute to obtain a percentage value. This percentage value is the pressure level of the device server, that is, the current server pressure state of the device server. For example, within a specified minute, the device server registered 8 devices, the average CPU usage was 80%, and the pressure level of the device server was 10%, that is, the CPU usage of 8 registered devices was only 80%, and the pressure level was low, indicating that the CPU of the device server is still not saturated, and the performance of the device server is still very redundant. Continuing to register more devices will not cause a large performance impact on the device server. In another case, within a specified minute, the device server registered 2 devices, the average CPU usage was 70%, and the pressure level of the device server was 35%, which is moderate, indicating that the CPU performance of the device server is also not saturated. There is still a situation that within a specified minute, the device server only newly registers one device, and the average CPU utilization rate is 90%. The pressure level of the device server is 90%, that is, the registration of a new device causes the CPU utilization rate of the device server to reach 90%. The pressure level is relatively large, and the CPU performance is about to reach a bottleneck. The capacity of the devices registered and connected to the device server is likely to be saturated.

[0065] Step S200: Determine a capacity expansion strategy based on the capacity data.

[0066] After obtaining the above-mentioned capacity data, a corresponding capacity expansion strategy needs to be determined for the capacity data.

[0067] In one implementation, determining a capacity expansion strategy based on the capacity data includes the following steps:

[0068] Step S210: obtaining a preset trigger threshold;

[0069] Step S220: If the capacity data is greater than the trigger threshold, determine the capacity expansion strategy based on the current number of registered devices.

[0070] In this embodiment, the trigger threshold needs to be specifically set based on the specific definition of capacity data. If the capacity data is defined as the maximum number of network interface connections that the device server can accommodate, the threshold can be set to the maximum number of network interface connections after reserving a spare network connection port. If the capacity data is defined as the maximum number of registered devices that the device server CPU performance can handle, the threshold can be set to the maximum number of registered devices after reserving server performance redundancy. If the capacity data is defined as the pressure level of the server, the threshold can be set to the server pressure level that can be tolerated after the server reserves performance redundancy. By monitoring the device server, it is determined whether the capacity data reaches the trigger threshold. If the trigger threshold has been reached, it is necessary to determine the expansion strategy based on the current number of device registrations of the device server and the usage data of the device server. Specifically, the expansion strategy can be to add a new device server network interface, increase CPU computing power, increase memory, etc., or to add a new device server to form a group with the original device server, or to add a new device server and add it to the original device server group.

[0071] In one implementation, the trigger threshold is set by the following steps:

[0072] Step S211, obtaining historical data of the device server, wherein the historical data includes device registration historical data and historical usage data of the device server;

[0073] Step S212: Setting the trigger threshold based on the correspondence between the device registration history data and the historical usage data of the device server.

[0074] In this embodiment, the device registration history data is specifically the registration data of all devices stored in the device information table of the device server, and the device server historical usage data is specifically the historical record of the performance indicator information of the device server stored in the server. Based on the corresponding relationship between the above two, the operation and maintenance personnel can manually set the trigger threshold of the capacity data according to actual experience.

[0075] Furthermore, based on the hardware foundation of the device server, it can be known that, in general, the number of device registrations is positively correlated with the CPU usage of the device server. Here, the number of device registrations is the historical data of device registrations, that is, the total number of device registrations. Therefore, an association model can be used to express the correlation between the number of device registrations and the CPU usage of the device server. Preferably, mathematical models such as linear regression and polynomial regression can be used to fit the relationship between the number of device registrations and the CPU usage. Substitute the historical record information of the above-mentioned device information table and the CPU usage of the device server into the association model, calculate the specific values ​​of the parameters of the model, and obtain the fitted association model. On the basis of this association model, we can substitute only one of the indicators of the number of device registrations or the CPU usage of the device server into the association model to obtain another simulated indicator data for obtaining the capacity data of the device server. Therefore, according to this model, the corresponding capacity data trigger threshold can be set for subsequent server expansion.

[0076] Furthermore, the positive correlation between the number of device registrations and the device server CPU usage rate can also be replaced by the correlation between the number of device registrations and other specific usage data of the device server, such as memory usage rate, memory space remaining value, network bandwidth usage rate, etc. If usage data such as memory space remaining value is used, the number of device registrations and the memory space remaining value are negatively correlated.

[0077] In one implementation, the method further includes, when the capacity data is greater than the trigger threshold, triggering an early warning mechanism, and determining an emergency treatment plan based on the early warning mechanism.

[0078] In this embodiment, when the capacity data is greater than the trigger threshold, it is necessary not only to trigger the above expansion strategy and expand the device server, but also to set up an early warning mechanism. The early warning mechanism also needs to determine the corresponding emergency treatment plan. Specifically, the emergency treatment plan needs to deal with some abnormal situations that may occur when the device server is expanded. For example, when adding new hardware devices such as CPU and memory, compatibility issues may occur. Even with the elastic mechanism of cloud services, problems such as uneven resource allocation and scheduling delays may occur during the elastic process. Therefore, in this embodiment, a set of early warning mechanisms is set. The early warning mechanism can be to send an alarm to notify relevant personnel immediately after reaching the set threshold. The early warning mechanism can also be an early warning for the correctness of device expansion. Specifically, the device server and all registered devices before and after the expansion are compared to determine whether the device server is running normally, whether the registered device is still connected, and whether the data information is transmitted correctly. If a verification abnormality occurs, such as if it is found that the registered device before the expansion is disconnected after the expansion, the emergency treatment plan needs to be executed. The emergency treatment plan can be a manual treatment plan, that is, the operation and maintenance personnel manually troubleshoot the problem and repair it. It can also be an automatic processing solution, that is, canceling the current expansion, restoring the hardware environment and software version before the expansion, and expanding and comparing again.

[0079] Step S300: performing a capacity expansion operation on the device server based on the capacity expansion strategy, and updating the current number of registered devices in the device server after the capacity expansion operation is completed.

[0080] In this embodiment, the capacity expansion strategy includes but is not limited to adding new device server network interfaces, increasing CPU computing power, increasing memory, etc., and can also be to add new device servers to form a group with the original device servers, or to add new device servers and add them to the original device server group. Based on the capacity expansion strategy, the capacity expansion operation is performed on the device server. Specifically, the capacity expansion operation of the server can be achieved by setting an automated tool or script. After performing the capacity expansion operation, the device server has the hardware capability to continue to register new devices. At this time, the device information table of the device server needs to be updated. Specifically, because the capacity expansion strategy can also include the expansion of the device server group and rebalancing for load balancing, after rebalancing, the IoT smart devices connected to each device server in the device server group can change. Therefore, the device information table in the device server needs to be updated according to the connection information after rebalancing. Similarly, the number of device registrations corresponding to each device server also needs to be updated.

[0081] In one implementation, the method further includes obtaining an updated number of registered devices, and adjusting the trigger threshold and the capacity expansion strategy based on the updated number of registered devices.

[0082] In this embodiment, after the device server is expanded, the number of registered devices changes, and the usage data of the device server, such as CPU usage, also changes. The capacity data of the device server decreases, and the trigger threshold and the expansion strategy need to be adaptively adjusted according to the changed capacity data. Specifically, with respect to the expansion strategy, if there is a single device server before the expansion, and the expansion strategy is to set up a device server group or cluster, then the subsequent expansion strategy becomes to add servers to the device server group. If the original expansion strategy is to increase the CPU core, but the number of CPU cores of the single device server after the expansion has reached the hardware upper limit, then the subsequent expansion strategy becomes to add a new device server.

[0083] With respect to the trigger threshold, if the capacity data is defined as the maximum number of network interface connections that the device server can accommodate or the maximum number of registered devices that the device server's CPU performance can handle, it is necessary to recalculate the maximum number of network interface connections that it can accommodate or the maximum number of registered devices that the CPU can handle based on the expanded device server hardware. If the capacity data is defined as the stress level of the device server, the absolute value of the threshold may not be adjusted. Because the stress level threshold of the device server is a percentage, it can be set to a fixed percentage value. Preferably, the percentage value is 50%. Before and after the expansion, the calculation method of the stress level value of the device server has not changed, and the threshold method has not changed. Therefore, the stress level value of the device server is the preferred method for capacity data. In this way, the trigger condition of the threshold is equivalent to adapting the expansion operation.

[0084] When this technical solution is implemented, Figure 3 As shown, in the application scenario of this method, devices such as device servers, IoT smart devices, detection servers, and capacity expansion servers are included. The specific process includes: the operation and maintenance personnel set the relevant thresholds for device registration on the monitoring server; the monitoring server monitors the device registration of the device server in real time and determines whether the threshold is reached; at this time, a large number of IoT smart devices request registration on the device server at the same time; the device server registers this batch of devices and synchronizes the relevant data of this batch of registrations to the monitoring server; the monitoring server calculates the relevant thresholds, determines and triggers the thresholds, and then synchronizes the message that triggers the expansion to the expansion server; the expansion server expands the hardware resources or software resources required by the device server, and updates the relevant device information table and records of the device server after the expansion.

[0085] In summary, under the technical solution of the above embodiment, a method for adaptively controlling the number of registered devices is implemented, and the registration strategy can be dynamically adjusted according to the actual changes in the number of devices, thereby improving the adaptability and performance of the system and maintaining stable control of the number of registered devices.

[0086] Exemplary Devices

[0087] like Figure 4 As shown in , an embodiment of the present invention provides a device server adaptive capacity expansion system, the device comprising: a capacity data analysis module 10, a capacity expansion strategy determination module 20, and a capacity expansion operation execution module 30.

[0088] Specifically, the capacity data analysis module 10 is used to obtain the current number of device registrations and the usage data of the device server, and determine the capacity data of the device server based on the current number of device registrations and the usage data of the device server; the capacity expansion strategy determination module 20 is used to determine the capacity expansion strategy based on the capacity data; the capacity expansion operation execution module 30 is used to perform a capacity expansion operation on the device server based on the capacity expansion strategy, and update the current number of device registrations in the device server after the capacity expansion operation is completed.

[0089] In one implementation, the capacity data analysis module 10 includes:

[0090] A device registration quantity determination unit, configured to determine the number of device registrations per unit time based on the current number of device registrations;

[0091] A CPU usage rate determining unit, configured to determine a CPU usage rate of the device server per unit time based on usage data of the device server;

[0092] a capacity data determining unit, configured to determine the capacity data of the device server based on the number of device registrations within the unit time and the CPU usage rate of the device server within the unit time;

[0093] The capacity data determining unit comprises:

[0094] The capacity data determination subunit is used to divide the CPU usage rate of the device server per unit time by the number of device registrations per unit time to obtain the capacity data of the device server.

[0095] In one implementation, the capacity expansion strategy determination module 20 includes:

[0096] A threshold acquisition unit, used to acquire a preset trigger threshold;

[0097] a capacity expansion strategy determining unit, configured to determine the capacity expansion strategy based on the current number of registered devices if the capacity data is greater than the trigger threshold;

[0098] A historical data acquisition unit, configured to acquire historical data of the device server, wherein the historical data includes device registration historical data and historical usage data of the device server;

[0099] a threshold setting unit, configured to set the trigger threshold based on a correspondence between the device registration history data and the historical usage data of the device server;

[0100] An early warning mechanism unit, configured to trigger an early warning mechanism when the capacity data is greater than the trigger threshold, and determine an emergency treatment plan based on the early warning mechanism;

[0101] The threshold and expansion strategy updating unit is used to obtain the updated number of registered devices and adjust the trigger threshold and the expansion strategy based on the updated number of registered devices.

[0102] Based on the above embodiments, the present invention further provides an intelligent terminal, whose principle block diagram can be shown as follows: Figure 5 As shown. The intelligent terminal includes a processor, a memory, a network interface, a display screen, and a temperature sensor connected through a system bus. Among them, the processor of the intelligent terminal is used to provide computing and control capabilities. The memory of the intelligent terminal includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the intelligent terminal is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for optimizing display quality is implemented. The display screen of the intelligent terminal can be a liquid crystal display screen or an electronic ink display screen, and the temperature sensor of the intelligent terminal is pre-set inside the intelligent terminal to detect the operating temperature of the internal device.

[0103] Those skilled in the art will understand that Figure 5 The principle block diagram shown in the figure is only a block diagram of a partial structure related to the scheme of the present invention, and does not constitute a limitation on the smart terminal to which the scheme of the present invention is applied. The specific smart terminal may include more or fewer components than those shown in the figure, or combine certain components, or have a different component arrangement.

[0104] In one embodiment, a smart terminal is provided, comprising a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors, and the one or more programs include instructions for performing the following operations:

[0105] Acquire the current number of registered devices and usage data of the device server, and determine the capacity data of the device server based on the current number of registered devices and the usage data of the device server;

[0106] Determining a capacity expansion strategy based on the capacity data;

[0107] An expansion operation is performed on the device server based on the expansion strategy, and after the expansion operation is completed, the current number of registered devices in the device server is updated.

[0108] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct RAMbus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0109] In summary, the present invention discloses a method, system, terminal device and medium for adaptive expansion of a device server, the method comprising: obtaining the current number of registered devices and the usage data of the device server, determining the capacity data of the device server based on the current number of registered devices and the usage data of the device server; determining the expansion strategy based on the capacity data; performing an expansion operation on the device server based on the expansion strategy, and updating the current number of registered devices in the device server after the expansion operation is completed. The present invention can realize capacity analysis of the device server and automatic expansion of the device server, which is conducive to improving the adaptability and performance of the system and maintaining stable control of the number of registered devices.

[0110] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0111] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A device server adaptive capacity expansion method, characterized in that: The method comprises: Acquire the current number of registered devices and usage data of the device server, and determine the capacity data of the device server based on the current number of registered devices and the usage data of the device server; Determining a capacity expansion strategy based on the capacity data; An expansion operation is performed on the device server based on the expansion strategy, and after the expansion operation is completed, the current number of registered devices in the device server is updated.

2. The device server adaptive expansion method according to claim 1, characterized in that: The determining the capacity data of the device server based on the current number of registered devices and the usage data of the device server includes: Based on the current number of registered devices, determine the number of registered devices per unit time; Determine the CPU usage rate of the device server per unit time based on the usage data of the device server; Based on the number of device registrations within the unit time and the CPU usage rate of the device server within the unit time, capacity data of the device server is determined.

3. The device server adaptive expansion method according to claim 2, characterized in that: The determining the capacity data of the device server based on the number of device registrations within the unit time and the CPU usage rate of the device server within the unit time includes: The CPU usage rate of the device server per unit time is divided by the number of device registrations per unit time to obtain the capacity data of the device server.

4. The device server adaptive expansion method according to claim 1, characterized in that: The determining of a capacity expansion strategy based on the capacity data includes: Get the preset trigger threshold; If the capacity data is greater than the trigger threshold, the capacity expansion strategy is determined based on the current number of registered devices.

5. The device server adaptive expansion method according to claim 4, characterized in that: The trigger threshold setting method includes: Acquire historical data of the device server, wherein the historical data includes device registration historical data and historical usage data of the device server; The trigger threshold is set based on the correspondence between the device registration history data and the historical usage data of the device server.

6. The device server adaptive expansion method according to claim 4, characterized in that: The method further comprises: When the capacity data is greater than the trigger threshold, an early warning mechanism is triggered, and an emergency treatment plan is determined based on the early warning mechanism.

7. The device server adaptive expansion method according to claim 5, characterized in that: The method further comprises: The updated number of registered devices is obtained, and the trigger threshold and the expansion strategy are adjusted based on the updated number of registered devices.

8. A device server adaptive expansion system, characterized in that: The system comprises: A capacity data analysis module, used to obtain the current number of registered devices and usage data of the device server, and determine the capacity data of the device server based on the current number of registered devices and the usage data of the device server; A capacity expansion strategy determination module, used to determine a capacity expansion strategy based on the capacity data; The capacity expansion operation execution module is used to execute the capacity expansion operation on the device server based on the capacity expansion strategy, and update the current number of device registrations in the device server after the capacity expansion operation is completed.

9. A terminal device, characterized in that: The terminal device includes a memory, a processor, and a device server adaptive capacity expansion program stored in the memory and executable on the processor. When the processor executes the device server adaptive capacity expansion program, the steps of the device server adaptive capacity expansion method as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a device server adaptive capacity expansion program, and when the device server adaptive capacity expansion program is executed by the processor, the steps of the device server adaptive capacity expansion method according to any one of claims 1 to 7 are implemented.

Images