Internet of Things node load balancing method and device, electronic equipment and storage medium

Abstract

The invention discloses an Internet of Things node load balancing method and device, electronic equipment and a storage medium. The method comprises the following steps: determining a dynamic load value corresponding to the complex building group Internet of Things; determining a load integration value according to the load data volume corresponding to all non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things; under the condition that the load integration value is greater than the dynamic load value, determining a priority corresponding to each non-uniformly distributed Internet of Things node; according to the priority, a load balancing strategy is determined and executed, and the load balancing strategy is used for scheduling load data in the non-uniformly distributed Internet of Things nodes so as to reduce the overall load degree of the non-uniformly distributed Internet of Things nodes. According to the method and the device, the technical problem that the load of the Internet of Things of the complex building group is unbalanced due to the fact that the management mode in the related technology lacks the consideration of communication and cooperation between the nodes of the Internet of Things in the complex building group is solved.

Description

Technical Field

[0001] The present application relates to the technical field of Internet of Things, and in particular to a method, device, electronic device and storage medium for load balancing of Internet of Things nodes. Background Art

[0002] IoT nodes in complex buildings have different information such as geographical location and device model, which leads to the formation of a non-uniform distribution structure of communication nodes. For example, some nodes may be concentrated in a certain area, while there are relatively few nodes in other areas. This uneven distribution will cause some nodes to be overloaded while other nodes are lightly loaded, resulting in unbalanced resource utilization.

[0003] In the Internet of Things for complex buildings, data exchange and collaboration between nodes are required. However, the static management method in related technologies lacks consideration of the communication and collaboration between IoT nodes, and fails to fully consider the communication needs between nodes, which may lead to unbalanced loads among nodes in the Internet of Things for complex buildings, causing communication congestion and data transmission delays.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present application provide a method, device, electronic device and storage medium for load balancing of Internet of Things nodes, so as to at least solve the technical problem of unbalanced load of the Internet of Things in complex building complexes caused by the lack of consideration of communication and collaboration between Internet of Things nodes in complex building complexes in the management methods of related technologies.

[0006] According to one aspect of an embodiment of the present application, a method for load balancing of Internet of Things nodes is provided, comprising: determining a dynamic load value corresponding to a complex building complex Internet of Things, wherein the complex building complex Internet of Things includes: non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to characterize the overall load level of the Internet of Things nodes in the complex building complex Internet of Things; determining a load integration value based on the amount of load data corresponding to all non-uniformly distributed Internet of Things nodes in the complex building complex Internet of Things, wherein the load integration value is used to characterize the load level of the non-uniformly distributed Internet of Things nodes in the complex building complex Internet of Things; when the load integration value is greater than the dynamic load value, determining the priority level corresponding to each non-uniformly distributed Internet of Things node, wherein the priority level is used to characterize the priority level of the non-uniformly distributed Internet of Things nodes in processing new load data; determining and executing a load balancing strategy based on the priority level, wherein the load balancing strategy is used to schedule the load data in the non-uniformly distributed Internet of Things nodes to reduce the overall load level of the non-uniformly distributed Internet of Things nodes.

[0007] Optionally, determining the priority corresponding to each unevenly distributed Internet of Things node includes: determining the load-bearing space and occupied space of the unevenly distributed Internet of Things nodes, and determining the remaining load space and node space utilization corresponding to the unevenly distributed Internet of Things nodes based on the load-bearing space and occupied space; determining the safety factor and location distance parameter corresponding to the unevenly distributed Internet of Things nodes, wherein the safety factor is used to characterize the safety level of the unevenly distributed Internet of Things nodes, and the location distance parameter is used to characterize the connection relationship between the unevenly distributed Internet of Things nodes and other Internet of Things nodes in the Internet of Things of a complex building complex; determining the priority corresponding to the unevenly distributed Internet of Things nodes based on the remaining load space, node space utilization, safety factor, and location distance parameter.

[0008] Optionally, determining the security factor and location distance parameter corresponding to the unevenly distributed Internet of Things nodes includes: determining the access status corresponding to the unevenly distributed Internet of Things nodes, wherein the access status includes: active state, idle state, busy state and offline state; determining the security measurement value corresponding to the unevenly distributed Internet of Things nodes based on the type of encryption mechanism and firewall type corresponding to the unevenly distributed Internet of Things nodes; determining the security factor corresponding to the unevenly distributed Internet of Things nodes based on the access status and the security measurement value.

[0009] Optionally, determining the safety factor and location distance parameters corresponding to the unevenly distributed Internet of Things nodes also includes: determining the number of channels of the channels to which the unevenly distributed Internet of Things nodes are connected; determining the hop ratio corresponding to the unevenly distributed Internet of Things nodes, wherein the hop ratio is the ratio of the hop number corresponding to the unevenly distributed Internet of Things nodes to a preset standard hop number, and the hop number corresponding to the unevenly distributed Internet of Things nodes is the minimum number of intermediate nodes that the unevenly distributed Internet of Things nodes need to pass through to reach another unevenly distributed Internet of Things node in the Internet of Things of a complex building complex; based on the number of channels and the hop ratio, determining the location distance parameters corresponding to the unevenly distributed Internet of Things nodes.

[0010] Optionally, determining the dynamic load value corresponding to the Internet of Things for a complex building complex includes: determining an extended component of a channel formed by unevenly distributed Internet of Things nodes in the Internet of Things for the complex building complex, wherein the extended component is used to characterize the spatial variation of channel characteristics caused by uneven node distribution; determining the dynamic load value corresponding to the Internet of Things for the complex building complex based on the extended component, the load peak value and load interference value of the Internet of Things nodes in the Internet of Things for the complex building complex.

[0011] Optionally, determining the load integration value based on the load data volume corresponding to all the unevenly distributed IoT nodes in the complex building complex IoT includes: determining the number of data packets processed by the unevenly distributed IoT nodes in unit time, and determining the load data volume corresponding to the data packets; normalizing the load data volume corresponding to each unevenly distributed IoT node based on the maximum and minimum values ​​of the load data volume corresponding to all the unevenly distributed IoT nodes in the complex building complex IoT, and obtaining the normalized load data volume corresponding to each unevenly distributed IoT node; determining the weight value corresponding to the unevenly distributed IoT node based on the expected number of access users corresponding to each unevenly distributed IoT node; determining the load integration value based on the normalized load data volume and weight value corresponding to the unevenly distributed IoT nodes.

[0012] Optionally, based on the priority, determining and executing the load balancing strategy includes: determining the non-uniformly distributed IoT node with the highest priority in the complex building complex IoT as the target node for load scheduling, and selecting the non-uniformly distributed IoT node with the lowest priority as the starting node for load scheduling; when the connectivity between the starting node and the target node is greater than zero, determining the target scheduling link and load scheduling amount between the starting node and the target node, wherein the load scheduling amount is the amount of data of the load planned to be transferred from the starting node to the target node; and transferring the load data of the load scheduling amount in the starting node to the target node through the target scheduling link for processing.

[0013] According to another aspect of the embodiment of the present application, there is also provided an Internet of Things node load balancing device, including: a first calculation module, used to determine the dynamic load value corresponding to the Internet of Things of a complex building complex, wherein the Internet of Things of a complex building complex includes: non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to characterize the overall load level of the Internet of Things nodes in the Internet of Things of the complex building complex; a second calculation module, used to determine the load integration value based on the amount of load data corresponding to all the non-uniformly distributed Internet of Things nodes in the Internet of Things of the complex building complex, wherein the load integration value is used to characterize the load level of the non-uniformly distributed Internet of Things nodes in the Internet of Things of the complex building complex; a priority determination module, used to determine the priority level corresponding to each non-uniformly distributed Internet of Things node when the load integration value is greater than the dynamic load value, wherein the priority level is used to characterize the priority level of the non-uniformly distributed Internet of Things nodes in processing new load data; a load balancing module, used to determine and execute the load balancing strategy based on the priority level, wherein the load balancing strategy is used to schedule the load data in the non-uniformly distributed Internet of Things nodes to reduce the overall load level of the non-uniformly distributed Internet of Things nodes.

[0014] According to another aspect of the embodiments of the present application, there is also provided an electronic device, including: a memory and a processor, the processor being used to run a program stored in the memory, wherein the Internet of Things node load balancing method is executed when the program is running.

[0015] According to another aspect of the embodiments of the present application, a non-volatile storage medium is provided, the non-volatile storage medium includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the Internet of Things node load balancing method by running the computer program.

[0016] According to another aspect of the embodiments of the present application, a computer program product is provided, including a computer program, which implements the steps of the Internet of Things node load balancing method when the computer program is executed by a processor.

[0017] In an embodiment of the present application, a dynamic load value corresponding to the Internet of Things of a complex building complex is determined, wherein the Internet of Things of a complex building complex includes: non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to characterize the overall load level of the Internet of Things nodes in the Internet of Things of a complex building complex; a load integration value is determined based on the amount of load data corresponding to all non-uniformly distributed Internet of Things nodes in the Internet of Things of a complex building complex, wherein the load integration value is used to characterize the load level of the non-uniformly distributed Internet of Things nodes in the Internet of Things of a complex building complex; when the load integration value is greater than the dynamic load value, the priority level corresponding to each non-uniformly distributed Internet of Things node is determined, wherein the priority level is used to characterize the priority level of the non-uniformly distributed Internet of Things nodes in processing new load data; based on the priority level, the priority level is determined. First, determine and execute the load balancing strategy, where the load balancing strategy is used to schedule the load data in the unevenly distributed Internet of Things nodes to reduce the overall load level of the unevenly distributed Internet of Things nodes. By introducing the random load balancing optimization technology of unevenly distributed nodes, priority calculation and scheduling link generation are adopted to realize the node load balancing scheduling task, optimize the load distribution and performance of the Internet of Things, and achieve the purpose of improving the load balancing ability of the Internet of Things in complex building complexes, so as to realize the precise and intelligent management of complex building complexes and ensure the stable operation of the Internet of Things system, thereby solving the technical problem of unbalanced load of the Internet of Things in complex building complexes caused by the lack of consideration of communication and collaboration between Internet of Things nodes in complex building complexes in the management methods of related technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0019] Figure 1It is a hardware structure block diagram of a computer terminal (or electronic device) for implementing a method for load balancing of Internet of Things nodes provided in an embodiment of the present application;

[0020] Figure 2 It is a schematic diagram of a method flow for load balancing of Internet of Things nodes provided according to an embodiment of the present application;

[0021] Figure 3 It is a schematic diagram of the distribution of IoT nodes in a complex building complex provided according to an embodiment of the present application;

[0022] Figure 4 It is a schematic diagram of a random load data collection process of unevenly distributed nodes provided according to an embodiment of the present application;

[0023] Figure 5 It is a structural diagram of an Internet of Things node load balancing device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0024] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0026] IoT nodes in complex buildings have different information such as geographical location and device model, which leads to the formation of a non-uniform distribution structure of communication nodes. For example, some nodes may be concentrated in a certain area, while there are relatively few nodes in other areas. This uneven distribution will cause some nodes to be overloaded while other nodes are lightly loaded, resulting in unbalanced resource utilization.

[0027] In the Internet of Things for complex buildings, data exchange and collaboration between nodes are required. However, the static management method in related technologies lacks consideration of the communication and collaboration between IoT nodes, and fails to fully consider the communication needs between nodes, which may lead to unbalanced loads among nodes in the Internet of Things for complex buildings, causing communication congestion and data transmission delays.

[0028] In order to solve the above problems, relevant solutions are provided in the embodiments of the present application, which are described in detail below.

[0029] According to an embodiment of the present application, an embodiment of a method for load balancing of Internet of Things nodes is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0030] The method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 The hardware structure block diagram of a computer terminal (or electronic device) for implementing a method for load balancing of IoT nodes is shown. Figure 1 As shown, the computer terminal 10 (or electronic device) may include one or more (102a, 102b, ..., 102n are used to illustrate) processors 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0031] It should be noted that the one or more processors 102 and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 10 (or electronic device). As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0032] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the Internet of Things node load balancing method in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, the above-mentioned Internet of Things node load balancing method is realized. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0033] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0034] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 (or electronic device).

[0035] Under the above operating environment, the embodiment of the present application provides a method for load balancing of Internet of Things nodes. Figure 2 is a schematic diagram of a method flow for load balancing of IoT nodes provided in accordance with an embodiment of the present application, such as Figure 2 As shown, the method comprises the following steps:

[0036] Step S202, determining a dynamic load value corresponding to the complex building complex Internet of Things, wherein the complex building complex Internet of Things includes: non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to characterize the overall load degree of the Internet of Things nodes in the complex building complex Internet of Things;

[0037] Step S204, determining a load integration value according to the load data amount corresponding to all the non-uniformly distributed Internet of Things nodes in the complex building complex Internet of Things, wherein the load integration value is used to characterize the load degree of the non-uniformly distributed Internet of Things nodes in the complex building complex Internet of Things;

[0038] Step S206, when the load integration value is greater than the dynamic load value, determining the priority corresponding to each non-uniformly distributed IoT node, wherein the priority is used to characterize the priority of the non-uniformly distributed IoT node in processing new load data;

[0039] Step S208, determining and executing a load balancing strategy based on the priority, wherein the load balancing strategy is used to schedule load data in the non-uniformly distributed IoT nodes to reduce the overall load level of the non-uniformly distributed IoT nodes.

[0040] Through the above steps, by introducing the random load balancing optimization technology of non-uniformly distributed nodes, adopting priority calculation and scheduling link generation, the node load balancing scheduling task is realized, the load distribution and performance of the Internet of Things are optimized, and the load balancing capability of the Internet of Things in complex building complexes is improved, so as to realize the precise and intelligent management of complex building complexes and ensure the stable operation of the Internet of Things system, thereby solving the technical problem of unbalanced load of the Internet of Things in complex building complexes caused by the lack of consideration of communication and collaboration between Internet of Things nodes in complex building complexes in the management methods of related technologies.

[0041] The method for balancing the load of IoT nodes for the IoT of complex buildings is to solve the problem of unbalanced load of IoT caused by unevenly distributed building structures. In this embodiment, by collecting and integrating the random load data of unevenly distributed nodes, the MPDTR (Markov Prediction Duplicate Transmission Routing) routing protocol is used to calculate the priority of the node, generate a scheduling link, and complete the load balancing scheduling task of the node. Among them, MPDTR is a load balancing routing protocol based on mutual cooperation between nodes. It takes the priority of the node as an important indicator of the node load capacity, calculates the distance and load between the nodes according to the cooperative relationship between the nodes, and predicts and generates scheduling links. The model fully considers the influencing factors such as the distance, access volume, priority, etc. of the node, so that the load of the node can be more accurately calculated and scheduled, with a quantitative optimization effect, which has a positive effect on the stable operation of the IoT.

[0042] The following further introduces the IoT node load balancing method in steps S202 to S208 of the embodiment of the present application.

[0043] In the Internet of Things environment of complex buildings, due to the design asymmetry of the building structure and the scale of the building complex, the deployment of Internet of Things nodes is unbalanced. Appropriate communication technologies and equipment, such as sensors, wireless networks, etc., are used in the Internet of Things of complex buildings to connect various nodes in the building complex and establish network infrastructure, including network topology, network connection and communication protocols, to ensure communication and data transmission between nodes.

[0044] Specific as Figure 3 As shown, the Internet of Things in complex buildings contains non-uniformly distributed Internet of Things nodes and evenly distributed Internet of Things nodes. Among them, the non-uniformly distributed Internet of Things nodes are usually access sources in buildings with large and dense traffic, which are prone to load imbalance, while the evenly distributed Internet of Things nodes are usually Internet of Things access nodes in buildings with relatively stable access users and are not prone to load balancing problems.

[0045] The embodiment of the present application can solve the problem of node load differences in the Internet of Things of complex buildings by introducing the random load balancing optimization technology of unevenly distributed nodes. The Internet of Things environment is constructed using sensor devices and wireless networks, and load data is collected and integrated according to the node distribution location. Based on the MPDTR routing protocol, the node load balancing scheduling task is realized by adopting priority calculation and scheduling link generation, the load distribution and performance of the Internet of Things are optimized, and precise and intelligent management can be achieved. It aims to improve the load balancing of the Internet of Things, improve the stability and performance of the system, and avoid node overload and performance degradation by optimizing node load balancing, making full use of idle node resources, reducing congestion probability, delay and improving data transmission efficiency, improving the system's response speed and user experience, so as to ensure the stability and efficiency of the Internet of Things system of complex buildings. The specific explanation is as follows.

[0046] First, the dynamic load value M corresponding to the Internet of Things of complex buildings can be determined by considering node attenuation and position offset. The specific steps are as follows.

[0047] In some embodiments of the present application, determining the dynamic load value corresponding to the Internet of Things for a complex building complex includes the following steps: determining an extended component of a channel formed by unevenly distributed Internet of Things nodes in the Internet of Things for the complex building complex, wherein the extended component is used to characterize the spatial variation of channel characteristics caused by uneven node distribution; determining the dynamic load value corresponding to the Internet of Things for the complex building complex based on the extended component, the load peak value and load interference value of the Internet of Things nodes in the Internet of Things for the complex building complex.

[0048] Specifically, the calculation formula of the dynamic load value M is as follows: Among them, f is the extended component of the channel formed by the non-uniformly distributed IoT nodes, which is determined by the distance between uniform nodes, the amount of data sent, the channel bandwidth, and the channel attenuation coefficient g. γ is the peak load of the node, t is the time, and m is the load interference threshold. The threshold value varies in different environments and is usually between 0.001-0.05.

[0049] In addition, in the embodiment of the present application, the load data of each node in the Internet of Things of a complex building complex, such as load amount, load type, and load change, can be collected to integrate the random load data of unevenly distributed nodes and determine the load integration value. The specific steps are as follows.

[0050] In some embodiments of the present application, determining the load integration value based on the load data volume corresponding to all the non-uniformly distributed IoT nodes in the complex building complex IoT includes the following steps: determining the number of data packets processed by the non-uniformly distributed IoT nodes per unit time, and determining the load data volume corresponding to the data packets; normalizing the load data volume corresponding to each non-uniformly distributed IoT node based on the maximum and minimum values ​​of the load data volume corresponding to all the non-uniformly distributed IoT nodes in the complex building complex IoT, and obtaining the normalized load data volume corresponding to each non-uniformly distributed IoT node; determining the weight value corresponding to the non-uniformly distributed IoT node based on the expected number of access users corresponding to each non-uniformly distributed IoT node; determining the load integration value based on the normalized load data volume and weight value corresponding to the non-uniformly distributed IoT node.

[0051] In this embodiment, for all non-uniformly distributed IoT nodes, the following Figure 4 The process shown completes the integration of random load data of IoT nodes. Specifically, the total number of data packets processed by each non-uniformly distributed IoT node and the corresponding response time are collected, and the number of data packets processed per unit time is calculated; then, the data packets are parsed to determine the load data volume corresponding to each non-uniformly distributed IoT node.

[0052] Since the data of each node load includes various forms such as tables, images, and data, in order to make the attributes of different natures reflect the same comprehensive effect, the data is normalized. The processing process is shown in the following formula:

[0053]

[0054] Among them, x c,i represents the load data volume corresponding to the node after normalization, x iIt represents the load data volume corresponding to the node before normalization processing. Here, i refers to the i-th specific non-uniformly distributed IoT node. X is the load data set corresponding to all non-uniformly distributed IoT nodes in the IoT of complex buildings. max(X) and min(X) correspond to the maximum and minimum values ​​of the load data volume in the set.

[0055] After that, the random load data collected at each non-uniformly distributed IoT node location is integrated to obtain the load integration value in, The weight value corresponding to the non-uniformly distributed IoT node can be set according to the expected number of users accessing the node. The value range is from 0 to 0.9. The larger the threshold, the more users accessing the node exceed the number of users of the uniform node. However, with the automatic optimization of the algorithm, the weight value parameter will be dynamically changed. node The number of unevenly distributed nodes included in the complex building Internet of Things.

[0056] By collecting the load data of each node in the Internet of Things of complex buildings and integrating the random load data of unevenly distributed nodes, the embodiment of the present application can analyze and evaluate the load conditions of the nodes and understand the distribution characteristics and load differences of the nodes. This provides a basis for subsequent load balancing optimization to achieve balanced distribution of loads between nodes and improve system performance.

[0057] After obtaining the dynamic load value and load integration value, the priority of each non-uniformly distributed IoT node can be determined by considering the load capacity and mutual cooperation relationship of the nodes, and the appropriate scheduling target node and transmission link can be selected according to the priority to optimize the data transmission path, and finally the load scheduling can achieve the optimization goal of random load balancing of non-uniformly distributed nodes, thereby improving the load balancing and stability of the network. The following is a detailed explanation.

[0058] The embodiment of the present application analyzes the load data of the non-uniformly distributed IoT nodes and formulates a corresponding priority calculation strategy. The strategy can consider factors such as the node load level, load change speed, and node type, and assign a priority value to each node. The specific steps are as follows.

[0059] In some embodiments of the present application, determining the priority corresponding to each non-uniformly distributed Internet of Things node includes the following steps: determining the load-bearing space and occupied space of the non-uniformly distributed Internet of Things nodes, and determining the remaining load space and node space utilization corresponding to the non-uniformly distributed Internet of Things nodes based on the load-bearing space and occupied space; determining the safety factor and location distance parameter corresponding to the non-uniformly distributed Internet of Things nodes, wherein the safety factor is used to characterize the safety level of the non-uniformly distributed Internet of Things nodes, and the location distance parameter is used to characterize the connection relationship between the non-uniformly distributed Internet of Things nodes and the remaining Internet of Things nodes in the Internet of Things of a complex building complex; determining the priority corresponding to the non-uniformly distributed Internet of Things nodes based on the remaining load space, node space utilization, safety factor, and location distance parameter.

[0060] Specifically, considering multiple aspects such as the number of node connection channels, node load space, and node security, the priority ψ of the non-uniformly distributed IoT nodes is calculated as shown in the following formula:

[0061]

[0062] Where W = W all -W occupy , W is the remaining load space of the node (i.e. the above-mentioned remaining load space), W all is the load carrying space of non-uniformly distributed IoT nodes, W occupy is the amount of occupied space; ξ1 and ξ2 are both constant coefficients; μ use is the node utilization (i.e. the node space utilization mentioned above); is the safety factor of the node, N L ×n Hops is the above position distance parameter, where N L and n Hops They represent the number of channels and hop ratio of node connections respectively.

[0063] The above safety factor The specific steps for determining are as follows.

[0064] In some embodiments of the present application, determining the security factor and location distance parameter corresponding to the unevenly distributed Internet of Things nodes includes the following steps: determining the access status corresponding to the unevenly distributed Internet of Things nodes, wherein the access status includes: active state, idle state, busy state and offline state; determining the security measurement value corresponding to the unevenly distributed Internet of Things nodes based on the type of encryption mechanism and firewall type corresponding to the unevenly distributed Internet of Things nodes; determining the security factor corresponding to the unevenly distributed Internet of Things nodes based on the access status and the security measurement value.

[0065] Specifically, Among them, q i , σ attri and ω i are the access status, security metric value and weight of the ith attribute of the node. In this embodiment, the access status of the node specifically includes active state, idle state, busy state and offline state; the security metric value can be determined according to the security characteristics of the node, which include but are not limited to: the strength of the encryption mechanism, the effectiveness of the authentication mechanism, the configuration of the firewall, intrusion detection and defense capabilities, etc. Weight value ω i The higher the value, the more important the attribute is in evaluating the security of the node.

[0066] The above position distance parameter N L ×n Hops The specific steps for determining are as follows.

[0067] In some embodiments of the present application, determining the safety factor and location distance parameter corresponding to the non-uniformly distributed IoT nodes further includes the following steps: determining the number of channels N of the channels to which the non-uniformly distributed IoT nodes are connected L ; Determine the hop count ratio n corresponding to the non-uniformly distributed IoT nodes Hops , where the hop ratio is the ratio of the hop count corresponding to the non-uniformly distributed IoT nodes to the preset standard hop count, and the hop count corresponding to the non-uniformly distributed IoT nodes is the minimum number of intermediate nodes that the non-uniformly distributed IoT nodes need to pass through to reach another non-uniformly distributed IoT node in the complex building complex IoT. Based on the number of channels and the hop ratio, the location distance parameters corresponding to the non-uniformly distributed IoT nodes are determined.

[0068] The embodiment of the present application integrates the load data of unevenly distributed nodes and calculates the priority of the nodes to obtain a comprehensive evaluation of the load and importance of the nodes. Then, according to the priority of the nodes, the corresponding load balancing strategy can be adopted to transfer the tasks and data on the nodes with higher loads to the nodes with lower loads, so as to achieve balanced distribution of loads, thereby improving the overall performance and resource utilization of the system, avoiding node overload or load imbalance, and improving the stability and reliability of the system.

[0069] The following is a further introduction to the steps of determining and executing the load balancing strategy based on priority, as follows.

[0070] In some embodiments of the present application, determining and executing a load balancing strategy based on priority includes the following steps: determining the highest priority non-uniformly distributed IoT node in the complex building complex IoT as the target node for load scheduling, and selecting the lowest priority non-uniformly distributed IoT node as the starting node for load scheduling; when the connectivity between the starting node and the target node is greater than zero, determining the target scheduling link and load scheduling amount between the starting node and the target node, wherein the load scheduling amount is the amount of data of the load planned to be transferred from the starting node to the target node; and transferring the load data of the load scheduling amount in the starting node to the target node for processing through the target scheduling link.

[0071] Specifically, in this embodiment, nodes with high priorities usually have better performance and higher security, and are more suitable for load scheduling; after determining the priorities of each unevenly distributed IoT node, the node with the highest priority can be selected from all unevenly distributed nodes as the target node for load scheduling, thereby ensuring that the scheduling task gives priority to nodes that can handle the load more efficiently.

[0072] Afterwards, any node (taking the non-uniformly distributed IoT node with the lowest priority as an example) can be selected as the starting node, and the connectivity between it and the scheduling target node can be measured. If the connectivity is greater than zero, it means that there is a valid communication link between the two nodes, and this link can be selected for load scheduling. If the connectivity is zero, it means that the current node cannot communicate directly with the scheduling target node, and the scheduling link node needs to be reselected.

[0073] After determining the scheduling link, it is necessary to determine the load scheduling amount, where the load scheduling amount refers to the load transferred from the current starting node to the scheduling target node. Then the calculated load scheduling amount is added to the selected scheduling link, and the load balancing scheduling instruction is executed to transfer part of the load from the node with higher load to the node with lower load to achieve load balancing.

[0074] After executing a load balancing scheduling task, the load of all nodes in the scheduling link needs to be updated. If the current node is still overloaded, the priority of the unevenly distributed nodes needs to be re-measured and the load balancing scheduling task needs to be repeated until all nodes reach a balanced state.

[0075] By introducing load balancing technology, the data transmission path can be dynamically adjusted according to the real-time load of the node and other factors, so that the network load can be more evenly distributed to each node, avoiding the waste of resources caused by excessive load on some nodes. It helps to reduce the probability of overload of certain nodes, make better use of available resources, improve resource utilization efficiency, help improve the throughput and response speed of the system, optimize the performance of the entire system, and improve the stability and performance of the network.

[0076] This application scheme aims at the uneven distribution of node loads in complex building complexes, and proposes a method of priority calculation and load balancing. By integrating the load data of nodes and calculating the priority of nodes, a comprehensive evaluation of load conditions and node importance is achieved. Then, according to the priority of the nodes, a load balancing strategy is adopted to evenly distribute tasks and data among nodes to optimize system performance and resource utilization. It also involves the design and implementation of data acquisition, storage and processing mechanisms to support data management and application development in the Internet of Things environment of complex building complexes. This includes establishing suitable data acquisition equipment, selecting appropriate storage solutions, and developing efficient data processing algorithms to meet the needs of processing and analyzing large amounts of real-time data.

[0077] Through this application, the interconnection of various nodes in the building complex can be realized, and building equipment can be monitored and controlled in real time to improve energy efficiency, safety and sustainability. This will bring convenience and innovation to the management and operation of the building complex, and enhance the user experience and the overall value of the building complex.

[0078] According to an embodiment of the present application, an embodiment of an Internet of Things node load balancing device is also provided. Figure 5 Schematic diagram of a load balancing device for an Internet of Things node provided according to an embodiment of the present application. Figure 5 As shown, the device comprises:

[0079] The first calculation module 50 is used to determine the dynamic load value corresponding to the complex building complex Internet of Things, wherein the complex building complex Internet of Things includes: non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to characterize the overall load degree of the Internet of Things nodes in the complex building complex Internet of Things;

[0080] The second calculation module 52 is used to determine the load integration value according to the load data amount corresponding to all the non-uniformly distributed Internet of Things nodes in the complex building complex Internet of Things, wherein the load integration value is used to characterize the load degree of the non-uniformly distributed Internet of Things nodes in the complex building complex Internet of Things;

[0081] A priority determination module 54, used for determining the priority corresponding to each non-uniformly distributed IoT node when the load integration value is greater than the dynamic load value, wherein the priority is used to characterize the priority of the non-uniformly distributed IoT node in processing new load data;

[0082] The load balancing module 56 is used to determine and execute a load balancing strategy based on the priority, wherein the load balancing strategy is used to schedule load data in the non-uniformly distributed IoT nodes to reduce the overall load level of the non-uniformly distributed IoT nodes.

[0083] Optionally, determining the priority corresponding to each unevenly distributed Internet of Things node includes: determining the load-bearing space and occupied space of the unevenly distributed Internet of Things nodes, and determining the remaining load space and node space utilization corresponding to the unevenly distributed Internet of Things nodes based on the load-bearing space and occupied space; determining the safety factor and location distance parameter corresponding to the unevenly distributed Internet of Things nodes, wherein the safety factor is used to characterize the safety level of the unevenly distributed Internet of Things nodes, and the location distance parameter is used to characterize the connection relationship between the unevenly distributed Internet of Things nodes and other Internet of Things nodes in the Internet of Things of a complex building complex; determining the priority corresponding to the unevenly distributed Internet of Things nodes based on the remaining load space, node space utilization, safety factor, and location distance parameter.

[0084] Optionally, determining the security factor and location distance parameter corresponding to the unevenly distributed Internet of Things nodes includes: determining the access status corresponding to the unevenly distributed Internet of Things nodes, wherein the access status includes: active state, idle state, busy state and offline state; determining the security measurement value corresponding to the unevenly distributed Internet of Things nodes based on the type of encryption mechanism and firewall type corresponding to the unevenly distributed Internet of Things nodes; determining the security factor corresponding to the unevenly distributed Internet of Things nodes based on the access status and the security measurement value.

[0085] Optionally, determining the safety factor and location distance parameters corresponding to the unevenly distributed Internet of Things nodes also includes: determining the number of channels of the channels to which the unevenly distributed Internet of Things nodes are connected; determining the hop ratio corresponding to the unevenly distributed Internet of Things nodes, wherein the hop ratio is the ratio of the hop number corresponding to the unevenly distributed Internet of Things nodes to a preset standard hop number, and the hop number corresponding to the unevenly distributed Internet of Things nodes is the minimum number of intermediate nodes that the unevenly distributed Internet of Things nodes need to pass through to reach another unevenly distributed Internet of Things node in the Internet of Things of a complex building complex; based on the number of channels and the hop ratio, determining the location distance parameters corresponding to the unevenly distributed Internet of Things nodes.

[0086] Optionally, determining the dynamic load value corresponding to the Internet of Things for a complex building complex includes: determining an extended component of a channel formed by unevenly distributed Internet of Things nodes in the Internet of Things for the complex building complex, wherein the extended component is used to characterize the spatial variation of channel characteristics caused by uneven node distribution; determining the dynamic load value corresponding to the Internet of Things for the complex building complex based on the extended component, the load peak value and load interference value of the Internet of Things nodes in the Internet of Things for the complex building complex.

[0087] Optionally, determining the load integration value based on the load data volume corresponding to all the unevenly distributed IoT nodes in the complex building complex IoT includes: determining the number of data packets processed by the unevenly distributed IoT nodes in unit time, and determining the load data volume corresponding to the data packets; normalizing the load data volume corresponding to each unevenly distributed IoT node based on the maximum and minimum values ​​of the load data volume corresponding to all the unevenly distributed IoT nodes in the complex building complex IoT, and obtaining the normalized load data volume corresponding to each unevenly distributed IoT node; determining the weight value corresponding to the unevenly distributed IoT node based on the expected number of access users corresponding to each unevenly distributed IoT node; determining the load integration value based on the normalized load data volume and weight value corresponding to the unevenly distributed IoT nodes.

[0088] Optionally, based on the priority, determining and executing the load balancing strategy includes: determining the non-uniformly distributed IoT node with the highest priority in the complex building complex IoT as the target node for load scheduling, and selecting the non-uniformly distributed IoT node with the lowest priority as the starting node for load scheduling; when the connectivity between the starting node and the target node is greater than zero, determining the target scheduling link and load scheduling amount between the starting node and the target node, wherein the load scheduling amount is the amount of data of the load planned to be transferred from the starting node to the target node; and transferring the load data of the load scheduling amount in the starting node to the target node through the target scheduling link for processing.

[0089] It should be noted that the various modules in the above-mentioned Internet of Things node load balancing device can be program modules (for example, a set of program instructions that implement a certain specific function) or hardware modules. For the latter, it can be expressed in the following forms, but is not limited to this: the expression form of each of the above-mentioned modules is a processor, or the functions of each of the above-mentioned modules are implemented by a processor.

[0090] It should be noted that the IoT node load balancing device provided in this embodiment can be used to execute Figure 2 The Internet of Things node load balancing method shown, therefore, the relevant explanations and instructions on the above-mentioned Internet of Things node load balancing method are also applicable to the embodiments of the present application and will not be repeated here.

[0091] The embodiment of the present application also provides a non-volatile storage medium, the non-volatile storage medium includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the following Internet of Things node load balancing method by running the computer program: determining a dynamic load value corresponding to the Internet of Things of a complex building complex, wherein the Internet of Things of a complex building complex includes: non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to characterize the overall load level of the Internet of Things nodes in the Internet of Things of the complex building complex; determining a load integration value based on the amount of load data corresponding to all non-uniformly distributed Internet of Things nodes in the Internet of Things of the complex building complex, wherein the load integration value is used to characterize the load level of the non-uniformly distributed Internet of Things nodes in the Internet of Things of the complex building complex; when the load integration value is greater than the dynamic load value, determining the priority level corresponding to each non-uniformly distributed Internet of Things node, wherein the priority level is used to characterize the priority level of the non-uniformly distributed Internet of Things node in processing new load data; determining and executing a load balancing strategy based on the priority level, wherein the load balancing strategy is used to schedule the load data in the non-uniformly distributed Internet of Things nodes to reduce the overall load level of the non-uniformly distributed Internet of Things nodes.

[0092] The embodiment of the present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the Internet of Things node load balancing method described in each embodiment of the present application: determining a dynamic load value corresponding to a complex building complex Internet of Things, wherein the complex building complex Internet of Things includes: non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to characterize the overall load level of the Internet of Things nodes in the complex building complex Internet of Things; determining a load integration value based on the amount of load data corresponding to all non-uniformly distributed Internet of Things nodes in the complex building complex Internet of Things, wherein the load integration value is used to characterize the load level of the non-uniformly distributed Internet of Things nodes in the complex building complex Internet of Things; when the load integration value is greater than the dynamic load value, determining the priority level corresponding to each non-uniformly distributed Internet of Things node, wherein the priority level is used to characterize the priority level of the non-uniformly distributed Internet of Things node in processing new load data; determining and executing a load balancing strategy based on the priority level, wherein the load balancing strategy is used to schedule the load data in the non-uniformly distributed Internet of Things nodes to reduce the overall load level of the non-uniformly distributed Internet of Things nodes.

[0093] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0094] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0095] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0096] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0097] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0098] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0099] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for load balancing of IoT nodes. It is characterized in that include: Determine a dynamic load value corresponding to the complex building complex Internet of Things, wherein the complex building complex Internet of Things includes: non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to characterize the overall load degree of the Internet of Things nodes in the complex building complex Internet of Things; Determine a load integration value according to the load data amount corresponding to all the non-uniformly distributed Internet of Things nodes in the complex building complex Internet of Things, wherein the load integration value is used to characterize the load degree of the non-uniformly distributed Internet of Things nodes in the complex building complex Internet of Things; In the case where the load integration value is greater than the dynamic load value, determining the priority corresponding to each of the non-uniformly distributed Internet of Things nodes, wherein the priority is used to characterize the priority of the non-uniformly distributed Internet of Things nodes in processing new load data; Based on the priority, a load balancing strategy is determined and executed, wherein the load balancing strategy is used to schedule the load data in the non-uniformly distributed Internet of Things nodes to reduce the overall load level of the non-uniformly distributed Internet of Things nodes.

2. The method for balancing the load of IoT nodes according to claim 1, It is characterized in that Determining the priority corresponding to each of the non-uniformly distributed IoT nodes includes: Determine the load bearing space amount and the occupied space amount of the non-uniformly distributed Internet of Things nodes, and determine the remaining load space amount and the node space utilization rate corresponding to the non-uniformly distributed Internet of Things nodes based on the load bearing space amount and the occupied space amount; Determine the safety factor and location distance parameter corresponding to the non-uniformly distributed Internet of Things nodes, wherein the safety factor is used to characterize the safety level of the non-uniformly distributed Internet of Things nodes, and the location distance parameter is used to characterize the connection relationship between the non-uniformly distributed Internet of Things nodes and the remaining Internet of Things nodes in the complex building complex Internet of Things; The priorities corresponding to the non-uniformly distributed Internet of Things nodes are determined according to the remaining load space, the node space utilization, the safety factor, and the location distance parameter.

3. The method for balancing the load of IoT nodes according to claim 2, It is characterized in that Determining the safety factor and location distance parameters corresponding to the non-uniformly distributed IoT nodes includes: Determine the access status corresponding to the non-uniformly distributed IoT nodes, wherein the access status includes: active state, idle state, busy state and offline state; Determine the security metric value corresponding to the non-uniformly distributed Internet of Things nodes according to the type of encryption mechanism and the type of firewall corresponding to the non-uniformly distributed Internet of Things nodes; The security factor corresponding to the non-uniformly distributed Internet of Things nodes is determined according to the access status and the security metric value.

4. The method for balancing the load of IoT nodes according to claim 2, It is characterized in that Determining the safety factor and location distance parameter corresponding to the non-uniformly distributed IoT nodes also includes: Determining the number of channels to which the non-uniformly distributed IoT nodes are connected; Determine the hop ratio corresponding to the non-uniformly distributed Internet of Things nodes, wherein the hop ratio is the ratio of the hop number corresponding to the non-uniformly distributed Internet of Things nodes to a preset standard hop number, and the hop number corresponding to the non-uniformly distributed Internet of Things nodes is the minimum number of intermediate nodes that the non-uniformly distributed Internet of Things nodes need to pass through to reach another non-uniformly distributed Internet of Things node in the complex building complex Internet of Things; The location distance parameter corresponding to the non-uniformly distributed Internet of Things nodes is determined according to the number of channels and the hop ratio.

5. The method for balancing the load of IoT nodes according to claim 1, It is characterized in that Determine the dynamic load value corresponding to the Internet of Things of complex buildings including: Determine an extended component of a channel formed by the non-uniformly distributed IoT nodes in the complex building complex IoT, wherein the extended component is used to characterize the spatial variation of channel characteristics caused by the uneven distribution of nodes; The dynamic load value corresponding to the complex building complex Internet of Things is determined based on the extended component, the load peak value and the load interference value of the Internet of Things nodes in the complex building complex Internet of Things.

6. The method for balancing the load of IoT nodes according to claim 1, It is characterized in that Determining the load integration value according to the load data amount corresponding to all the non-uniformly distributed Internet of Things nodes in the complex building complex Internet of Things includes: Determine the number of data packets processed by the non-uniformly distributed IoT nodes per unit time, and determine the amount of load data corresponding to the data packets; According to the maximum and minimum values ​​of the load data amounts corresponding to all the non-uniformly distributed Internet of Things nodes in the complex building complex Internet of Things, the load data amounts corresponding to each of the non-uniformly distributed Internet of Things nodes are normalized to obtain the normalized load data amount corresponding to each of the non-uniformly distributed Internet of Things nodes; Determine the weight value corresponding to the non-uniformly distributed Internet of Things node according to the expected number of access users corresponding to each of the non-uniformly distributed Internet of Things nodes; The load integration value is determined according to the normalized load data volume and the weight value corresponding to the non-uniformly distributed Internet of Things nodes.

7. The method for balancing the load of IoT nodes according to claim 1, It is characterized in that Based on the priorities, determining and executing a load balancing strategy includes: Determine the non-uniformly distributed Internet of Things node with the highest priority in the complex building complex Internet of Things as the target node for load scheduling, and select the non-uniformly distributed Internet of Things node with the lowest priority as the starting node for load scheduling; In the case where the connectivity between the starting node and the target node is greater than zero, determining a target scheduling link and a load scheduling amount between the starting node and the target node, wherein the load scheduling amount is a data amount of a load planned to be transferred from the starting node to the target node; The load data of the load scheduling amount in the starting node is transferred to the target node through the target scheduling link for processing.

8. A load balancing device for Internet of Things nodes, It is characterized in that include: The first calculation module is used to determine the dynamic load value corresponding to the complex building complex Internet of Things, wherein the complex building complex Internet of Things includes: non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to characterize the overall load degree of the Internet of Things nodes in the complex building complex Internet of Things; A second calculation module is used to determine a load integration value according to the load data amount corresponding to all the non-uniformly distributed Internet of Things nodes in the complex building complex Internet of Things, wherein the load integration value is used to characterize the load degree of the non-uniformly distributed Internet of Things nodes in the complex building complex Internet of Things; A priority determination module, used for determining the priority corresponding to each of the non-uniformly distributed IoT nodes when the load integration value is greater than the dynamic load value, wherein the priority is used to characterize the priority of the non-uniformly distributed IoT nodes in processing new load data; The load balancing module is used to determine and execute a load balancing strategy based on the priority, wherein the load balancing strategy is used to schedule the load data in the non-uniformly distributed Internet of Things nodes to reduce the overall load level of the non-uniformly distributed Internet of Things nodes.

9. An electronic device, It is characterized in that include: A memory and a processor, wherein the processor is used to run a program stored in the memory, wherein the program executes the Internet of Things node load balancing method described in any one of claims 1 to 7 when running.

10. A non-volatile storage medium, It is characterized in that The non-volatile storage medium includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the Internet of Things node load balancing method described in any one of claims 1 to 7 by running the computer program.

11. A computer program product comprising a computer program, It is characterized in that When the computer program is executed by a processor, the steps of the Internet of Things node load balancing method described in any one of claims 1 to 7 are implemented.

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