Iot node load balancing method and device, electronic equipment and storage medium

Abstract

The application discloses a kind of Internet of Things node load balancing method, device, electronic equipment and storage medium.Therein, the method comprises: determining the dynamic load value corresponding to complex building group Internet of Things;According to the load data volume corresponding to all non-uniformly distributed Internet of Things nodes in complex building group Internet of Things, determine the load integration value;In the case where load integration value is greater than dynamic load value, determine the priority corresponding to each non-uniformly distributed Internet of Things node;According to the priority, determine and execute load balancing strategy, wherein the load balancing strategy is used to schedule the load data in non-uniformly distributed Internet of Things nodes, to reduce the overall load degree of non-uniformly distributed Internet of Things nodes.The application solves the technical problem of complex building group Internet of Things load imbalance caused by the lack of consideration of communication and cooperation between Internet of Things nodes in complex building group in the management mode in the related art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Things, in particular to an Internet of Things node load balancing method and device, electronic equipment and storage medium. BACKGROUND

[0002] Internet of Things nodes in complex building groups have differences in geographical location, device model, etc., resulting in a non-uniform distribution structure feature of communication nodes. For example, some nodes may be concentrated in a certain area, while nodes in other areas are relatively few. This uneven distribution can cause some nodes to be overloaded, while other nodes are lightly loaded, resulting in unbalanced resource utilization.

[0003] In the Internet of Things in complex building groups, nodes need to interact and work together. However, the static management method in the related art lacks consideration of communication and collaboration between Internet of Things nodes, and fails to fully consider the communication needs between nodes, which can lead to unbalanced load of nodes in the Internet of Things in complex building groups, causing communication congestion and data transmission delay.

[0004] In view of the above problems, no effective solution has been proposed so far. SUMMARY

[0005] The embodiments of the present application provide an Internet of Things node load balancing method, device, electronic equipment and storage medium to at least solve the technical problem of unbalanced load of the Internet of Things in complex building groups caused by the lack of consideration of communication and collaboration between Internet of Things nodes in the management method in the related art.

[0006] According to an aspect of an embodiment of the present application, an Internet of Things node load balancing method is provided, comprising: determining a dynamic load value corresponding to the Internet of Things in complex building groups, wherein the Internet of Things in complex building groups comprises non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to represent the overall load degree of the Internet of Things nodes in the Internet of Things in complex building groups; determining a load integration value according to the load data amount corresponding to all non-uniformly distributed Internet of Things nodes in the Internet of Things in complex building groups, wherein the load integration value is used to represent the load degree of the non-uniformly distributed Internet of Things nodes in the Internet of Things in complex building groups; in the case 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, wherein the priority is used to represent the priority degree of the non-uniformly distributed Internet of Things node in processing new load data; determining and executing a load balancing strategy according to 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 degree of the non-uniformly distributed Internet of Things nodes.

[0007] Optionally, determining the priority corresponding to each non-uniformly distributed IoT node comprises: determining a load carrying space amount and an occupied space amount of the non-uniformly distributed IoT node, and determining a residual load space amount and a node space utilization rate of the non-uniformly distributed IoT node according to the load carrying space amount and the occupied space amount; determining a security coefficient and a location distance parameter of the non-uniformly distributed IoT node, wherein the security coefficient is used to represent the security degree of the non-uniformly distributed IoT node, and the location distance parameter is used to represent the connection relationship between the non-uniformly distributed IoT node and the remaining IoT nodes in the complex building group IoT; and determining the priority corresponding to the non-uniformly distributed IoT node according to the residual load space amount, the node space utilization rate, the security coefficient, and the location distance parameter.

[0008] Optionally, determining the security coefficient and the location distance parameter corresponding to the non-uniformly distributed IoT node comprises: determining an access state corresponding to the non-uniformly distributed IoT node, wherein the access state comprises an active state, an idle state, a busy state, and an offline state; determining a security metric value corresponding to the non-uniformly distributed IoT node according to the type of the encryption mechanism and the type of the firewall corresponding to the non-uniformly distributed IoT node; and determining the security coefficient corresponding to the non-uniformly distributed IoT node according to the access state and the security metric value.

[0009] Optionally, determining the security coefficient and the location distance parameter corresponding to the non-uniformly distributed IoT node further comprises: determining the number of channels connected by the non-uniformly distributed IoT node; determining a hop ratio corresponding to the non-uniformly distributed IoT node, wherein the hop ratio is the ratio of the number of hops of the non-uniformly distributed IoT node to a preset standard hop number, and the number of hops of the non-uniformly distributed IoT node is the minimum number of intermediate nodes required by the non-uniformly distributed IoT node to reach another non-uniformly distributed IoT node in the complex building group IoT; and determining the location distance parameter corresponding to the non-uniformly distributed IoT node according to the number of channels and the hop ratio.

[0010] Optionally, determining the dynamic load value corresponding to the complex building group IoT comprises: determining an expansion component of a channel formed by the non-uniformly distributed IoT nodes in the complex building group IoT, wherein the expansion component is used to represent the spatial variation of the channel characteristics caused by the uneven distribution of nodes; and determining the dynamic load value corresponding to the complex building group IoT according to the expansion component, a load peak value, and a load interference value of the IoT nodes in the complex building group IoT.

[0011] Optionally, determining the load integration value according to the load data amount corresponding to all of the non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things comprises: determining the number of data packets processed by the non-uniformly distributed Internet of Things nodes in a unit of time, and determining the load data amount corresponding to the data packets; performing normalization processing on the load data amount corresponding to each of the non-uniformly distributed Internet of Things nodes according to the maximum value and the minimum value of the load data amount corresponding to all of the non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, to obtain the load data amount corresponding to each of the non-uniformly distributed Internet of Things nodes after normalization processing; determining the weight value corresponding to the non-uniformly distributed Internet of Things nodes according to the number of predicted access users corresponding to each of the non-uniformly distributed Internet of Things nodes; and determining the load integration value according to the load data amount corresponding to each of the non-uniformly distributed Internet of Things nodes after normalization processing and the weight value.

[0012] Optionally, determining and executing the load balancing strategy according to the priority comprises: determining the non-uniformly distributed Internet of Things node with the highest priority in the complex building group Internet of Things as a target node of load scheduling, and selecting the non-uniformly distributed Internet of Things node with the lowest priority as a starting node of load scheduling; in the case that 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 the data amount of the load planned to be transferred from the starting node to the target node; and transferring the load data with the size 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 embodiments of the present application, a kind of Internet of Things node load balancing device is also provided, comprising: first calculation module, for determining the dynamic load value corresponding to complex building group Internet of Things, wherein, complex building group Internet of Things includes: non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, dynamic load value is used to represent the overall load degree of Internet of Things nodes in complex building group Internet of Things;Second calculation module, for determining the load integration value according to the load data amount corresponding to all of the non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, wherein, load integration value is used to represent the load degree of non-uniformly distributed Internet of Things nodes in complex building group Internet of Things;Priority determination module, for determining the priority corresponding to each of the non-uniformly distributed Internet of Things nodes in the case that load integration value is greater than dynamic load value, wherein, priority is used to represent the priority degree of non-uniformly distributed Internet of Things nodes processing new load data;Load balancing module, for determining and executing load balancing strategy according to priority, wherein, load balancing strategy is used to schedule load data in non-uniformly distributed Internet of Things nodes, to reduce the overall load degree of non-uniformly distributed Internet of Things nodes.

[0014] According to a further aspect of the embodiments of the present application, an electronic device is provided, comprising a memory and a processor, the processor being configured to execute a program stored in the memory, wherein the program, when executed, performs the method for load balancing of Internet of Things nodes.

[0015] According to a further aspect of the embodiments of the present application, a non-transitory storage medium is provided, comprising a stored computer program, wherein a device in which the non-transitory storage medium is located performs the method for load balancing of Internet of Things nodes by executing the computer program.

[0016] According to a further aspect of the embodiments of the present application, a computer program product is provided, comprising a computer program, the computer program, when executed by a processor, implementing the steps of the method for load balancing of Internet of Things nodes.

[0017] In the embodiments of the present application, a dynamic load value corresponding to a complex building group Internet of Things is determined, wherein the complex building group Internet of Things comprises non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to represent the overall load degree of the Internet of Things nodes in the complex building group Internet of Things; a load integration value is determined according to the load data amount corresponding to all non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, wherein the load integration value is used to represent the load degree of the non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things; in the case that the load integration value is greater than the dynamic load value, a priority corresponding to each non-uniformly distributed Internet of Things node is determined, wherein the priority is used to represent the priority degree of the non-uniformly distributed Internet of Things node in processing new load data; and a load balancing strategy is determined and executed according to the priority, wherein the load balancing strategy is used to schedule the 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, and by introducing a non-uniformly distributed node random load balancing optimization technology, priority calculation and scheduling link generation are adopted to implement 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 capability of the complex building group Internet of Things, so as to realize the precise and intelligent management of the complex building group and ensure the stable operation of the Internet of Things system, thereby solving the technical problem of unbalanced load of the complex building group Internet of Things caused by the lack of consideration of communication and cooperation between the Internet of Things nodes in the complex building group in the management mode in the related art. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings, which are included to provide a further understanding of the present application and are incorporated in and constitute a part of this application, illustrate embodiments of the present application and serve to explain the present application. In the drawings:

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

[0020] Figure 2 A flowchart of a method for load balancing of Internet of Things nodes according to an embodiment of the present application is provided.

[0021] Figure 3 A schematic diagram of distribution of Internet of Things nodes in a complex building group according to an embodiment of the present application is provided.

[0022] Figure 4 A schematic diagram of a random load data collection process of non-uniformly distributed nodes according to an embodiment of the present application is provided.

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

[0024] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to only those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to the process, method, product, or device.

[0026] Internet of Things nodes in a complex building group have differences in geographical location, device model, and other information, resulting in a non-uniform distribution structure feature of communication nodes. For example, some nodes may be concentrated in a certain area, while nodes in other areas are relatively few. This non-uniform distribution can cause some nodes to be overloaded, while other nodes are lightly loaded, resulting in unbalanced resource utilization.

[0027] In the complex building group Internet of Things, data interaction and collaborative work are needed between nodes. However, the static management mode in the related art lacks consideration of the communication and collaboration between Internet of Things nodes, and fails to fully consider the communication demand between nodes, which may cause unbalanced load of each node in the complex building group Internet of Things, and cause problems such as communication congestion and delay of data transmission.

[0028] To solve the above problems, the related solutions are provided in the embodiments of the present application, which are described in detail below.

[0029] According to the embodiments of the present application, a method embodiment for balancing the load 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 the 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 embodiment provided by the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 A hardware structure block diagram of a computer terminal (or electronic device) for implementing the method for balancing the load of Internet of Things nodes is shown. As shown in Figure 1 The computer terminal 10 (or electronic device) can include one or more processors 102 (the processor 102 can include but is not limited to a microprocessor MCU or a programmable logic device FPGA processing device), a memory 104 for storing data, and a transmission device 106 for communication function. In addition, it can also include a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which can be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. Those skilled in the art can understand that Figure 1 The structure shown is only schematic, which does not limit the structure of the above-mentioned electronic device. For example, the computer terminal 10 can also include more or less components than those shown in Figure 1 or have a different configuration from that shown in Figure 1 .

[0031] It should be noted that the one or more processors 102 and / or other data processing circuitry described above can be referred to herein generically as "data processing circuitry". The data processing circuitry can be embodied in whole or in part as software, hardware, firmware, or any combination thereof. Furthermore, the data processing circuitry can be a single standalone processing module, or it can be incorporated in whole or in part within any one of other elements of the computer terminal 10 (or electronic device). As referred to in the embodiments herein, the data processing circuitry functions as a processor to control, for example, selection of variable resistance terminal paths connected to the interface.

[0032] The memory 104 can be used to store software programs of application software and modules, such as program instructions / data storage means corresponding to the Internet of Things node load balancing method in the embodiments of the present application. The processor 102 performs various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, implements the Internet of Things node load balancing method described above. The memory 104 can include a high-speed random access memory, and can also include a non-volatile memory, such as one or more magnetic storage devices, flash memories, or other non-volatile solid-state memories. In some examples, the memory 104 can further include a memory remotely arranged with respect to the processor 102, which can be connected to the computer terminal 10 through a network. Examples of the 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. Specific examples of the network can 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 be able to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, RF) module, which is used to communicate with the Internet in a wireless manner.

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

[0035] In the above operating environment, the embodiments of the present application provide an Internet of Things node load balancing method, Figure 2 is a schematic diagram of a method flow of an Internet of Things node load balancing method according to the embodiments of the present application, as Figure 2 shown, the method comprises the following steps:

[0036] In step S202, a dynamic load value corresponding to the complex building group Internet of Things is determined, wherein the complex building group Internet of Things comprises non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to represent the overall load degree of the Internet of Things nodes in the complex building group Internet of Things.

[0037] In step S204, a load integration value is determined according to the load data amount corresponding to all non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, wherein the load integration value is used to represent the load degree of the non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things.

[0038] In step S206, the priority corresponding to each non-uniformly distributed Internet of Things node is determined in the case that the load integration value is greater than the dynamic load value, wherein the priority is used to represent the priority degree of the non-uniformly distributed Internet of Things node in processing new load data.

[0039] In step S208, a load balancing strategy is determined and executed according to the priority, wherein the load balancing strategy is used to schedule the 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.

[0040] Through the above steps, by introducing the non-uniformly distributed node random load balancing optimization technology, the priority calculation and the 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 capability of the complex building group Internet of Things, so as to realize the precise and intelligent management of the complex building group, and ensure the stable operation of the Internet of Things system, thereby solving the complex building group Internet of Things load imbalance technical problem caused by the lack of consideration of the communication and cooperation between the Internet of Things nodes in the complex building group in the related technology.

[0041] The Internet of Things node load balancing method for the complex building group Internet of Things is to solve the Internet of Things load imbalance problem caused by the non-uniformly distributed building structure. In this embodiment, by collecting and integrating the non-uniformly distributed node random load data, the priority of the node is calculated by using the MPDTR (Markov Prediction Duplicate Transmission Routing) routing protocol, the scheduling link is generated, and the node load balancing scheduling task is completed. The MPDTR is a load balancing routing protocol based on the cooperation between nodes. It takes the priority of the node as an important indicator of the load capacity of the node, calculates the distance and load amount between nodes according to the cooperation relationship between nodes, and predicts the generation of scheduling link. This model fully considers the distance, access amount, priority and other influencing factors of the node, so that the load amount of the node can be more accurately calculated and scheduled, and has a quantitative optimization effect, which has a positive effect on the stable operation of the Internet of Things.

[0042] The steps S202 to S208 of the embodiment of the present application are further described below.

[0043] In the complex building group Internet of Things environment, due to the design asymmetry of the building structure and the scale of the building group, the deployment of the Internet of Things nodes is not balanced. In the complex building group Internet of Things, appropriate communication technologies and devices such as sensors, wireless networks are used to connect each node in the building group, establish network infrastructure including network topology, network connection and communication protocol, etc., to ensure communication and data transmission between nodes.

[0044] As shown in the specific embodiment of the present application, Figure 3 The non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things are usually buildings with large and dense human flow, which are prone to cause unbalanced load access sources, while the uniformly distributed Internet of Things nodes are usually building Internet of Things access nodes with relatively stable access users and are not prone to cause load balancing problems.

[0045] The embodiment of the present application can solve the problem of node load difference in the complex building group Internet of Things by introducing a non-uniformly distributed node random load balancing optimization technology. The sensor device and wireless network are used to build the Internet of Things environment, and the load data is collected and integrated according to the node distribution position. Based on the MPDTR routing protocol, the node load balancing scheduling task is realized by using priority calculation and scheduling link generation, which optimizes the load distribution and performance of the Internet of Things, and realizes precise and intelligent management. The purpose is to improve the load balancing of the Internet of Things, improve the stability and performance of the system, avoid node overload and performance degradation by optimizing node load balancing, fully utilize idle node resources, reduce congestion probability, delay and improve data transmission efficiency, and improve the response speed and user experience of the system, so as to ensure the stability and efficiency of the complex building group Internet of Things system. The following is a specific description.

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

[0047] In some embodiments of the present application, determining the dynamic load value corresponding to the complex building group Internet of Things includes the following steps: determining that the non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things form an expansion component of a channel, wherein the expansion component is used to represent the spatial variation of channel characteristics caused by uneven distribution of nodes; determining the dynamic load value corresponding to the complex building group Internet of Things according to the expansion component, the load peak value and the load interference value of the Internet of Things nodes in the complex building group Internet of Things.

[0048] Specifically, the calculation formula of the dynamic load value M is as shown in the following formula: Wherein, f is the extension component of the channel formed by the non-uniformly distributed Internet of Things nodes, which is jointly determined by the distance between the uniformly distributed nodes, the size of the transmitted data, the channel bandwidth, and the channel attenuation coefficient g. γ is the load peak value of the node, t is the time, and m is the load interference threshold, which has different values in different environments, usually between 0.001 and 0.05.

[0049] In addition, in the embodiments of the present application, the load integration value can also be determined by collecting the load data of each node in the complex building group Internet of Things, such as load amount, load type and load change, integrating the random load data of the non-uniformly distributed nodes, and the specific steps are as follows.

[0050] In some embodiments of the present application, the load integration value is determined according to the load data amount corresponding to all non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, including the following steps: determining the number of data packets processed by the non-uniformly distributed Internet of Things nodes in unit time, and determining the load data amount corresponding to the data packets; according to the maximum and minimum values of the load data amount corresponding to all non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, the load data amount corresponding to each non-uniformly distributed Internet of Things node is normalized to obtain the load data amount corresponding to each non-uniformly distributed Internet of Things node after normalization; according to the expected number of access users corresponding to each non-uniformly distributed Internet of Things node, the weight value corresponding to the non-uniformly distributed Internet of Things node is determined; according to the normalized load data amount and the weight value corresponding to the non-uniformly distributed Internet of Things node, the load integration value is determined.

[0051] In this embodiment, for all non-uniformly distributed Internet of Things nodes, the integration of the random load data of the Internet of Things nodes can be completed according to the process as shown in Figure 4 Specifically, the total number of data packets processed by each non-uniformly distributed Internet of Things node and the corresponding response time are collected, and the number of data packets processed in unit time is calculated; then, the data packets are parsed to determine the load data amount corresponding to each non-uniformly distributed Internet of Things node.

[0052] Since the data loaded by each node includes tables, images, data and other forms, in order to make different properties reflect equal comprehensive effect, the data is normalized, and the processing process is as shown in the following formula:

[0053]

[0054] Wherein, x c,i represents the load data amount corresponding to the node after normalization, and x irepresents the load data volume corresponding to the node before normalization, where i represents the i-th specific non-uniformly distributed IoT node, X represents the load data set corresponding to all non-uniformly distributed IoT nodes in the complex building group IoT, and max(X) and min(X) represent the maximum and minimum load data volumes in the set.

[0055] After that, the random load data collected at the positions of the respective non-uniformly distributed IoT nodes is integrated, and the load integration value is obtained wherein, is the weight value corresponding to the non-uniformly distributed IoT node, which can be set according to the expected number of users accessing the node, and the value range is from 0 to 0.9. The greater the threshold value, the more users accessing the node than the users of the uniform node, but with the automatic optimization of the algorithm, the weight value parameter will be dynamically changed. node is the number of non-uniformly distributed nodes included in the complex building group IoT.

[0056] The embodiments of the present application can analyze and evaluate the load conditions of the nodes by collecting the load data of the respective nodes in the complex building group IoT and integrating the random load data of the non-uniformly distributed nodes, and understand the distribution characteristics and load difference conditions of the nodes. This provides a basis for subsequent load balancing optimization to achieve balanced distribution of loads among the nodes and improvement of system performance.

[0057] After obtaining the dynamic load value and the 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. Finally, through load scheduling, the random load balancing optimization target of the non-uniformly distributed nodes is achieved, thereby improving the load balancing and stability of the network. The following will be specifically described.

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

[0059] In some embodiments of the present application, the step of determining the priority corresponding to each non-uniformly distributed IoT node comprises the following steps: determining the load carrying space amount and the occupied space amount of the non-uniformly distributed IoT node, and determining the residual load space amount and the node space utilization of the non-uniformly distributed IoT node according to the load carrying space amount and the occupied space amount; determining the security coefficient and the location distance parameter of the non-uniformly distributed IoT node, wherein the security coefficient is used to represent the security degree of the non-uniformly distributed IoT node, and the location distance parameter is used to represent the connection relationship between the non-uniformly distributed IoT node and the remaining IoT nodes in the complex building group IoT; and determining the priority corresponding to the non-uniformly distributed IoT node according to the residual load space amount, the node space utilization, the security coefficient, and the location distance parameter.

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

[0061]

[0062] wherein W = W all -W occupy , W is the residual load space of the node (i.e., the residual load space described above), W all is the load carrying space amount of the non-uniformly distributed IoT node, W occupy is the occupied space amount; ξ1 and ξ2 are constant coefficients; μ use is the node utilization (i.e., the node space utilization described above); is the security coefficient of the node, N L ×n Hops is the location distance parameter described above, wherein N L and n Hops represent the number of node connection channels and the hop number ratio, respectively.

[0063] The determination of the security coefficient is specifically as follows.

[0064] In some embodiments of the present application, the step of determining the security coefficient and the location distance parameter corresponding to the non-uniformly distributed IoT node comprises the following steps: determining the access state corresponding to the non-uniformly distributed IoT node, wherein the access state comprises: an active state, an idle state, a busy state, and an offline state; determining the security metric value corresponding to the non-uniformly distributed IoT node according to the type of encryption mechanism and the type of firewall corresponding to the non-uniformly distributed IoT node; and determining the security coefficient corresponding to the non-uniformly distributed IoT node according to the access state and the security metric value.

[0065] Specifically, wherein q i , s attri and w i are the access state, security metric value and weight of the i-th attribute of the node respectively, in the embodiment, the access state 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, the security characteristics include but are not limited to: the strength of the encryption mechanism, the effectiveness of the authentication mechanism, the configuration of the firewall, the intrusion detection and defense ability, etc. The weight value w i is higher, indicating that the attribute is more important in evaluating the security of the node.

[0066] The determination step of the above position distance parameter N L x n Hops is specifically as follows.

[0067] In some embodiments of the present application, the step of determining the security coefficient and the position distance parameter corresponding to the non-uniformly distributed Internet of Things node further comprises the following steps: determining the channel quantity N L of the channel connected by the non-uniformly distributed Internet of Things node; determining the hop ratio n Hops corresponding to the non-uniformly distributed Internet of Things node, wherein the hop ratio is the ratio of the hop quantity corresponding to the non-uniformly distributed Internet of Things node to the preset standard hop quantity, the hop quantity corresponding to the non-uniformly distributed Internet of Things node is the minimum number of intermediate nodes required by the non-uniformly distributed Internet of Things node to reach another non-uniformly distributed Internet of Things node in the complex building group Internet of Things; determining the position distance parameter corresponding to the non-uniformly distributed Internet of Things node according to the channel quantity and the hop ratio.

[0068] The embodiment of the present application obtains the comprehensive evaluation of the load condition and importance of the node by integrating the load data of the non-uniformly distributed node and calculating the priority of the node. Then, according to the priority of the node, the corresponding load balancing strategy can be adopted to transfer the tasks and data on the node with higher load to the node with lower load, so as to realize the balanced distribution of the load, improve the overall performance and resource utilization of the system, avoid the situation of node overload or unbalanced load, and improve the stability and reliability of the system.

[0069] The steps of determining and executing the load balancing strategy according to the priority are further introduced as follows.

[0070] In some embodiments of the present application, the priority-based determination and execution of the load balancing strategy includes the following steps: determining and executing the load balancing strategy according to the priority, including determining the non-uniformly distributed IoT node with the highest priority in the complex building IoT as the target node of load scheduling, and selecting the non-uniformly distributed IoT node with the lowest priority as the starting node of load scheduling; in the case that the connectivity between the starting node and the target node is greater than zero, determining the target scheduling link and the 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; transferring the load data with the size of the load scheduling amount in the starting node to the target node for processing through the target scheduling link.

[0071] Specifically, in the present embodiment, the node with high priority generally has better performance and higher security, and is more suitable for load scheduling; after determining the priority of each non-uniformly distributed IoT node, the node with the highest priority can be selected as the target node of load scheduling among all non-uniformly distributed nodes, so as to ensure that the scheduling task gives priority to the node capable of processing the load more efficiently.

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

[0073] After the scheduling link is determined, the load scheduling amount needs to be determined, wherein the load scheduling amount refers to the amount of load transferred from the current starting node to the target node of scheduling; 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 high load to the node with low load, so as to realize load balancing.

[0074] After the load balancing scheduling task is executed once, the load of all nodes in the scheduling link needs to be updated. If the current node still has an overload condition, the priority of the non-uniformly distributed node needs to be re-measured, and the load balancing scheduling task needs to be repeatedly executed until all nodes reach the balanced state.

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

[0076] The application scheme proposes a priority calculation and load balancing method for the non-uniform distribution of node loads in complex building groups. By integrating node load data and calculating node priority, 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 balance the allocation of tasks and data among nodes, optimizing system performance and resource utilization. It also involves designing and implementing data collection, storage and processing mechanisms to support data management and application development in complex building group IoT environments. This includes establishing appropriate data collection equipment, selecting appropriate storage solutions, and developing efficient data processing algorithms to meet the processing and analysis needs of large amounts of real-time data.

[0077] Through the application, interconnection and intercommunication of nodes in the building group can be realized, real-time monitoring and control of building equipment can be achieved, and energy efficiency, safety and sustainability can be improved. This will bring convenience and innovation to the management and operation of building groups, improve user experience and the overall value of building groups.

[0078] According to the embodiments of the application, an embodiment of an Internet of Things node load balancing device is also provided. Figure 5 is a structural diagram of an Internet of Things node load balancing device provided by the embodiments of the application. As shown in Figure 5 , the device includes:

[0079] The first calculation module 50 is configured to determine the dynamic load value of the complex building group Internet of Things, wherein the complex building group 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 represent the overall load degree of the Internet of Things nodes in the complex building group Internet of Things;

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

[0081] The priority determination module 54 is configured to determine a priority corresponding to each of the non-uniformly distributed IoT nodes when the load integration value is greater than the dynamic load value, where the priority is used to represent a priority degree of the non-uniformly distributed IoT node in processing new load data.

[0082] The load balancing module 56 is configured to determine and execute a load balancing strategy according to the priority, where the load balancing strategy is used to schedule the load data in the non-uniformly distributed IoT nodes, so as to reduce the overall load degree of the non-uniformly distributed IoT nodes.

[0083] Optionally, the priority corresponding to each of the non-uniformly distributed IoT nodes is determined by determining a load bearing space amount and an occupied space amount of the non-uniformly distributed IoT node, and determining a remaining load space amount and a node space utilization rate of the non-uniformly distributed IoT node according to the load bearing space amount and the occupied space amount; determining a security coefficient and a location distance parameter of the non-uniformly distributed IoT node, where the security coefficient is used to represent a security degree of the non-uniformly distributed IoT node, and the location distance parameter is used to represent a connection relationship between the non-uniformly distributed IoT node and the remaining IoT nodes in the complex building group IoT; and determining the priority corresponding to the non-uniformly distributed IoT node according to the remaining load space amount, the node space utilization rate, the security coefficient, and the location distance parameter.

[0084] Optionally, the security coefficient and the location distance parameter corresponding to the non-uniformly distributed IoT node are determined by determining an access state of the non-uniformly distributed IoT node, where the access state includes an active state, an idle state, a busy state, and an offline state; determining a security metric value of the non-uniformly distributed IoT node according to a type of an encryption mechanism and a type of a firewall of the non-uniformly distributed IoT node; and determining the security coefficient of the non-uniformly distributed IoT node according to the access state and the security metric value.

[0085] Optionally, the security coefficient and the location distance parameter corresponding to the non-uniformly distributed IoT node are further determined by determining a channel number of a channel connected to the non-uniformly distributed IoT node; determining a hop ratio of the non-uniformly distributed IoT node, where the hop ratio is a ratio of a hop number of the non-uniformly distributed IoT node to a preset standard hop number, and the hop number of the non-uniformly distributed IoT node is a minimum number of intermediate nodes required for the non-uniformly distributed IoT node to reach another non-uniformly distributed IoT node in the complex building group IoT; and determining the location distance parameter of the non-uniformly distributed IoT node according to the channel number and the hop ratio.

[0086] Optionally, determining the dynamic load value corresponding to the complex building group Internet of Things comprises: determining an extension component formed by the non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, wherein the extension component is used to represent the spatial variation of channel characteristics caused by the non-uniform distribution of nodes; and determining the dynamic load value corresponding to the complex building group Internet of Things according to the extension component, the load peak value and the load interference value of the Internet of Things nodes in the complex building group Internet of Things.

[0087] Optionally, 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 group Internet of Things comprises: determining the number of data packets processed by the non-uniformly distributed Internet of Things nodes in a unit of time, and determining the load data amount corresponding to the data packets; performing normalization processing on the load data amount corresponding to each non-uniformly distributed Internet of Things node according to the maximum value and the minimum value of the load data amount corresponding to all the non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, to obtain the load data amount corresponding to each non-uniformly distributed Internet of Things node after normalization processing; determining the weight value corresponding to the non-uniformly distributed Internet of Things nodes according to the number of predicted access users corresponding to each non-uniformly distributed Internet of Things node; and determining the load integration value according to the load data amount corresponding to the non-uniformly distributed Internet of Things nodes after normalization processing and the weight value.

[0088] Optionally, determining and executing the load balancing strategy according to the priority comprises: determining the non-uniformly distributed Internet of Things node with the highest priority in the complex building group Internet of Things as a target node of load scheduling, and selecting the non-uniformly distributed Internet of Things node with the lowest priority as a starting node of load scheduling; in the case that 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 the data amount of the load planned to be transferred from the starting node to the target node; and transferring the load data with the size 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 each module in the above Internet of Things node load balancing device can be a program module (for example, a set of program instructions for implementing a certain specific function) or a hardware module. For the latter, it can be in the following form, but is not limited to this: the form of each module is a processor, or the functions of each module are implemented by a processor.

[0090] It should be noted that the Internet of Things node load balancing device provided in the present embodiment can be used to execute the Internet of Things node load balancing method shown in Figure 2 Therefore, the related explanations and descriptions of the above Internet of Things node load balancing method are also applicable to the present embodiment, and will not be repeated here.

[0091] The embodiment of the present application further provides a nonvolatile storage medium comprising a stored computer program, wherein a device in which the nonvolatile 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 a complex building group Internet of Things, wherein the complex building group Internet of Things comprises non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to represent the overall load degree of the Internet of Things nodes in the complex building group Internet of Things; determining a load integration value according to the load data amount corresponding to all non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, wherein the load integration value is used to represent the load degree of the non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things; determining a priority corresponding to each non-uniformly distributed Internet of Things node in the case that the load integration value is greater than the dynamic load value, wherein the priority is used to represent the priority degree of the non-uniformly distributed Internet of Things node in processing new load data; and determining and executing a load balancing strategy according to the priority, wherein the load balancing strategy is used to schedule the 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.

[0092] The embodiment of the present application further provides a computer program product comprising a computer program, which, when executed by a processor, implements the steps of the Internet of Things node load balancing method described in various embodiments of the present application: determining a dynamic load value corresponding to a complex building group Internet of Things, wherein the complex building group Internet of Things comprises non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to represent the overall load degree of the Internet of Things nodes in the complex building group Internet of Things; determining a load integration value according to the load data amount corresponding to all non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, wherein the load integration value is used to represent the load degree of the non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things; determining a priority corresponding to each non-uniformly distributed Internet of Things node in the case that the load integration value is greater than the dynamic load value, wherein the priority is used to represent the priority degree of the non-uniformly distributed Internet of Things node in processing new load data; and determining and executing a load balancing strategy according to the priority, wherein the load balancing strategy is used to schedule the 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.

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

[0094] In the above-mentioned embodiments of the present application, the description of each embodiment has its own emphasis, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0095] In several embodiments provided in the present application, it should be understood that the disclosed technology can be implemented by other ways. Among them, the above-described device embodiments are only schematic, for example, the division of the units can be a logical function division, and actual implementation can have another division manner, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed units can be indirect coupling or communication connection through some interfaces, units or modules, and can be electrical or other forms.

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

[0097] In addition, the functional units in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0098] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part of the prior art that contributes to the technical solutions or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0099] The above description is only the preferred embodiment of the present application, and it should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. A load balancing method for Internet of Things (IoT) nodes, characterized in that, The method comprises the following steps: determining a dynamic load value corresponding to a complex building group Internet of Things, comprising: determining an extension component formed by non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, wherein the extension component is used to represent the spatial variation of channel characteristics caused by non-uniform distribution of nodes; determining the dynamic load value corresponding to the complex building group Internet of Things according to the extension component, the load peak value and the load interference value of the Internet of Things nodes in the complex building group Internet of Things, wherein the complex building group Internet of Things comprises non-uniformly distributed Internet of Things nodes and uniformly distributed Internet of Things nodes, and the dynamic load value is used to represent the overall load degree of the Internet of Things nodes in the complex building group Internet of Things; determining a load integration value according to the load data amount corresponding to all non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, wherein the load integration value is used to represent the load degree of the non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things; in the case 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, wherein the priority is used to represent the priority degree of the non-uniformly distributed Internet of Things node in processing new load data; determining and executing a load balancing strategy according to 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 degree of the non-uniformly distributed Internet of Things nodes.

2. The IoT node load balancing method of claim 1, wherein, The method for determining the priority corresponding to each non-uniformly distributed Internet of Things node comprises: determining the load bearing space amount and the occupied space amount of the non-uniformly distributed Internet of Things nodes, and determining the residual load space amount and the node space utilization rate corresponding to the non-uniformly distributed Internet of Things nodes according to the load bearing space amount and the occupied space amount; determining a safety coefficient and a location distance parameter corresponding to the non-uniformly distributed Internet of Things nodes, wherein the safety coefficient is used to represent the safety degree of the non-uniformly distributed Internet of Things nodes, and the location distance parameter is used to represent the connection relationship between the non-uniformly distributed Internet of Things nodes and the remaining Internet of Things nodes in the complex building group Internet of Things; determining the priority corresponding to the non-uniformly distributed Internet of Things nodes according to the residual load space amount, the node space utilization rate, the safety coefficient and the location distance parameter.

3. The IoT node load balancing method of claim 2, wherein, The method for determining the safety coefficient and the location distance parameter corresponding to the non-uniformly distributed Internet of Things nodes comprises: determining an access state corresponding to the non-uniformly distributed Internet of Things nodes, wherein the access state comprises an active state, an idle state, a busy state and an offline state; determining a safety 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; determining the safety coefficient corresponding to the non-uniformly distributed Internet of Things nodes according to the access state and the safety metric value.

4. The IoT node load balancing method of claim 2, wherein, The method for determining the safety coefficient and the location distance parameter corresponding to the non-uniformly distributed Internet of Things nodes further comprises: determining a channel number of a channel to which the non-uniformly distributed Internet of Things node is connected; determining a hop number ratio corresponding to the non-uniformly distributed Internet of Things node, wherein the hop number ratio is a ratio of a hop number corresponding to the non-uniformly distributed Internet of Things node to a preset standard hop number, and the hop number corresponding to the non-uniformly distributed Internet of Things node is a minimum number of intermediate nodes required for the non-uniformly distributed Internet of Things node to reach another non-uniformly distributed Internet of Things node in the complex building group Internet of Things; determining the location distance parameter corresponding to the non-uniformly distributed Internet of Things node according to the channel number and the hop number ratio.

5. The IoT node load balancing method of claim 1, wherein, determining a load integration value according to load data amounts corresponding to all non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things includes: determining a number of data packets processed by the non-uniformly distributed Internet of Things node in a unit of time, and determining a load data amount corresponding to the data packets; normalizing the load data amount corresponding to each non-uniformly distributed Internet of Things node according to a maximum value and a minimum value of the load data amount corresponding to all non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, to obtain the load data amount corresponding to each non-uniformly distributed Internet of Things node after normalization processing; determining a weight value corresponding to the non-uniformly distributed Internet of Things node according to a predicted number of access users corresponding to each non-uniformly distributed Internet of Things node; determining the load integration value according to the load data amount corresponding to each non-uniformly distributed Internet of Things node after normalization processing and the weight value.

6. The IoT node load balancing method of claim 1, wherein, determining and executing a load balancing strategy according to the priority includes: determining a non-uniformly distributed Internet of Things node with the highest priority in the complex building group Internet of Things as a target node of load scheduling, and selecting a non-uniformly distributed Internet of Things node with the lowest priority as a starting node of load scheduling; when 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 load planned to be transferred from the starting node to the target node; transferring load data with the size of the load scheduling amount in the starting node to the target node through the target scheduling link for processing.

7. An Internet of Things node load balancing apparatus, characterized by, includes: The first calculation module is configured to determine a dynamic load value corresponding to the complex building group Internet of Things, and includes: determining an extension component of a channel formed by non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, wherein the extension component is used to represent spatial variation of channel characteristics caused by non-uniform distribution of nodes; and determining the dynamic load value corresponding to the complex building group Internet of Things according to the extension component, a load peak value and a load interference value of the Internet of Things nodes in the complex building group Internet of Things, wherein the complex building group 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 represent an overall load degree of the Internet of Things nodes in the complex building group Internet of Things. The second calculation module is configured to determine a load integration value according to load data amounts corresponding to all the non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things, wherein the load integration value is used to represent a load degree of the non-uniformly distributed Internet of Things nodes in the complex building group Internet of Things. The priority determination module is configured to determine a priority corresponding to each of the non-uniformly distributed Internet of Things nodes when the load integration value is greater than the dynamic load value, wherein the priority is used to represent a priority degree of the non-uniformly distributed Internet of Things nodes in processing new load data. The load balancing module is configured to determine and execute a load balancing strategy according to the priority, wherein the load balancing strategy is used to schedule load data in the non-uniformly distributed Internet of Things nodes to reduce an overall load degree of the non-uniformly distributed Internet of Things nodes.

8. An electronic device, comprising: The memory and the processor are configured to run a program stored in the memory, and the program is configured to perform the Internet of Things node load balancing method in any one of claims 1 to 6 when running. The non-volatile storage medium includes a stored computer program, and a device in which the non-volatile storage medium is located performs the Internet of Things node load balancing method in any one of claims 1 to 6 by running the computer program.

9. A non-volatile storage medium, comprising: The computer program is executed by the processor to implement the steps of the Internet of Things node load balancing method in any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that, ​

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