Edge internet-of-things proxy communication energy efficiency assessment method, device and medium

Abstract

The invention provides an edge internet-of-things proxy communication energy efficiency evaluation method, equipment and a medium, and relates to the field of communication energy efficiency evaluation. The evaluation method comprises the following steps: establishing a hierarchical structure model based on an overall architecture of a local communication network of the power Internet of Things; obtaining quantitative scores of the basic communication capability, the service guarantee capability, the survival guarantee capability and the resource utilization capability in the second layer based on a third layer index of the hierarchical structure model; constructing a communication energy efficiency evaluation judgment matrix in the first layer of the hierarchical structure model based on the quantitative score; solving a feature vector of the judgment matrix based on a mathematical method to obtain a weight vector of a second-layer index; and performing consistency check on the judgment matrix, and when a preset threshold value is met, obtaining a final communication energy efficiency evaluation result based on the quantization score and the weight vector. The evaluation method provided by the invention can comprehensively and accurately evaluate the communication energy efficiency of the edge Internet of Things agent.

Description

Technical Field

[0001] The present invention relates to the field of communication energy efficiency evaluation, and in particular to an edge IoT proxy communication energy efficiency evaluation method, an electronic device, and a computer-readable storage medium. Background Art

[0002] With the rapid development of Internet of Things technology and the continuous advancement of smart grid construction, edge IoT agents are playing an increasingly important role in power systems. As a key device connecting the perception layer and the network layer, edge IoT agents are responsible for data collection, processing, transmission, and execution of local control tasks. However, in practical applications, edge IoT agents face many challenges, such as complex electromagnetic environments, variable working conditions, and resource constraints. These challenges have a significant impact on the communication energy efficiency of edge IoT agents, so the evaluation of communication energy efficiency is particularly important.

[0003] At present, the existing implementation solutions for the communication energy efficiency evaluation of edge IoT agents mainly include the following: Evaluation method based on a single indicator: This method usually only focuses on one or a few communication indicators, such as transmission rate, energy consumption, etc., while ignoring other factors that may affect communication energy efficiency. Therefore, this method cannot fully reflect the communication energy efficiency performance of edge IoT agents.

[0004] Evaluation method based on statistical methods: This method evaluates the communication efficiency of edge IoT agents by statistically analyzing a large amount of historical data. Although this method can provide a certain reference, it may have certain limitations when facing new environments and working conditions because it relies on historical data.

[0005] Evaluation method based on simulation model: This method builds a simulation model of the edge IoT agent and simulates its communication behavior in different environments to evaluate its communication energy efficiency. However, due to the complexity of the simulation model and the uncertainty of the parameters, the results of this method may have certain errors.

[0006] Therefore, it is urgent to provide a solution to improve the above problems. Summary of the invention

[0007] The purpose of the present invention is to provide an edge IoT agent communication energy efficiency evaluation method, an electronic device and a computer-readable storage medium, which comprehensively considers multiple communication indicators of the edge IoT agent, allocates evaluation indicator weights through scientific methods, reduces evaluation errors, and improves the reliability and accuracy of evaluation results.

[0008] The present invention provides an edge IoT proxy communication energy efficiency evaluation method using the following technical solutions: Establish a hierarchical model based on the overall architecture of the local communication network of the power Internet of Things; Based on the third-layer indicators of the hierarchical structure model, the quantitative scores of the basic communication capability, business assurance capability, survival assurance capability, and resource utilization capability in the second layer are obtained; Constructing a communication energy efficiency evaluation judgment matrix in the first layer of the hierarchical structure model based on the quantitative scores; The weight vector of the second-layer index is obtained by solving the eigenvector of the judgment matrix based on mathematical methods; A consistency check is performed on the judgment matrix, and when it meets a preset threshold, a final communication energy efficiency evaluation result is obtained based on the quantization score and the weight vector.

[0009] Optionally, based on the third-layer indicators of the hierarchical model, quantitative scores of basic communication capability, service assurance capability, survivability assurance capability, and resource utilization capability in the second layer are obtained, including: Based on the hierarchical analysis method, the weights of the third-layer indicators of basic communication capability, business assurance capability, survival assurance capability, and resource utilization capability in the second layer are determined respectively, and the evaluation values ​​of the third-layer indicators are calculated. Based on the evaluation values ​​and weights, the quantitative scores of the basic communication capability, business assurance capability, survival assurance capability, and resource utilization capability in the second layer are obtained.

[0010] Optionally, the third-layer indicators include: When obtaining the quantitative score of the basic communication capability in the second layer of the hierarchical model, the third layer indicators include standard channel capacity evaluation, transmission bit error rate evaluation, communication transmission delay evaluation, and time synchronization accuracy evaluation; When obtaining the quantitative score of the service assurance capability in the second layer of the hierarchical structure model, the third layer indicators include service blocking rate evaluation and channel utilization rate evaluation; When obtaining the quantitative score of the survivability assurance capability in the second layer of the hierarchical model, the third layer indicators include business recovery capability assessment and node connectivity capability assessment; When obtaining the quantitative score of the resource utilization capability in the second layer of the hierarchical structure model, the third layer indicators include link utilization evaluation and node utilization evaluation.

[0011] Optionally, a communication energy efficiency evaluation judgment matrix in the first layer of the hierarchical model is constructed based on the quantitative scores, including: judging the characteristics and importance of four indicators, namely, basic communication capability, business assurance capability, survival assurance capability, and resource utilization capability, based on experts, and comparing the four indicators in pairs based on a specific proportion scale to construct a judgment matrix, wherein the specific proportion scale includes a 1-9 scaling method.

[0012] Optionally, in the process of solving the eigenvector of the judgment matrix based on a mathematical method, the mathematical method includes an eigenvalue method, a power method, and a product method.

[0013] Optionally, the judgment matrix is ​​subjected to a consistency check, including: calculating a consistency index and searching for a corresponding average random consistency index, calculating a consistency ratio based on the consistency index and the average random consistency index, and when the consistency ratio is less than a preset threshold, the judgment matrix is ​​considered to have good consistency and the evaluation result is valid.

[0014] Optionally, a final communication energy efficiency evaluation result is obtained based on the quantified scores and weight vectors, including: multiplying the quantified scores based on basic communication capability, service assurance capability, survival assurance capability, and resource utilization capability by the corresponding weight vectors, and summing them to obtain the communication energy efficiency evaluation result.

[0015] Optionally, the evaluation method includes: performing a consistency check on the judgment matrix, and when it does not meet a preset threshold, reconstructing the communication energy efficiency evaluation judgment matrix.

[0016] In a second aspect of the present invention, an electronic device is provided, comprising a processor, a memory, a user interface and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes any one of the methods described above.

[0017] In a third aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, any of the above methods is executed.

[0018] The invention provides an edge IoT proxy communication energy efficiency evaluation method, an electronic device, and a computer-readable storage medium, which have the following beneficial effects: 1. The present invention constructs a hierarchical model from four levels: basic communication capability, business assurance capability, survival assurance capability, and resource utilization capability, as well as various evaluation indicators under the four levels, which can comprehensively and accurately evaluate the communication energy efficiency of the edge IoT agent.

[0019] 2. The analytic hierarchy process adopted in the present invention scientifically allocates the weight of each indicator to ensure that both the depth and breadth of the evaluation are given equal importance, thereby improving the reliability of the evaluation results.

[0020] 3. The method and device of the present invention can evaluate the communication energy efficiency of the edge IoT agent in real time, and adapt to new environmental and working condition changes, ensuring the real-time and accuracy of the evaluation results. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1A flow chart of an edge IoT proxy communication energy efficiency evaluation method provided by an embodiment of the present invention;

[0022] Figure 2 A hierarchical diagram of the overall architecture of the local communication network of the electric power Internet of Things provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Unless otherwise defined, the technical terms or scientific terms used herein should be understood by people with general skills in the field to which the present invention belongs. "Including" and similar words used in this article mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects.

[0024] The embodiment of the present invention provides a method for evaluating the energy efficiency of edge IoT proxy communication. Figure 1 ,include: S1. Establish a hierarchical model based on the overall architecture of the local communication network of the power Internet of Things; S2. Based on the third-layer indicators of the hierarchical structure model, the quantitative scores of the basic communication capability, business assurance capability, survival assurance capability, and resource utilization capability in the second layer are obtained; S3, constructing a communication energy efficiency evaluation judgment matrix in the first layer of the hierarchical structure model based on the quantitative scores; S4, solving the eigenvector of the judgment matrix based on mathematical methods to obtain the weight vector of the second-level indicators; S5. Perform a consistency check on the judgment matrix, and when it meets a preset threshold, obtain a final communication energy efficiency evaluation result based on the quantization score and the weight vector.

[0025] In some embodiments, during the execution of step S1, the overall architecture of the local communication network of the power Internet of Things is as follows: Figure 2 ,include: Edge IoT agent: A local processing device at the perception layer terminal, with functions including edge computing, communication protocol adaptation, unified data model, and secure access; it realizes the processing and calculation of different types of terminal data at the perception layer, greatly reduces the impact of a large amount of invalid data transmitted from the perception layer to the platform layer on the network layer and platform layer, and improves cloud-fog collaboration and regional autonomy capabilities.

[0026] Local network aggregation unit: deployed on the edge IoT agent side, plays the role of data relay and centralized management; connects the edge IoT agent and the local network aggregation unit through the interface to realize the centralized upload of local access unit data; and performs preliminary processing and analysis on the collected data, and determines the data forwarding path and processing method according to preset rules or algorithms.

[0027] Local network access unit: deployed on the user metering action terminal side, responsible for realizing the access function of the terminal device; connecting the metering action terminal and the local network access unit through the interface, supporting data uploading and command issuing, and ensuring smooth data transmission between the terminal device and the upper communication network.

[0028] Metering action terminal: equipment responsible for functions such as power data collection, transmission, processing and equipment control.

[0029] In fact, there is an interface between the local network access unit and the local network aggregation unit, which is responsible for data exchange and communication coordination between the two, ensuring that the data collected by the local access unit can be accurately transmitted to the aggregation unit, and supporting two-way communication to provide timely feedback and control the execution of instructions; as well as the interface between local network access units, which is used for mutual communication between multiple local network access units. In a distributed deployment scenario, load balancing and data sharing between access units can be achieved, enhancing the robustness and flexibility of the entire local communication network.

[0030] Furthermore, a hierarchical model for edge IoT communication energy efficiency evaluation is constructed through the overall architecture of the local communication network of the power IoT.

[0031] In some embodiments, the process of executing step S2 includes: S2.1. Obtain the quantitative score of basic communication capabilities in the second layer based on the third layer indicators of the hierarchical model; S2.2, based on the third-layer indicators of the hierarchical model, obtain the quantitative score of the service assurance capability in the second layer; S2.3, based on the third level indicators of the hierarchical model, obtain the quantitative score of the survival support capability in the second level; S2.4. Obtain the quantitative score of resource utilization capability in the second layer based on the third layer indicators of the hierarchical model.

[0032] Specifically, when executing step S2.1, it includes: S2.1.1, Standard channel capacity assessment; S2.1.2, transmission bit error rate evaluation; S2.1.3, communication transmission delay evaluation; S2.1.4. Calculate the quantitative score of basic communication ability.

[0033] Specifically, when executing step S2.1.1, standard channel capacity evaluation, the channel capacity is the maximum amount of information that can be transmitted by the channel under a specific bit error rate condition.

[0034] Furthermore, the following formula is used for calculation: ; in, is the channel capacity of a single link, is the useful communication bandwidth, is the receiving signal-to-noise ratio of the edge IoT agent.

[0035] Specifically, when executing step S2.1.2, the transmission bit error rate evaluation, the transmission bit error rate is the ratio of the number of received erroneous code elements to the total number of transmitted code elements.

[0036] Furthermore, the following formula is used for calculation: ; in, is the transmission bit error rate, is the number of error symbols transmitted, is the total number of transmitted symbols.

[0037] Specifically, when executing step S2.1.3, communication transmission delay evaluation, the communication transmission delay is the time required for a node to send data.

[0038] Furthermore, the following formula is used for calculation: ; in, is the transmission delay of a single communication. is the data frame length, is the channel bandwidth.

[0039] Specifically, when executing step S2.1.4 and calculating the quantitative score of basic communication capability, it includes: determining the weights of the standard channel capacity, transmission bit error rate, communication transmission delay, and time synchronization accuracy of the edge IoT agent based on the hierarchical analysis method, and multiplying the calculated standard channel capacity, transmission bit error rate, communication transmission delay, and the obtained time synchronization accuracy by the corresponding weights to obtain the quantitative score of the basic communication capability, and the weights add up to 1.

[0040] Specifically, when executing step S2.2, it includes: S2.2.1, business blocking rate assessment; S2.2.2, channel utilization assessment; S2.2.3. Calculate the quantitative score of business assurance capability.

[0041] Specifically, when executing step S2.2.1, evaluating the service blocking rate, the service blocking rate is the ratio of the rejected service flow to the total service flow, which is used to calibrate the network service quality.

[0042] Furthermore, the following formula is used for calculation: ; in, is the service blocking rate, S is the total number of links, K is the link occupancy count, and λ / μ is the traffic intensity.

[0043] Specifically, when executing step S2.2.2, channel utilization evaluation, the channel utilization is the proportion of the channel effectively utilized during the sending cycle, which is a core indicator of network efficiency in the form of a percentage.

[0044] Furthermore, the following formula is used for calculation: ; in, is the channel utilization, is the effective data transmission amount within the cycle, is the data transmission rate, The sending cycle duration.

[0045] Specifically, when executing step S2.2.3 and calculating the quantitative score of the service assurance capability, it includes: determining the weights of the edge IoT agent service blocking rate and channel utilization based on the hierarchical analysis method, and multiplying the calculated service blocking rate and channel utilization by the corresponding weights to obtain the quantitative score of the service assurance capability. The quantitative score is combined with the inverse operation of the negative indicators service blocking rate and the channel utilization α to adopt a weighted mean.

[0046] Specifically, when executing step S2.3, it includes: S2.3.1, Business recovery capability assessment; S2.3.2, node connectivity capability assessment; S2.3.3. Calculate the quantitative score of survivability support capability.

[0047] Specifically, when executing step S2.3.1, business recovery capability assessment, the business recovery rate is the proportion of business reestablished after the attack, reflecting the network communication resilience.

[0048] Furthermore, the following formula is used for calculation: ; in, is the business recovery rate, To restore the business volume, The total amount of damaged business.

[0049] Specifically, when executing step S2.3.2, node connectivity capability evaluation, the node connectivity is based on the graph theory model G(V,U) to quantify the node interconnection strength, where V is the node set and U is the edge set. The network's anti-destruction and survivability are evaluated, and deviation normalization is used to make D* fall into the [0, 1] interval.

[0050] Furthermore, the following formula is used for calculation: ; in, is the normalized connectivity, is the node connectivity, is the minimum extreme value of the original data, is the maximum extreme value of the original data.

[0051] Specifically, when executing step S2.3.3 and calculating the quantitative score of the survivability assurance capability, it includes: determining the weights of the edge IoT agent business recovery capability and the signal node connectivity based on the hierarchical analysis method, and multiplying the calculated business recovery rate and normalized connectivity by the corresponding weights to obtain the quantitative score of the survivability assurance capability, and the weights add up to 1.

[0052] Specifically, when executing step S2.4, it includes: S2.4.1, link utilization evaluation; S2.4.2, node utilization evaluation; S2.4.3. Quantitative score of computing resource utilization capability.

[0053] Specifically, when executing step S2.4.1, link utilization evaluation, the link utilization is the ratio of the number of links with active data transmission in the edge IoT proxy network to the total number of links within the communication cycle.

[0054] Furthermore, the following formula is used for calculation: ; in, is the link utilization, is the number of active communication links, is the total number of links in the network.

[0055] Specifically, when executing step S2.4.2, node utilization evaluation, the node utilization is the ratio of the number of fusion terminal nodes actually participating in communication in the network to the total number of nodes during the communication cycle.

[0056] Furthermore, the following formula is used for calculation: ; in, is the node utilization, is the number of active communication nodes, is the total number of nodes.

[0057] Specifically, when executing step S2.4.3 and calculating the quantitative score of resource utilization capability, it includes: determining the weights of edge IoT agent link utilization and node utilization based on the hierarchical analysis method, and multiplying the calculated link utilization and node utilization by the corresponding weights to obtain the quantitative score of resource utilization capability, and the weights are accumulated to 1.

[0058] In some embodiments, the process of executing step S3 includes: Based on the characteristics and importance of the four indicators of basic communication capability, business assurance capability, survival assurance capability, and resource utilization capability judged by experts, and based on a specific proportion scale, the four indicators are compared in pairs to construct a judgment matrix, and the specific proportion scale includes a 1-9 scaling method.

[0059] In some embodiments, the process of executing step S4 includes: The eigenvector of the judgment matrix is ​​solved by mathematical methods, and the eigenvector is the weight vector of basic communication capability, business guarantee capability, survival guarantee capability, and resource utilization capability; the mathematical methods include eigenvalue method, power method, and sum-product method.

[0060] In some embodiments, the process of executing step S5 includes: S5.1, perform consistency check on the judgment matrix; S5.2. Obtain a final communication energy efficiency evaluation result based on the quantized score and the weight vector.

[0061] Specifically, when executing step S5.1 and performing consistency check on the judgment matrix, the consistency index is calculated and the corresponding average random consistency index is found, and the consistency ratio is calculated based on the consistency index and the average random consistency index. When the consistency ratio is less than the preset threshold, it is considered that the consistency of the judgment matrix is ​​good and the evaluation result is valid.

[0062] Furthermore, when the preset threshold is not met, the communication energy efficiency evaluation judgment matrix will be reconstructed.

[0063] Specifically, when executing step S5.2, it includes: multiplying the quantified scores based on basic communication capability, business assurance capability, survival assurance capability, and resource utilization capability by the corresponding weight vectors, and summing them to obtain the communication energy efficiency evaluation result.

[0064] An embodiment of the present invention provides an electronic device, including a memory, a processor, and an executable program stored in the memory and capable of being run by the processor; when the processor runs the executable program, the edge IoT proxy communication energy efficiency evaluation method as described above is executed.

[0065] An embodiment of the present invention provides a computer-readable storage medium, which stores an executable program; when the executable program is executed, the above-mentioned edge IoT proxy communication energy efficiency evaluation method is implemented.

[0066] Although the embodiments of the present invention are described in detail above, it is obvious to those skilled in the art that various modifications and variations can be made to these embodiments. However, it should be understood that such modifications and variations are within the scope and spirit of the present invention as described in the claims. Moreover, the present invention described herein may have other embodiments and may be implemented or realized in a variety of ways.

Claims

1. A method for evaluating energy efficiency of edge IoT proxy communication, characterized in that: The following steps are involved: Establish a hierarchical model based on the overall architecture of the local communication network of the power Internet of Things; Based on the third-layer indicators of the hierarchical structure model, the quantitative scores of the basic communication capability, business assurance capability, survival assurance capability, and resource utilization capability in the second layer are obtained; Constructing a communication energy efficiency evaluation judgment matrix in the first layer of the hierarchical structure model based on the quantitative scores; The weight vector of the second-layer index is obtained by solving the eigenvector of the judgment matrix based on mathematical methods; A consistency check is performed on the judgment matrix, and when it meets a preset threshold, a final communication energy efficiency evaluation result is obtained based on the quantization score and the weight vector.

2. According to claim 1, a method for evaluating energy efficiency of edge IoT proxy communication is characterized in that: Based on the third-layer indicators of the hierarchical model, the quantitative scores of the basic communication capability, business assurance capability, survival assurance capability, and resource utilization capability in the second layer are obtained, including: Based on the hierarchical analysis method, the weights of the third-layer indicators of basic communication capability, business assurance capability, survival assurance capability, and resource utilization capability in the second layer are determined respectively, and the evaluation values ​​of the third-layer indicators are calculated. Based on the evaluation values ​​and weights, the quantitative scores of the basic communication capability, business assurance capability, survival assurance capability, and resource utilization capability in the second layer are obtained.

3. According to claim 2, a method for evaluating energy efficiency of edge IoT proxy communication is characterized in that: The third-tier indicators include: When obtaining the quantitative score of the basic communication capability in the second layer of the hierarchical model, the third layer indicators include standard channel capacity evaluation, transmission bit error rate evaluation, communication transmission delay evaluation, and time synchronization accuracy evaluation; When obtaining the quantitative score of the service assurance capability in the second layer of the hierarchical structure model, the third layer indicators include service blocking rate evaluation and channel utilization rate evaluation; When obtaining the quantitative score of the survivability assurance capability in the second layer of the hierarchical model, the third layer indicators include business recovery capability assessment and node connectivity capability assessment; When obtaining the quantitative score of the resource utilization capability in the second layer of the hierarchical structure model, the third layer indicators include link utilization evaluation and node utilization evaluation.

4. The method for evaluating energy efficiency of edge IoT proxy communication according to claim 1, characterized in that: A communication energy efficiency evaluation judgment matrix in the first layer of the hierarchical structure model is constructed based on the quantitative scores, including: Based on the characteristics and importance of the four indicators of basic communication capability, business assurance capability, survival assurance capability, and resource utilization capability judged by experts, and based on a specific proportion scale, the four indicators are compared in pairs to construct a judgment matrix, and the specific proportion scale includes a 1-9 scaling method.

5. The method for evaluating energy efficiency of edge IoT proxy communication according to claim 1, characterized in that: In the process of solving the eigenvector of the judgment matrix based on a mathematical method, the mathematical method includes an eigenvalue method, a power method, and a product method.

6. The method for evaluating energy efficiency of edge IoT proxy communication according to claim 1, characterized in that: Performing a consistency check on the judgment matrix includes: Calculate the consistency index and find the corresponding average random consistency index. Calculate the consistency ratio based on the consistency index and the average random consistency index. When the consistency ratio is less than the preset threshold, it is considered that the consistency of the judgment matrix is ​​good and the evaluation result is valid.

7. The method for evaluating energy efficiency of edge IoT proxy communication according to claim 1, characterized in that: The final communication energy efficiency evaluation result is obtained based on the quantized score and the weight vector, including: The quantitative scores of basic communication capability, business assurance capability, survival assurance capability, and resource utilization capability are multiplied by the corresponding weight vectors and summed to obtain the communication energy efficiency evaluation results.

8. The method for evaluating energy efficiency of edge IoT proxy communication according to claim 1, characterized in that: include: The judgment matrix is ​​subjected to consistency check, and when it does not meet the preset threshold, the communication energy efficiency evaluation judgment matrix is ​​reconstructed.

9. An electronic device, characterized in that: It includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are both used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 8 is performed.

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