Link access mode switching method and system for sensing equipment of electric power internet of things

Abstract

The invention relates to the technical field of power internet of things, in particular to a method and a system for switching link access modes of sensing equipment of the power internet of things. The method comprises the following steps: calculating a score of each heterogeneous link based on a weight corresponding to each evaluation index and an evaluation index value of each heterogeneous link in a network layer of the electric power Internet of Things; the average value of the scores of all the heterogeneous links in the network layer of the electric power Internet of Things serves as a multi-link binding mode score; taking the maximum value in the scores of all the heterogeneous links in the network layer of the electric power internet of things as a multi-path switching mode score; taking the difference between the maximum value and the minimum value of the scores of all the heterogeneous links in the network layer of the electric power Internet of Things as a multi-path backup mode score; and taking the mode with the highest score as a target heterogeneous link access mode. According to the invention, the problem that channel congestion often occurs under the condition of high concurrency of the existing power internet of things is solved, and high-efficiency transmission of signals of the power internet of things is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power internet of things, and particularly relates to a power internet of things sensing device link access mode switching method and system. BACKGROUND

[0002] With the accelerated development of new power systems and energy internet, power internet of things is a core supporting technology for realizing energy resource interconnection, information collaboration, intelligent scheduling and efficient management and control. The power internet of things includes a sensing layer, a network layer, a platform layer and an application layer. A large number of sensors, intelligent meters and other devices are widely deployed in substation, distribution network, transmission line and user side and other core scenes. Using the sensing layer, the running data of power equipment is collected in real time, and then the data collected by the sensing layer is quickly and stably transmitted to the cloud or control center through the heterogeneous links such as 5G, optical fiber and wireless communication in the network layer. The platform layer uses cloud computing and big data analysis technology to store, process and mine massive data, and forms device state evaluation, fault warning and other information. The application layer develops various applications such as intelligent scheduling, fault diagnosis, energy management and user side energy efficiency optimization based on the analysis results of the platform layer.

[0003] At present, the selection of access mode of each heterogeneous link in the network layer of the power internet of things mainly relies on experience judgment and preset rules. For example, in a closed scene with extremely high reliability requirements, such as a substation automation system, technicians consider the large amount of real-time monitoring data and the requirement that transmission cannot be interrupted, and prefer to select a multi-link binding mode, which aggregates multiple heterogeneous links into a logical link to improve transmission bandwidth and enhance stability. For wide-area scenarios of distribution network and user side, according to preset rules such as device deployment characteristics and environmental interference degree, end dispersed devices often adopt a multi-path switching mode. The system automatically switches between different links according to real-time link state to ensure data transmission. In some key power business links, such as power grid dispatching data transmission, a multi-path backup mode is used according to the established engineering specification to provide redundant protection for data transmission.

[0004] However, this selection method mainly based on experience judgment and preset rules relies on the subjective cognition of technicians, lacks quantitative standards, and leads to large differences in access mode selection for different projects and low reusability. Once the link access mode is selected improperly, it will lead to unreasonable resource allocation and improper data transmission strategy, seriously affecting the data transmission efficiency of the power internet of things, and eventually leading to channel congestion and hindering the stable operation of the power system. In addition, the running state of the power network changes all the time, and factors such as peak and valley of power consumption and sudden environmental disturbances will affect the transmission quality of the link. The selection method relying only on experience and preset rules is difficult to adapt to the complex and variable actual operation scenarios of the power internet of things, further exacerbating the problems of low data transmission efficiency and waste of network resources in the power internet of things. SUMMARY

[0005] To this end, the technical problem to be solved by the present application is to overcome the defects that the existing power internet of things sensing device link access mode switching method relies on the subjective cognition of technical personnel, cannot be adjusted in time according to actual data, is difficult to adapt to the complex and changeable actual operation scene of the power internet of things, leads to insufficient selection precision of the link access mode, and easily causes high concurrent channel congestion.

[0006] To solve the above technical problems, the present application provides a power internet of things sensing device link access mode switching method, comprising the following steps:

[0007] obtaining heterogeneous link evaluation indexes and corresponding weights of each evaluation index; based on the corresponding weights of each evaluation index and the evaluation index values of each heterogeneous link in the last period of the power internet of things network layer, calculating the scores of each heterogeneous link in the last period of the power internet of things network layer;

[0008] taking the average value of the scores of all heterogeneous links in the last period of the power internet of things network layer as the multi-link bundling mode score of the last period of the power internet of things network layer;

[0009] taking the maximum value of the scores of all heterogeneous links in the last period of the power internet of things network layer as the multi-path switching mode score of the last period of the power internet of things network layer;

[0010] taking the difference between the maximum value and the minimum value of the scores of all heterogeneous links in the last period of the power internet of things network layer as the multi-path backup mode score of the last period of the power internet of things network layer;

[0011] taking the mode with the highest score as the target heterogeneous link access mode of the current period of the power internet of things network layer.

[0012] Preferably, the heterogeneous link evaluation indexes include bandwidth, delay, jitter, packet loss rate and throughput.

[0013] Preferably, based on the corresponding weights of each evaluation index and the evaluation index values of each heterogeneous link in each period of the power internet of things network layer, the scores of each heterogeneous link in each period of the power internet of things network layer are calculated, and the formula is:

[0014]

[0015] wherein Q i (t) is the score of the ith heterogeneous link in the t period, BW i (t) is the bandwidth of the ith heterogeneous link in the t period, BW max is the maximum bandwidth in all heterogeneous links, D i (t) is the delay of the ith heterogeneous link in the t period, Dreq Jmax is the maximum allowed latency, i (t) is the jitter of the ith heterogeneous link at time period t, PL i (t) is the packet loss rate of the ith heterogeneous link at time period t, S i (t) is the throughput of the ith heterogeneous link at time period t, I1 is the weight corresponding to the bandwidth, I2 is the weight corresponding to the latency, I3 is the weight corresponding to the jitter, I4 is the weight corresponding to the packet loss rate, and I5 is the weight corresponding to the throughput.

[0016] Preferably, the weight corresponding to each evaluation index of the heterogeneous link is obtained, including:

[0017] The subjective weight and the objective weight corresponding to each evaluation index of the heterogeneous link are obtained.

[0018] The subjective weight and the objective weight corresponding to each evaluation index of the heterogeneous link are fused to obtain a comprehensive weight corresponding to each evaluation index of the heterogeneous link as the weight corresponding to each evaluation index of the heterogeneous link.

[0019] Preferably, the method for obtaining the subjective weight corresponding to each evaluation index of the heterogeneous link is any one of interval analytic hierarchy process, analytic hierarchy process, ring ratio scoring method, least square method, and optimal order diagram method.

[0020] Preferably, the method for obtaining the subjective weight corresponding to each evaluation index of the heterogeneous link by the interval analytic hierarchy process includes:

[0021] The target layer is set as the target heterogeneous link access mode selection, the index layer is set as each evaluation index of the heterogeneous link, and the scheme layer is set as the multi-link bundling mode, the multi-path switching mode, and the multi-path backup mode, so as to construct a hierarchical evaluation model;

[0022] The importance of each evaluation index in the index layer of the hierarchical evaluation model is sequentially sorted from high to low to obtain each sorted evaluation index;

[0023] Based on each sorted evaluation index, a consistency judgment matrix is constructed by the scale construction method; wherein each element s a,b in the consistency judgment matrix represents the importance ratio of the a th evaluation index to the b th evaluation index with respect to the target layer, a is the first evaluation index index, and b is the second evaluation index index;

[0024] Based on the consistency judgment matrix, the subjective weight corresponding to each evaluation index of the heterogeneous link is calculated.

[0025] Preferably, the method for obtaining the objective weight corresponding to each evaluation index of the heterogeneous link is any one of principal component method, entropy method, and CRITIC weight method.

[0026] Preferably, the method for obtaining the objective weight corresponding to each evaluation index of the heterogeneous link by the CRITIC weight method comprises the following steps:

[0027] Obtaining the evaluation index values of the heterogeneous link under different link access modes, and sequentially performing dimensionless processing and normalization processing on the evaluation index values to construct a dimensionless network attribute matrix.

[0028] Based on the dimensionless network attribute matrix, the objective weight corresponding to each evaluation index of the heterogeneous link is calculated.

[0029] Preferably, the subjective weight and the objective weight corresponding to each evaluation index of the heterogeneous link are fused to obtain the comprehensive weight corresponding to each evaluation index of the heterogeneous link, and the fusion method is any one of the minimum information discrimination principle, the linear weighted fusion method and the least square method fusion.

[0030] The application further provides a power internet of things sensing device link access mode switching system, which comprises:

[0031] A heterogeneous link score obtaining module is configured to obtain the evaluation indexes of the heterogeneous link and the weight corresponding to each evaluation index, and calculate the score of each heterogeneous link in the power internet of things network layer in the last period based on the weight corresponding to each evaluation index and the evaluation index value of each heterogeneous link in the power internet of things network layer in the last period.

[0032] A bundling mode score module is configured to take the average value of the scores of all the heterogeneous links in the power internet of things network layer in the last period as the multi-link bundling mode score of the power internet of things network layer in the last period.

[0033] A switching mode score module is configured to take the maximum value of the scores of all the heterogeneous links in the power internet of things network layer in the last period as the multi-path switching mode score of the power internet of things network layer in the last period.

[0034] A backup mode score module is configured to take the difference between the maximum value and the minimum value of the scores of all the heterogeneous links in the power internet of things network layer in the last period as the multi-path backup mode score of the power internet of things network layer in the last period.

[0035] A selection module is configured to take the mode with the highest score as the target heterogeneous link access mode of the power internet of things network layer in the current period.

[0036] The above technical scheme of the application has the following beneficial effects compared with the prior art:

[0037] The power internet of things sensing device link access mode switching method and system provided by the application, according to different access mode communication, designs different access mode score calculation method, takes the average value of scores of all heterogeneous links in the power internet of things network layer as the multi-link bundling mode score, fits the characteristics of multi-link simultaneous transmission and redundancy processing, and can comprehensively reflect the overall performance level of the heterogeneous link. The maximum value is used as the multi-path switching mode score, which accurately matches the characteristics of single-link operation and switching transmission. The difference between the maximum value and the minimum value is used as the multi-path backup mode score, which conforms to the mechanism of master and backup link configuration and fault switching, and the greater the difference means that the link performance difference is significant. Moreover, the application determines the target access mode of the current period according to the real-time link score of the last period, effectively improves the link access mode selection accuracy, can quickly respond to real-time conditions such as power load fluctuation and environmental interference change in the power network, and improves the stability and reliability of power internet of things data transmission. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to make the content of the application more easily understood, the application will be further described in detail below according to specific embodiments of the application and in conjunction with the drawings, in which:

[0039] Figure 1 is a flowchart of a power internet of things sensing device link access mode switching method of the application.

[0040] Figure 2 is a structure diagram of a hierarchical evaluation model.

[0041] Figure 3 is a structure diagram of a power internet of things sensing device link access mode switching system of the application. DETAILED DESCRIPTION

[0042] The application will be further described below in conjunction with the drawings and specific embodiments, so that those skilled in the art can better understand the application and implement it, but the embodiments are not limiting the application.

[0043] Referring to Figure 1 The embodiment one provides a power internet of things sensing device link access mode switching method, which comprises the following steps:

[0044] Step S1: Obtain heterogeneous link evaluation indexes and corresponding weights of each evaluation index; based on the corresponding weights of each evaluation index and the evaluation index values of each heterogeneous link in the power internet of things network layer of the last period, calculate the score of each heterogeneous link in the power internet of things network layer of the last period;

[0045] In this embodiment, specifically, the evaluation indexes of the heterogeneous links include bandwidth, delay, jitter, packet loss rate and throughput. In this embodiment, preferably, based on the weight corresponding to each evaluation index and the evaluation index value of each heterogeneous link in the power internet of things network layer in each period, the score of each heterogeneous link in the power internet of things network layer in each period is calculated, and the formula is:

[0046]

[0047] wherein Q i (t) is the score of the ith heterogeneous link in the t period, BW i (t) is the bandwidth of the ith heterogeneous link in the t period, BW max is the maximum bandwidth in all heterogeneous links, D i (t) is the delay of the ith heterogeneous link in the t period, D req is the maximum allowed delay of the business to which the power internet of things belongs, J i (t) is the jitter of the ith heterogeneous link in the t period, PL i (t) is the packet loss rate of the ith heterogeneous link in the t period, S i (t) is the throughput of the ith heterogeneous link in the t period, I1 is the weight corresponding to the bandwidth, I2 is the weight corresponding to the delay, I3 is the weight corresponding to the jitter, I4 is the weight corresponding to the packet loss rate, and I5 is the weight corresponding to the throughput.

[0048] In this embodiment, when the business to which the power internet of things belongs is a collection type business, the weight corresponding to each evaluation index is shown in Table 1, and Table 1 is an evaluation index weight diagram for a collection type business.

[0049] Table 1

[0050]

[0051] The score formula quantitatively integrates multiple dimensions of key indicators. The bandwidth index introduces normalization processing to measure the link transmission capacity by the ratio of the actual bandwidth to the maximum bandwidth, ensuring that the score can be compared horizontally between different links and providing data support for bandwidth aggregation decisions in the multi-link bundling mode. The delay, jitter and packet loss rate are in the form of inverse, which converts factors that have a negative impact on transmission quality into positive scores, so that the link performance and the score are positively correlated, which conforms to the intuitive evaluation logic and effectively avoids improper data transmission strategies caused by fluctuations in link performance. The throughput index is directly included in the score, which strengthens the consideration of the long-term reliable operation capacity of the link.

[0052] In this embodiment, optionally, the weight corresponding to each evaluation index of the heterogeneous link is a subjective weight or an objective weight.

[0053] In this embodiment, preferably, the weight corresponding to each evaluation index of the heterogeneous link is obtained by:

[0054] Step S11: obtaining the subjective weight and the objective weight corresponding to each evaluation index of the heterogeneous link;

[0055] In this embodiment, specifically, the method for obtaining the subjective weight corresponding to each evaluation index of the heterogeneous link is any one of interval analytic hierarchy process, analytic hierarchy process, ring ratio scoring method, least square method, and optimal sequence diagram method.

[0056] In this embodiment, preferably, the method for obtaining the subjective weight corresponding to each evaluation index of the heterogeneous link by the interval analytic hierarchy process comprises:

[0057] As shown in Figure 2 , a structural diagram of the hierarchical evaluation model is shown in Figure 2 .

[0058] Step S111: setting the target layer as the target heterogeneous link access mode selection, setting the measurement layer as the heterogeneous link quality and the heterogeneous link stability, setting the index layer as each evaluation index of the heterogeneous link, and setting the scheme layer as the multi-link bundling mode, the multi-path switching mode, and the multi-path backup mode, to construct a hierarchical evaluation model;

[0059] Step S112: sequentially sorting the importance of each evaluation index in the index layer of the hierarchical evaluation model from high to low to obtain each sorted evaluation index;

[0060] Step S113: based on each sorted evaluation index, constructing a consistency judgment matrix S=(s a,b ) n×n by the scale construction method (1-9 scale method); wherein each element s a,b in the consistency judgment matrix represents the importance ratio of the a-th evaluation index to the b-th evaluation index relative to the target layer, a is the first evaluation index index, b is the second evaluation index index, and n is the total number of evaluation indexes in the index layer of the hierarchical evaluation model;

[0061] The consistency judgment matrix S satisfies the following conditions:

[0062] s a,b >0、s a,a =1、s a,b =1 / s b,a 、s a,b >s a,k s k,b , k represents any evaluation index index, and the value range of k is [1, n].

[0063] According to the transitivity of the importance of the indexes, s a,b is:

[0064]

[0065] wherein, t k is the importance degree ratio of the kth evaluation index and the k+1th evaluation index relative to the target layer

[0066] Step S114: based on the consistency judgment matrix, the subjective weight corresponding to each evaluation index of the heterogeneous link is calculated The formula is:

[0067]

[0068] wherein, is the subjective weight of the ath evaluation index.

[0069] The interval analytic hierarchy process replaces the traditional single value with an interval value, which can effectively contain the uncertainty and fuzziness of expert subjective judgment, and the interval value can more truly reflect the judgment range, avoid information loss, and improve the credibility of the weight. At the same time, compared with the traditional analytic hierarchy process, the calculation process can output the weight interval, providing a risk boundary reference for decision-making. For example, in the complex and variable power internet of things scene, the sensitivity of a certain index to the link access mode selection result can be intuitively judged through the weight interval, enhancing the robustness of the decision. In addition, this method is more flexible when dealing with the opinions of multiple experts, and can integrate the differences in the judgments of different experts into a unified interval result, reducing the influence of individual cognitive bias, and thus improving the scientificity of the link access mode selection.

[0070] The method for obtaining the objective weight corresponding to each evaluation index of the heterogeneous link is any one of the principal component method, the entropy method, and the CRITIC weight method.

[0071] In this embodiment, preferably, the method for obtaining the objective weight corresponding to each evaluation index of the heterogeneous link by the CRITIC weight method comprises:

[0072] Step S115: obtain the evaluation index values of the heterogeneous link under different link access modes, and construct a network attribute matrix X=(x a,β ) n×m , and sequentially perform dimensionless processing and normalization processing on the evaluation index values, to standardize the index data to the range of [0, 1], to obtain a dimensionless network attribute matrix G=(g a,β ) n×m ; wherein, m is the number of link access modes, m=3 in this application, which are respectively the multi-link bundling mode, the multi-path switching mode, and the multi-path backup mode score;

[0073] In the process of using CRITIC weight method to solve the objective weight, due to the dimensional difference of original index data (such as bandwidth unit is Mbps, time delay unit is ms) and the different numerical magnitude, direct calculation will lead to the result deviation. Therefore, the index data needs to be dimensionless processed to eliminate the influence of unit and magnitude, so that each index has comparability. According to the characteristics of different types of indexes, the processing strategy is as follows:

[0074] Benefit type index (the greater the better): such as bandwidth, the greater the value of this kind of index, the better the link performance. When dimensionless, the positive conversion strategy is adopted to ensure that the greater the original value, the higher the standardized value after conversion, so as to retain and highlight the index advantage;

[0075] Cost type index (the smaller the better): such as time delay, the smaller the value, the higher the link quality. When processing, the inverse conversion method is adopted, so that the original value and the standardized value are negatively correlated, that is, the smaller the value, the greater the result after conversion, so as to highlight the high quality performance of this kind of index;

[0076] Intermediate type index (the closer to a certain value, the better): typical such as ideal transmission power, there is a specific optimal value, when dimensionless, take the ideal value as the benchmark, calculate the deviation of the original data from the benchmark value, the closer the distance, the greater the standardized value, which accurately reflects the degree of conformity between the index and the ideal state.

[0077] The expression g a,β of each element in the dimensionless network attribute matrix G is:

[0078]

[0079] Wherein, x a,β is the original value of the a-th evaluation index under the β-th link access mode, g a,β is the element of the a-th row and the β-th column in the dimensionless network attribute matrix G, max|X a | is the maximum value of the absolute value of the original value of the a-th evaluation index under all link access modes;

[0080] Step S115: based on the dimensionless network attribute matrix, calculate the objective weight corresponding to each evaluation index of the heterogeneous link, including:

[0081] Based on the dimensionless network attribute matrix, calculate the information amount ψ a contained in each evaluation index, the calculation formula is:

[0082]

[0083] Wherein, ψ a is the information amount contained in the a-th evaluation index, is the average value of the elements in the a-th row of the dimensionless network attribute matrix G, cov(G a ,G b ) is the covariance of the element G a in the a-th row and the element G b in the b-th row of the dimensionless network attribute matrix G, cov(G a ) is the standard deviation of the elements in the a-th row of the dimensionless network attribute matrix G, cov(G b ) is the standard deviation of the elements in the b-th row of the dimensionless network attribute matrix G.

[0084] The larger the information amount ψ a contained in the evaluation index is, the greater the weight of the evaluation index is, and the formula for calculating the objective weight of the index is:

[0085]

[0086] wherein, w is the objective weight of the a-th evaluation index.

[0087] The objective weight of each evaluation index is solved by using the CRITIC weight method. The method eliminates the calculation deviation caused by the dimensional and order-of-magnitude differences of the original index data through dimensionless and normalization processing, and ensures the comparability of different types of indexes (such as bandwidth, delay, etc.). On this basis, the information amount is calculated based on the standard deviation of the index and the correlation between the indexes, which not only considers the fluctuation degree (discreteness) of a single index under different link access modes, but also improves the independence and discrimination of the weight by eliminating the overlapping information (correlation) between the indexes, so as to accurately reflect the actual importance of each evaluation index in the power internet of things link performance evaluation, and provide an objective and reliable quantitative basis for the scientific selection of heterogeneous link access modes.

[0088] Step S12: fusing the subjective weight and the objective weight corresponding to each evaluation index of the heterogeneous link to obtain the comprehensive weight corresponding to each evaluation index of the heterogeneous link as the weight corresponding to each evaluation index of the heterogeneous link.

[0089] In this embodiment, specifically, the subjective weight and the objective weight corresponding to each evaluation index of the heterogeneous link are fused to obtain the comprehensive weight corresponding to each evaluation index of the heterogeneous link, and the fusion method is any one of the minimum information discrimination principle, the linear weighting fusion method, and the least squares fusion method.

[0090] In this embodiment, in order to make the comprehensive weight corresponding to each evaluation index of the heterogeneous link as close as possible to the subjective weight and the objective weight, the comprehensive weight corresponding to each evaluation index of the heterogeneous link is solved by using the minimum information discrimination principle, and the comprehensive weight corresponding to each evaluation index of the heterogeneous link is taken as the weight of each evaluation index of the heterogeneous link. The formula of the minimum information discrimination principle is:​

[0091]

[0092] By solving the above problem, the index comprehensive weight vector is ω=[ω1,ω2,…,ω n ]。

[0093] Wherein, minF(ω) indicates that the target is to minimize the function F(ω), which is used to measure the deviation of the comprehensive weight from the subjective and objective weights, ω a is the comprehensive weight of the a-th evaluation index.

[0094] Step S2: The average value of the scores of all heterogeneous links in the last period power internet of things network layer is taken as the multi-link bundling mode score of the last period power internet of things network layer.

[0095] The multi-path bundling mode refers to that three or more links are online at the same time, and all data are transmitted at the same time, but only the data on one link is processed, and the data on the other two links is not processed. Only when it is detected that the data transmitted by the current link is incomplete, the data on the other two links is processed, and then the data of the three links is fused to cover the overlapping part and make up the missing part, so as to maximize the integrity of the data. The multi-link is online at the same time, and the same data is transmitted at the same time, so that the integrity of the data can be maximized. When one link is abnormal, the system will not appear any abnormality, and there is no switching, time delay, network jitter and the like, so that the implementation is simple, and the overall reliability of the system and the smoothness of the data are the highest.

[0096] In the embodiment, preferably, the multi-link bundling mode score of the power internet of things network layer in each period is:

[0097]

[0098] Wherein, Q bundle (t) is the multi-link bundling mode score of the power internet of things network layer in the t period, N is the total number of heterogeneous links in the power internet of things network layer, and Q i (t) is the score of the i-th heterogeneous link in the t period.

[0099] Step S3: The maximum value in the scores of all heterogeneous links in the last period power internet of things network layer is taken as the multi-path switching mode score of the last period power internet of things network layer. The multi-path switching mode has simple implementation and saves cost, and only one link consumes traffic at the same time.

[0100] The formula of the multi-path switching mode score of the power internet of things network layer in each period is:

[0101] Q switch (t)=max(Q i(t)),

[0102] Among them, Q switch (t) represents the multi-path switching mode score of the power IoT network layer during time period t, Q i (t) represents the score of the i-th heterogeneous link in time period t, and max(·) represents the maximum value.

[0103] Step S4: Take the difference between the maximum and minimum scores of all heterogeneous links in the power IoT network layer of the previous time period as the multi-path backup mode score of the power IoT network layer of the previous time period.

[0104] Multi-path backup mode refers to three or more links being online simultaneously, but the system only selects the optimal link for data transmission at any given time, while another link remains idle. When the system detects an anomaly in the status of the working link, such as increased latency, severe network jitter, or a circuit break, it immediately switches data transmission to the backup link.

[0105] The formula for scoring the multi-path backup mode of the power Internet of Things network layer for each time period is:

[0106] Q backup (t)=max(Q i (t))-min(Q i (t)),

[0107] Among them, Q backup (t) represents the multi-path backup mode score of the power IoT network layer during time period t, Q i (t) represents the score of the i-th heterogeneous link in time period t, maX(·) represents the maximum value, and min(·) represents the minimum value.

[0108] Step S5: Select the highest-scoring mode as the target heterogeneous link access mode for the current time period in the power Internet of Things network layer.

[0109] Reference Figure 3 As shown in the figure, this embodiment 2 provides a power Internet of Things (IoT) sensing device link access mode switching system, including:

[0110] The heterogeneous link scoring acquisition module 10 is used to acquire the heterogeneous link evaluation indicators and the corresponding weight of each evaluation indicator; based on the corresponding weight of each evaluation indicator and the evaluation indicator value of each heterogeneous link in the power Internet of Things network layer in the previous time period, the score of each heterogeneous link in the power Internet of Things network layer in the previous time period is calculated.

[0111] The bundling mode scoring module 20 is used to take the average score of all heterogeneous links in the power IoT network layer of the previous time period as the multi-link bundling mode score of the power IoT network layer of the previous time period.

[0112] The switching mode scoring module 30 takes the maximum value of the scores of all the heterogeneous links in the last period power internet of things network layer as the multi-path switching mode score of the last period power internet of things network layer.

[0113] The backup mode scoring module 40 takes the difference between the maximum value and the minimum value of the scores of all the heterogeneous links in the last period power internet of things network layer as the multi-path backup mode score of the last period power internet of things network layer.

[0114] The selection module 50 is configured to take the mode with the highest score as the target heterogeneous link access mode of the current period power internet of things network layer.

[0115] Those skilled in the art will understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage, etc.) containing computer usable program code.

[0116] The present application is described with reference to flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and combinations of flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus generate a means for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in a flow or multiple flows and / or blocks Figure 1 The functions specified in a flow or multiple flows and / or blocks

[0117] These computer program instructions can also be stored in a computer-readable memory that can direct the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including instruction means, which implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The functions specified in a flow or multiple flows and / or blocks Figure 1 The functions specified in a flow or multiple flows and / or blocks

[0118] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable data processing apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable data processing apparatus provide a means for implementing the functions specified in the flowcharts and / or block diagrams.Figure 1 one or more processes and / or functions described in one or more blocks Figure 1 one or more processes and / or functions described in one or more blocks

[0119] Obviously, the above-mentioned embodiments are only examples for clearly illustrating the present application, and are not intended to limit the present application. Based on the above-mentioned embodiments, other different forms of changes or variations can be made by those skilled in the art. Here, it is not necessary or possible to enumerate all the embodiments. The obvious changes or variations derived from the above-mentioned embodiments are still within the protection scope of the present application.

Claims

1. A method for switching the link access mode of a power Internet of Things (IoT) sensing device, characterized in that, include: Obtain the evaluation metrics for heterogeneous links and the corresponding weights for each evaluation metric; Based on the weight of each evaluation indicator and the evaluation indicator value of each heterogeneous link in the power Internet of Things network layer in the previous time period, the score of each heterogeneous link in the power Internet of Things network layer in the previous time period is calculated. The average score of all heterogeneous links in the power IoT network layer of the previous time period is used as the multi-link bonding mode score of the power IoT network layer of the previous time period. The maximum score among all heterogeneous links in the power IoT network layer of the previous time period is taken as the multi-way switching mode score of the power IoT network layer of the previous time period. The difference between the maximum and minimum scores of all heterogeneous links in the power IoT network layer of the previous time period is used as the multi-path backup mode score of the power IoT network layer of the previous time period. The mode with the highest score will be used as the target heterogeneous link access mode for the power Internet of Things network layer in the current period.

2. The method for switching the link access mode of a power Internet of Things sensing device according to claim 1, characterized in that, Evaluation metrics for heterogeneous links include: bandwidth, latency, jitter, packet loss rate, and throughput.

3. The method for switching the link access mode of a power Internet of Things sensing device according to claim 1, characterized in that, Based on the weight corresponding to each evaluation indicator and the evaluation indicator value of each heterogeneous link in the power IoT network layer for each time period, the score of each heterogeneous link in the power IoT network layer for each time period is calculated using the following formula: Among them, Q i (t) represents the score of the i-th heterogeneous link in time period t, BW i (t) represents the bandwidth of the i-th heterogeneous link in time period t, BW max D represents the maximum bandwidth among all heterogeneous links. i (t) represents the latency of the i-th heterogeneous link in time period t, and D rea For the maximum allowable delay, J i (t) represents the jitter of the i-th heterogeneous link in time period t, PL i (t) represents the packet loss rate of the i-th heterogeneous link in time period t, S i (t) represents the throughput of the i-th heterogeneous link in time period t, where I1 is the weight corresponding to bandwidth, I2 is the weight corresponding to latency, I3 is the weight corresponding to jitter, I4 is the weight corresponding to packet loss rate, and I5 is the weight corresponding to throughput.

4. The method for switching the link access mode of a power Internet of Things sensing device according to claim 1, characterized in that, Obtain the weights corresponding to each evaluation metric of the heterogeneous link, including: Obtain the subjective and objective weights corresponding to each evaluation metric of the heterogeneous link; The subjective and objective weights corresponding to each evaluation indicator of the heterogeneous link are integrated to obtain the comprehensive weight corresponding to each evaluation indicator of the heterogeneous link, which is used as the weight corresponding to each evaluation indicator of the heterogeneous link.

5. The method for switching the link access mode of a power Internet of Things sensing device according to claim 4, characterized in that, The method for obtaining the subjective weights corresponding to each evaluation index of heterogeneous links can be any one of the following: interval analytic hierarchy process, analytic hierarchy process, chain ratio scoring method, least squares method, and pecking order graph method.

6. The method for switching the link access mode of a power Internet of Things sensing device according to claim 5, characterized in that, Methods for obtaining the subjective weights corresponding to each evaluation index of heterogeneous links using interval hierarchical analysis include: The target layer is set to the target heterogeneous link access mode selection, the indicator layer is set to the various evaluation indicators of heterogeneous links, and the solution layer is set to multi-link bundling mode, multi-path switching mode, and multi-path backup mode to construct a hierarchical evaluation model. The importance of each evaluation indicator in the hierarchical evaluation model indicator layer is sorted from high to low to obtain the sorted evaluation indicators. Based on the ranked evaluation indicators, a consistency decision matrix is ​​constructed using the scaling method; where each element s in the consistency decision matrix... a，b This represents the ratio of the importance of the a-th evaluation indicator to the b-th evaluation indicator relative to the target layer among the sorted evaluation indicators, where a is the index of the first evaluation indicator and b is the index of the second evaluation indicator. Based on the consistency decision matrix, the subjective weight corresponding to each evaluation index of the heterogeneous link is calculated.

7. The method for switching the link access mode of a power Internet of Things sensing device according to claim 4, characterized in that, The method for obtaining the objective weights corresponding to each evaluation index of heterogeneous links is any one of the principal component method, entropy method, or CRITIC weight method.

8. The method for switching the link access mode of a power Internet of Things sensing device according to claim 7, characterized in that, The CRITIC weighting method is used to obtain the objective weights corresponding to each evaluation metric of heterogeneous links, including: The evaluation index values ​​of heterogeneous links under different link access modes are obtained, and the evaluation index values ​​are successively processed into dimensionless and normalized to construct a dimensionless network attribute matrix. Based on the dimensionless network attribute matrix, the objective weight corresponding to each evaluation index of heterogeneous links is calculated.

9. The method for switching the link access mode of a power Internet of Things sensing device according to claim 4, characterized in that, The subjective and objective weights corresponding to each evaluation index of the heterogeneous link are fused to obtain the comprehensive weight corresponding to each evaluation index of the heterogeneous link. The fusion method can be any one of the following: minimum information identification principle, linear weighted fusion method, and least squares fusion method.

10. A power Internet of Things (IoT) sensing device link access mode switching system, characterized in that, include: The heterogeneous link scoring acquisition module is used to acquire the evaluation indicators of heterogeneous links and the corresponding weight of each evaluation indicator; Based on the weight of each evaluation indicator and the evaluation indicator value of each heterogeneous link in the power Internet of Things network layer in the previous time period, the score of each heterogeneous link in the power Internet of Things network layer in the previous time period is calculated. The bundling mode scoring module is used to take the average score of all heterogeneous links in the power IoT network layer of the previous time period as the multi-link bundling mode score of the power IoT network layer of the previous time period. The switching mode scoring module takes the maximum score of all heterogeneous links in the power IoT network layer in the previous time period as the multi-way switching mode score of the power IoT network layer in the previous time period. The backup mode scoring module takes the difference between the maximum and minimum scores of all heterogeneous links in the power IoT network layer of the previous time period as the multi-path backup mode score of the power IoT network layer of the previous time period. The selection module is used to select the highest-scoring mode as the target heterogeneous link access mode for the power Internet of Things network layer during the current time period.

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