Low-delay communication routing method and system based on power network

Abstract

The invention provides a low-time-delay communication routing method and system based on a power network, and relates to the technical field of communication routing control. Electromagnetic interference levels and electromagnetic compatibility parameters are considered during path selection, electromagnetic field simulation software is utilized to predict the electromagnetic interference levels in different states in real time, and the communication routing efficiency is improved. A second electromagnetic interference distribution diagram is generated, and the accuracy and optimization effect of path selection are improved; besides, by monitoring and analyzing service transmission requirements and electromagnetic interference environment data of the power internet of things in real time, generating a comprehensive evaluation index, and combining the comprehensive evaluation index with a transmission time delay index, dynamically adjusting a comprehensive priority index of an optimal path, and further improving the self-adaptive capability and response speed of the system.

Description

Technical Field

[0001] The present invention relates to the technical field of communication routing control, and in particular to a low-latency communication routing method and system based on a power network. Background Art

[0002] The power Internet of Things integrates sensors, controllers, and communication modules into power equipment to achieve intelligent interconnection and data exchange between devices. However, with the increasing complexity of power networks and the growth in the number of devices, how to transmit data efficiently and reliably has become an urgent problem to be solved. Traditional communication routing methods have certain limitations in dealing with the high transmission requirements and low latency requirements of the power Internet of Things. Especially in the electromagnetic interference (EMI) environment, the electromagnetic compatibility (EMC) problem is more prominent, affecting the stability and reliability of communication. Therefore, the research on low-latency communication routing methods based on power networks has important practical significance;

[0003] In the prior art, the publication number is CN117857423A, and the name is a low-latency communication routing method and system based on electricity. The method includes: determining the service transmission requirements and network resource requirements according to the application requirements of the power Internet of Things; establishing a broadband resource allocation model using a nonlinear programming method; and determining the optimal routing path for delay-sensitive services according to the network topology in the power Internet of Things scenario.

[0004] Existing technologies mainly rely on fixed path selection and simple interference avoidance strategies in the communication routing of the power Internet of Things. These methods can meet basic communication needs in an ideal environment, but in actual applications, the electromagnetic interference environment faced by the power Internet of Things is complex and changeable, and fixed path selection methods are difficult to adapt to such dynamic changes. In addition, traditional routing methods usually lack consideration of electromagnetic compatibility parameters, resulting in insufficient optimization of communication path selection and high transmission delay in high interference environments, which affects the performance and reliability of the overall system.

[0005] The above information disclosed in the above Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not form the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0006] The purpose of the present invention is to provide a low-latency communication routing method and system based on a power network to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] The low-latency communication routing method based on the power network includes the following specific steps:

[0009] Step S1: collecting the service transmission requirements and electromagnetic interference environment data corresponding to the power Internet of Things of the current device, where the electromagnetic interference environment data includes the electromagnetic interference level and the electromagnetic compatibility parameters of the device; and constructing a first electromagnetic interference distribution map based on the collected electromagnetic interference environment data;

[0010] Step S2: Introduce electromagnetic compatibility as a constraint condition, create an optimization objective function according to the first electromagnetic interference distribution map, and the optimization objective function is that the ratio of resource utilization and electromagnetic interference level is less than a preset threshold value to determine several low-interference transmission paths, and finally construct a multi-level routing optimization model, and comprehensively calculate the transmission delay index according to the output of the multi-level routing optimization model;

[0011] Step S3: Based on the multi-level routing optimization model, electromagnetic field simulation software is used to predict the electromagnetic interference level, so as to simulate the electromagnetic interference level of the current device under different operating conditions in real time, obtain a second electromagnetic interference distribution map, and based on the simulation results, select the path with the least interference and the best bandwidth resource utilization from the several low-interference transmission paths determined in step S2;

[0012] Step S4: Monitor the business transmission requirements and electromagnetic interference environment data of the current device corresponding to the power Internet of Things in real time, analyze and process them, generate a comprehensive evaluation index, combine the transmission delay index with the comprehensive evaluation index for analysis, and generate a comprehensive priority index for dynamically adjusting the optimal path in step S3.

[0013] Furthermore, a comprehensive evaluation index is generated, specifically including:

[0014] The maximum amount of data transmission is marked as CSM, and the allowed delay of data transmission is marked as CSY;

[0015] Conducted emission, radiated emission, conducted immunity and radiated immunity are marked as CF1, CF2, CF3 and CF4 respectively;

[0016] The normalized output values ​​corresponding to the parameters contained in the business transmission requirements and electromagnetic interference environment data are adjusted to the range of (0, 1) by scaling and offsetting;

[0017] x j ∈{CSM, CSY, CF1, CF2, CF3, CF4} are the adjusted parameter values;

[0018] When j takes the values ​​of 1, 2, 3, 4, 5, and 6, they represent CSM, CSY, CF1, CF2, CF3, and CF4;

[0019] The comprehensive evaluation index is defined as CEI, and the calculation formula is as follows:

[0020]

[0021] Among them, x j is the jth parameter value, e is the base of the natural logarithm, α is the adjustment parameter, 0.12≤α≤0.68, α is used to control the decay speed of the exponential function; η1 is a positive constant; 0.02≤η1≤0.11;

[0022] Set the effective value range of the comprehensive evaluation index CEI to (0,1);

[0023] When 0.5≤CEI<1, it is a high priority interval, indicating that the device has high transmission requirements and excellent electromagnetic compatibility;

[0024] When 0.2≤CEI<0.5, it is a medium priority interval, indicating that the equipment has medium transmission requirements and electromagnetic compatibility;

[0025] When 0<CEI<0.2, it is a low priority interval, indicating low-level equipment transmission requirements or poor electromagnetic compatibility.

[0026] Furthermore, the transmission delay index and the comprehensive evaluation index are combined and analyzed to generate a comprehensive priority index for dynamically adjusting the optimal path in step S3, specifically including:

[0027] The transmission delay index and the comprehensive evaluation index are combined, and the generated comprehensive priority index is defined as CPI. The calculation formula is as follows:

[0028]

[0029] Among them, 0.01≤η2≤0.14; when CPI>1, it means that the currently selected optimal path is a low priority path, avoid using it, and reselect from several low-interference transmission paths;

[0030] When 0.5≤CPI≤1, it means that the currently selected optimal path is the medium priority path, and as the suboptimal choice, the optimal one is reselected from several low-interference transmission paths;

[0031] When CPI is less than 0.5, it indicates that the currently selected optimal path is a high priority path and is selected as a priority.

[0032] A low-latency communication routing system based on an electric power network, the system being used to execute the low-latency communication routing method based on an electric power network, comprising:

[0033] Data acquisition module: used to collect the business transmission requirements and electromagnetic interference environment data of the current device corresponding to the power Internet of Things, the electromagnetic interference environment data including the electromagnetic interference level and the electromagnetic compatibility parameters of the device; and based on the collected electromagnetic interference environment data, construct a first electromagnetic interference distribution map;

[0034] Optimization model building module: used to introduce electromagnetic compatibility as a constraint condition, create an optimization objective function according to the first electromagnetic interference distribution map, and the optimization objective function is that the ratio of resource utilization and electromagnetic interference level is less than a preset threshold, so as to determine several low-interference transmission paths, and finally build a multi-level routing optimization model, and comprehensively calculate the transmission delay index according to the output of the multi-level routing optimization model;

[0035] Simulation prediction module: It is used to predict the electromagnetic interference level by using electromagnetic field simulation software based on the multi-level routing optimization model, so as to simulate the electromagnetic interference level of the current equipment under different operating conditions in real time, obtain the second electromagnetic interference distribution map, and select the path with the least interference and the best bandwidth resource utilization from the determined several low-interference transmission paths based on the simulation results;

[0036] Dynamic adjustment module: used to monitor the business transmission requirements and electromagnetic interference environment data of the current equipment corresponding to the power Internet of Things in real time, and analyze and process them to generate a comprehensive evaluation index. The transmission delay index is combined with the comprehensive evaluation index for analysis to generate a comprehensive priority index for dynamic adjustment of the optimal path.

[0037] Compared with the prior art, the beneficial effects of the present invention are as follows: by taking into account the electromagnetic interference level and electromagnetic compatibility parameters when selecting the path, and also using electromagnetic field simulation software to make real-time predictions on the electromagnetic interference level under different states, a second electromagnetic interference distribution map is generated, thereby improving the accuracy and optimization effect of the path selection; in addition, by real-time monitoring and analysis of the business transmission requirements and electromagnetic interference environment data of the power Internet of Things, a comprehensive evaluation index is generated, and combined with the transmission delay index, the comprehensive priority index of the optimal path is dynamically adjusted, thereby further improving the system's adaptability and response speed; these technical means effectively solve the problems of unstable transmission and excessive delay caused by electromagnetic interference in the prior art, and provide an efficient and reliable low-latency communication routing solution for the power Internet of Things. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a schematic diagram of the overall method flow of the present invention;

[0039] Figure 2 It is a system module block diagram of the present invention. DETAILED DESCRIPTION

[0040] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0041] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words 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. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0042] Embodiment 1:

[0043] See also Figure 1 , the present invention provides a technical solution:

[0044] A low-latency communication routing method based on a power network comprises the following steps:

[0045] Step S1: collecting the service transmission requirements and electromagnetic interference environment data corresponding to the power Internet of Things of the current device, where the electromagnetic interference environment data includes the electromagnetic interference level and the electromagnetic compatibility parameters of the device; and constructing a first electromagnetic interference distribution map based on the collected electromagnetic interference environment data;

[0046] Step S2: Introduce electromagnetic compatibility as a constraint condition, create an optimization objective function according to the first electromagnetic interference distribution map, and the optimization objective function is that the ratio of resource utilization and electromagnetic interference level is less than a preset threshold value to determine several low-interference transmission paths, and finally construct a multi-level routing optimization model, and comprehensively calculate the transmission delay index according to the output of the multi-level routing optimization model;

[0047] Step S3: Based on the multi-level routing optimization model, electromagnetic field simulation software is used to predict the electromagnetic interference level, so as to simulate the electromagnetic interference level of the current device under different operating conditions in real time, obtain a second electromagnetic interference distribution map, and based on the simulation results, select the path with the least interference and the best bandwidth resource utilization from the several low-interference transmission paths determined in step S2;

[0048] Step S4: Monitor the business transmission requirements and electromagnetic interference environment data of the current device corresponding to the power Internet of Things in real time, analyze and process them, generate a comprehensive evaluation index, combine the transmission delay index with the comprehensive evaluation index for analysis, and generate a comprehensive priority index for dynamically adjusting the optimal path in step S3.

[0049] Further description: constructing a first electromagnetic interference distribution map based on the collected electromagnetic interference environment data specifically includes:

[0050] 1.1) Extract the service transmission requirements of the current equipment corresponding to the power Internet of Things to clarify the information transmission requirements of delay-sensitive services;

[0051] Information transmission requirements include the maximum amount of data transmitted per unit time, the allowable delay in data transmission, and the quality requirements of the communication link;

[0052] 1.2) The electromagnetic interference level includes the spectrum bandwidth and intensity of the interference source, and the electromagnetic interference level is used as the input parameter for subsequent optimization; these parameters are collected through existing electromagnetic compatibility test equipment;

[0053] Electromagnetic compatibility parameters include conducted emission, radiated emission, conducted immunity and radiated immunity;

[0054] Conducted emission: The electromagnetic energy emitted by the device through the cable, expressed as voltage or current;

[0055] Radiated emission: The electromagnetic energy radiated by a device through space, expressed in terms of field strength;

[0056] Conducted immunity: the resistance of the equipment to electromagnetic interference transmitted through the cable;

[0057] Radiated immunity: the ability of equipment to resist electromagnetic interference transmitted through space;

[0058] 1.3) Based on the collected electromagnetic interference environment data, an electromagnetic compatibility analysis tool is used to visualize the potential interference area and degree in the power Internet of Things corresponding to the current device, and then a first electromagnetic interference distribution map is constructed.

[0059] Electromagnetic compatibility analysis tools use any of the following:

[0060] EMCStud io: Modeling and simulation for electromagnetic compatibility;

[0061] CSTStud ioSuite: widely used in antenna design, signal integrity and electromagnetic interference analysis;

[0062] Ansys HFSS: Focuses on high-frequency electromagnetic field simulation and is suitable for antenna, RF and microwave device analysis.

[0063] Use electromagnetic compatibility analysis tools to visualize potential interference areas and levels in the power Internet of Things, including:

[0064] Use electromagnetic compatibility analysis tools to process data and generate spectrum bandwidth and intensity models of electromagnetic interference sources;

[0065] Input the collected electromagnetic interference level and electromagnetic compatibility parameters into the electromagnetic compatibility analysis tool.

[0066] Use electromagnetic compatibility analysis tools to perform spectrum analysis on electromagnetic signals and identify interference sources in each frequency band.

[0067] Determine the frequency and intensity of major interference sources;

[0068] Based on the spectrum analysis results, a three-dimensional spatial model is established to mark the locations of different interference sources in the network and obtain a 3D topological structure;

[0069] Use color coding or other visual means to identify interference intensity;

[0070] Simulate the impact of different interference sources on each node and calculate their specific impact on signal quality and communication delay.

[0071] Evaluate the compatibility parameters of each node and identify the areas most susceptible to interference.

[0072] The analysis results are integrated into an EMI impact map showing the location of interference sources and their impact range.

[0073] For constructing the first EMI distribution map:

[0074] The acquired spectrum and spatial distribution data will be analyzed to ensure that the data contains the frequency, intensity, location and impact range of the interference source;

[0075] Use MATLAB software tools to color code the three-dimensional space model;

[0076] Define color and identification rules:

[0077] Interference intensity levels: low (0-33%) green, medium (34%-66%) yellow, high (67%-100%) red.

[0078] Generate distribution maps based on the model to identify key interference areas and their intensity levels;

[0079] Export distribution diagrams to PDF format and use them to evaluate and optimize communication paths.

[0080] Further explanation: several low-interference transmission paths are determined, and finally a multi-level routing optimization model is constructed. The transmission delay index is comprehensively calculated based on the output of the multi-level routing optimization model, including:

[0081] 2.1) The optimization objective function is created based on the existing bandwidth resource allocation model. The objective function form is as follows:

[0082] Based on experimental verification and expert analysis, it is determined that the ratio of resource utilization to electromagnetic interference level is less than the preset threshold value as BY1;

[0083]

[0084] Among them, B represents the bandwidth allocation vector, EMI represents the overall electromagnetic interference environment; the goal of this optimization model is to avoid high-interference paths and ensure low-latency communication while meeting business needs; f represents the objective function; according to the relationship between the objective and the variable, it is selected from linear and nonlinear mathematical expressions, which will not be elaborated;

[0085] when When , it is a determined low-interference transmission path; when When , the value of the objective function is infinite, and this transmission path needs to be excluded;

[0086] RUR stands for resource utilization rate, ESL stands for electromagnetic interference level, S i is the spectrum bandwidth of the i-th interference source, I i is the strength of the i-th interference source; n is the number of interference sources, and i represents the index of the i-th interference source;

[0087] When determining bandwidth allocation, the path with RUR less than 30% is selected as the priority path;

[0088] If RUR is reduced by 10% and ESL remains unchanged, f(B,EMI) will be reduced by 10%;

[0089] 2.2) Divide the power Internet of Things into at least four levels and optimize different network levels;

[0090] The four layers are access network layer, core network layer, edge computing layer, and cloud service layer. Each layer is optimized based on electromagnetic interference environment data to minimize the interference impact between layers.

[0091] For the access network layer:

[0092] In the access network layer, the focus is on the electromagnetic environment near the user access end. The main task is to evaluate and mitigate the interference caused by nearby power equipment. The optimization strategy at this level includes adjusting the frequency allocation of equipment and strengthening the electromagnetic shielding of equipment to ensure that users can connect to the power Internet of Things stably and efficiently.

[0093] For the core network layer:

[0094] The core network layer is responsible for the transmission and processing of large-scale data. Its optimization focuses on identifying and mitigating electromagnetic interference from the external environment during cross-regional transmission. By using advanced signal processing technology and anti-interference algorithms, it ensures that data is not interfered with during long-distance transmission, maintaining network efficiency and reliability.

[0095] For the edge computing layer:

[0096] The edge computing layer aims to reduce the latency of data transmission and improve real-time processing capabilities. The optimization of this layer focuses on reducing interference between local devices and terminals, ensuring efficient use of computing resources, and optimizing processing performance through dynamic resource allocation and local caching technology;

[0097] For the cloud service tier:

[0098] The cloud service layer provides data storage and advanced analysis capabilities. The optimization focus is on protecting the cloud infrastructure from large-scale electromagnetic interference, ensuring the integrity and security of the data, and ensuring the continuity and stability of services by adopting advanced cloud security measures and redundant designs, so that normal operations can be maintained even in high-interference environments.

[0099] When determining bandwidth allocation, select paths with RUR less than 30% as several low-interference transmission paths, and determine the benchmark values ​​of electromagnetic shielding coverage, signal processing capability value, local cache technical indicators, and redundant design ratio in turn based on expert group or experimental verification;

[0100] If RUR is reduced by 10% and ESL remains unchanged, f(B,EMI) will be reduced by 10%;

[0101] For access network layer optimization, evaluate the electromagnetic environment at the user access end and adjust frequency allocation;

[0102] If the electromagnetic shielding coverage exceeds 15% of the corresponding benchmark value, the ESL is reduced by 15%, improving the connection stability;

[0103] Define the ESL adjusted by the access network layer as ESL access , and ESL access =ESL(1-0.15);

[0104] For core network layer optimization, signal processing technology is used to reduce cross-region interference;

[0105] When the signal processing capability value exceeds the corresponding benchmark value by 20%, the ESL is reduced by 20%, improving the transmission efficiency;

[0106] Define the adjusted ESL of the core network layer as ESL core , and ESL core =ESL(1-0.2);

[0107] Optimize the edge computing layer, dynamically allocate computing resources, and reduce latency;

[0108] If the local cache technical indicator exceeds the corresponding benchmark value by 25%, the data transmission delay is reduced by 25%;

[0109] Define the ESL adjusted by the edge computing layer as ESL edge , and ESL edge =ESL(1-0.25);

[0110] For cloud service layer optimization, redundant design is adopted to enhance anti-interference capability;

[0111] When the proportion of redundant design exceeds 30% of the corresponding benchmark value, ESL is reduced by 30% to ensure data security;

[0112] Define the adjusted ESL of the cloud service layer as ESL cloud , and ESL cloud =ESL(1-0.3);

[0113] The transmission delay index is defined as Delay, and the calculation formula is as follows:

[0114]

[0115] Where TD is the total data transmission time, P is the path priority, and ESL total is the ESL-adjusted composite average.

[0116] Further explanation: electromagnetic interference level prediction is performed using electromagnetic field simulation software to simulate the electromagnetic interference level of the current device under different operating conditions in real time, obtain a second electromagnetic interference distribution map, and based on the simulation results, select a path with minimal interference and optimal bandwidth resource utilization from among the several low-interference transmission paths determined in step S2, specifically including:

[0117] Different operating states include different business transmission requirements and electromagnetic interference environment data;

[0118] 3.1) The electromagnetic interference level prediction is based on the multi-level routing optimization model, and the electromagnetic field simulation software is COMSOL or CST. The electromagnetic field simulation software is also used to predict the impact of electromagnetic interference levels on different communication links;

[0119] Draw a network topology diagram of the power Internet of Things, marking the device nodes and the connection paths between them; at the same time, superimpose the predicted second electromagnetic interference distribution map with the network topology diagram; specifically including:

[0120] Set the input parameters of the simulation as follows:

[0121] Information transmission requirements include the maximum amount of data transmitted per unit time, the allowable delay in data transmission, and the quality requirements of the communication link;

[0122] Electromagnetic compatibility parameters include conducted emission, radiated emission, conducted immunity and radiated immunity;

[0123] Conducted emission is expressed as conducted voltage; radiated emission is expressed as field strength; conducted immunity is expressed as immunity to interference introduced by cables; radiated immunity is expressed as immunity to interference introduced by space;

[0124] Choose COMSOL Multiphysics: This software has multi-physics coupling capabilities and is suitable for simulation of complex electromagnetic environments;

[0125] Obtain the 3D topology structure drawn in step S1: establish a 3D model of the device and connection path according to the actual device layout of the power Internet of Things;

[0126] Set the material parameters and boundary conditions of the current device; set open boundary conditions to simulate electromagnetic radiation in open space, and set absorbing boundary conditions to reduce reflection effects;

[0127] Start COMSOL simulation: Run the simulation calculation of electromagnetic interference level according to the set input parameters and physical model;

[0128] generating a second electromagnetic interference distribution diagram to display the electromagnetic interference distribution of the interference source at different spectrum bandwidths and intensities;

[0129] Mark areas where interference intensity exceeds 85% for subsequent route optimization;

[0130] Identify key interference nodes: Combine the network topology of the power Internet of Things to identify high-interference nodes and areas;

[0131] Based on data from high-interference areas, adjust communication routes to avoid transmitting delay-sensitive services in these areas;

[0132] Ensure that the quality of the communication link reaches more than 95% and reduce the data transmission delay to 80% of the original;

[0133] 3.2) Based on the simulation results, the network topology diagram of the power Internet of Things is superimposed on the second electromagnetic interference distribution diagram to determine the transmission path with the least interference and the best bandwidth resource utilization; specifically, including:

[0134] The power Internet of Things is regarded as a graph model. Based on the several low-interference transmission paths determined in step S2, each communication node is a vertex in the graph, and the links between the nodes are the edges of the graph. For each link, the following two weights are assigned:

[0135] Interference weight: Based on simulation results, the higher the interference intensity, the greater the weight;

[0136] Bandwidth weight: indicates the bandwidth resource utilization of the path. The better the bandwidth resource, the smaller the weight.

[0137] These two factors are combined into a comprehensive weight to define the transmission cost of each path; the total transmission cost of a path is the sum of the interference and bandwidth weights of each link on the path;

[0138] Use dynamic programming algorithm to select the optimal path, which is implemented as follows:

[0139] Define the problem state as: the minimum transmission cost path from the starting node to the target node, define an array, and use the array to record the minimum transmission cost of each node;

[0140] For each node, calculate the minimum transmission cost to the next node and update the array;

[0141] By iteratively calculating the minimum transmission cost of each node, the optimal path to the target node is finally determined gradually starting from the starting node;

[0142] The optimal path from the starting node to the target node is obtained through dynamic planning calculation, that is, the transmission path with the minimum electromagnetic interference and the best bandwidth resource utilization; this path is directly applied to the routing planning of the power Internet of Things through automated scripts or management systems.

[0143] Further explanation: generating a comprehensive evaluation index, combining the transmission delay index with the comprehensive evaluation index for analysis, and generating a comprehensive priority index for dynamically adjusting the optimal path in step S3, specifically includes:

[0144] The maximum amount of data transmission currently monitored is marked as CSM, and the allowed delay of data transmission is marked as CSY;

[0145] The conducted emission, radiated emission, conducted immunity and radiated immunity currently monitored are marked as CF1, CF2, CF3 and CF4 respectively;

[0146] The normalized output values ​​corresponding to the parameters contained in the business transmission requirements and electromagnetic interference environment data are adjusted to the range of (0, 1) by scaling and offsetting;

[0147] x j ∈{CSM, CSY, CF1, CF2, CF3, CF4} are the adjusted parameter values;

[0148] When j takes the values ​​of 1, 2, 3, 4, 5, and 6, they represent CSM, CSY, CF1, CF2, CF3, and CF4;

[0149] The comprehensive evaluation index is defined as CEI, and the calculation formula is as follows:

[0150]

[0151] Among them, x j is the jth parameter value, e is the base of the natural logarithm, α is the adjustment parameter, 0.12≤α≤0.68, α is used to control the decay speed of the exponential function; η1 is a positive constant; 0.02≤η1≤0.11; the specific values ​​of α and η1 are determined by the expert group through experimental data;

[0152] Set the effective value range of the comprehensive evaluation index CEI to (0,1);

[0153] For advanced transmission requirements and excellent electromagnetic compatibility:

[0154] Advanced transmission requirements:

[0155] Maximum data transmission (CSM) ≥ 80Mbps;

[0156] The allowed delay of data transmission (CSY) is ≤30ms;

[0157] Excellent electromagnetic compatibility:

[0158] Conducted emission (CF1) ≤ 10dB;

[0159] Radiated emission (CF2) ≤ 20dB;

[0160] Conducted immunity (CF3) ≥ 80dB;

[0161] Radiated immunity (CF4) ≥ 60dB;

[0162] For medium transmission requirements and electromagnetic compatibility:

[0163] Medium transmission requirements:

[0164] The maximum data transfer rate (CSM) is between 40 and 80 Mbps;

[0165] The allowable delay (CSY) for data transmission is between 30 and 70 ms;

[0166] Medium EMC:

[0167] Conducted emission (CF1) is between 10 and 20 dB;

[0168] Radiated emission (CF2) between 20 and 40 dB;

[0169] Conducted immunity (CF3) is between 60 and 80dB;

[0170] Radiated immunity (CF4) is between 40 and 60 dB;

[0171] For devices with low transmission requirements or poor electromagnetic compatibility:

[0172] Low-end device transmission requirements:

[0173] Maximum data transmission (CSM) < 40Mbps;

[0174] Data transmission allowable delay (CSY)> 70ms;

[0175] Poor electromagnetic compatibility:

[0176] Conducted emission (CF1)>20dB;

[0177] Radiated emission (CF2)>40dB;

[0178] Conducted immunity (CF3) < 60dB;

[0179] Radiated immunity (CF4) < 40dB;

[0180] When 0.5≤CE I<1, it is a high priority interval, indicating that the device has high transmission requirements and excellent electromagnetic compatibility;

[0181] When 0.2≤CE I<0.5, it is a medium priority interval, indicating that the equipment has medium transmission requirements and electromagnetic compatibility;

[0182] When 0<CE I<0.2, it is a low priority interval, indicating low-level equipment transmission requirements or poor electromagnetic compatibility;

[0183] The transmission delay index and the comprehensive evaluation index are combined, and the generated comprehensive priority index is defined as CPI. The calculation formula is as follows:

[0184]

[0185] Among them, 0.01≤η2≤0.14; the specific value of η2 is determined by the expert group through experimental data;

[0186] When CPI>1, it means that the currently selected optimal path is a low-priority path, so it should be avoided and reselected from several low-interference transmission paths;

[0187] When 0.5≤CPI≤1, it means that the currently selected optimal path is the medium priority path, and as the suboptimal choice, the optimal one is reselected from several low-interference transmission paths;

[0188] When CPI is less than 0.5, it indicates that the currently selected optimal path is a high priority path and is selected as a priority.

[0189] Embodiment 2:

[0190] See also Figure 2 , a low-latency communication routing system based on a power network, the system is used to execute the low-latency communication routing method based on a power network, comprising:

[0191] Data acquisition module: used to collect the business transmission requirements and electromagnetic interference environment data of the current device corresponding to the power Internet of Things, the electromagnetic interference environment data including the electromagnetic interference level and the electromagnetic compatibility parameters of the device; and based on the collected electromagnetic interference environment data, construct a first electromagnetic interference distribution map;

[0192] Optimization model building module: used to introduce electromagnetic compatibility as a constraint condition, create an optimization objective function according to the first electromagnetic interference distribution map, and the optimization objective function is that the ratio of resource utilization and electromagnetic interference level is less than a preset threshold, so as to determine several low-interference transmission paths, and finally build a multi-level routing optimization model, and comprehensively calculate the transmission delay index according to the output of the multi-level routing optimization model;

[0193] Simulation prediction module: It is used to predict the electromagnetic interference level by using electromagnetic field simulation software based on the multi-level routing optimization model, so as to simulate the electromagnetic interference level of the current equipment under different operating conditions in real time, obtain the second electromagnetic interference distribution map, and select the path with the least interference and the best bandwidth resource utilization from the determined several low-interference transmission paths based on the simulation results;

[0194] Dynamic adjustment module: used to monitor the business transmission requirements and electromagnetic interference environment data of the current equipment corresponding to the power Internet of Things in real time, and analyze and process them to generate a comprehensive evaluation index. The transmission delay index is combined with the comprehensive evaluation index for analysis to generate a comprehensive priority index for dynamic adjustment of the optimal path.

[0195] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0196] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0197] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0198] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A low-latency communication routing method based on a power network, characterized in that: The specific steps include: Step S1: collecting the service transmission requirements and electromagnetic interference environment data corresponding to the power Internet of Things of the current device, where the electromagnetic interference environment data includes the electromagnetic interference level and the electromagnetic compatibility parameters of the device; and constructing a first electromagnetic interference distribution map based on the collected electromagnetic interference environment data; Step S2: Introduce electromagnetic compatibility as a constraint condition, create an optimization objective function according to the first electromagnetic interference distribution map, and the optimization objective function is that the ratio of resource utilization and electromagnetic interference level is less than a preset threshold value to determine several low-interference transmission paths, and finally construct a multi-level routing optimization model, and comprehensively calculate the transmission delay index according to the output of the multi-level routing optimization model; Step S3: Based on the multi-level routing optimization model, electromagnetic field simulation software is used to predict the electromagnetic interference level, so as to simulate the electromagnetic interference level of the current device under different operating conditions in real time, obtain a second electromagnetic interference distribution map, and based on the simulation results, select the path with the least interference and the best bandwidth resource utilization from the several low-interference transmission paths determined in step S2; Step S4: Monitor the business transmission requirements and electromagnetic interference environment data of the current device corresponding to the power Internet of Things in real time, analyze and process them, generate a comprehensive evaluation index, combine the transmission delay index with the comprehensive evaluation index for analysis, and generate a comprehensive priority index for dynamically adjusting the optimal path in step S3.

2. The low-latency communication routing method based on the power network according to claim 1, characterized in that: Based on the collected electromagnetic interference environment data, a first electromagnetic interference distribution map is constructed, which specifically includes: 1.1) Information transmission requirements include the maximum amount of data transmitted per unit time and the allowable delay of data transmission; 1.2) The electromagnetic interference level includes the spectrum bandwidth and intensity of the interference source, and the electromagnetic interference level is used as an input parameter for subsequent optimization; Electromagnetic compatibility parameters include conducted emission, radiated emission, conducted immunity and radiated immunity; 1.3) Based on the collected electromagnetic interference environment data, an electromagnetic compatibility analysis tool is used to visualize the potential interference area and degree in the power Internet of Things corresponding to the current device, and then a first electromagnetic interference distribution map is constructed.

3. The low-latency communication routing method based on the power network according to claim 2, characterized in that: Determine several low-interference transmission paths, and finally build a multi-level routing optimization model. Based on the output of the multi-level routing optimization model, comprehensively calculate the transmission delay index, including: 2.1) The objective function is as follows: Based on experimental verification and expert analysis, it is determined that the ratio of resource utilization to electromagnetic interference level is less than the preset threshold value as BY1; Where B represents the bandwidth allocation vector, EMI represents the overall electromagnetic interference environment; the goal of this optimization model is to avoid high-interference paths and ensure low-latency communication while meeting business needs; f represents the objective function; when When , it is a determined low-interference transmission path; when When , the value of the objective function is infinite, and this transmission path needs to be excluded; RUR stands for resource utilization rate, ESL stands for electromagnetic interference level, S i is the spectrum bandwidth of the i-th interference source, I i is the strength of the i-th interference source; n is the number of interference sources, and i represents the index of the i-th interference source; When determining bandwidth allocation, select the path with RUR less than 30% as the priority path; If RUR is reduced by 10% and ESL remains unchanged, f(B,EMI) will be reduced by 10%; 2.2) Divide the power Internet of Things into at least four levels and optimize different network levels; The four layers are access network layer, core network layer, edge computing layer, and cloud service layer. Each layer is optimized based on electromagnetic interference environment data to minimize the interference impact between layers. When determining bandwidth allocation, select paths with RUR less than 30% as several low-interference transmission paths, and determine the benchmark values ​​of electromagnetic shielding coverage, signal processing capability value, local cache technical indicators, and redundant design ratio in turn based on expert group or experimental verification; If RUR is reduced by 10% and ESL remains unchanged, f(B,EMI) will be reduced by 10%; For access network layer optimization, evaluate the electromagnetic environment at the user access end and adjust frequency allocation; If the electromagnetic shielding coverage exceeds the corresponding benchmark value by 15%, the ESL is reduced by 15% to improve the connection stability; Define the ESL adjusted by the access network layer as ESL access , and ESL access =ESL(1-0.15); For core network layer optimization, signal processing technology is used to reduce cross-region interference; When the signal processing capability value exceeds the corresponding benchmark value by 20%, the ESL is reduced by 20% to improve the transmission efficiency; Define the adjusted ESL of the core network layer as ESL core , and ESL core =ESL(1-0.2); Optimize the edge computing layer, dynamically allocate computing resources, and reduce latency; If the local cache technical indicator exceeds the corresponding benchmark value by 25%, the ESL is reduced by 25%; Define the ESL adjusted by the edge computing layer as ESL edge , and ESL edge =ESL(1-0.25); For cloud service layer optimization, redundant design is adopted to enhance anti-interference capability; When the proportion of redundant design exceeds 30% of the corresponding benchmark value, ESL is reduced by 30% to ensure data security; Define the adjusted ESL of the cloud service layer as ESL cloud , and ESL cloud =ESL(1-0.3); The transmission delay index is defined as Delay, and the calculation formula is as follows: Where TD is the total data transmission time, P is the path priority, and ESL total is the ESL-adjusted composite average.

4. The low-latency communication routing method based on the power network according to claim 3 is characterized in that: Electromagnetic interference level prediction is performed using electromagnetic field simulation software to simulate the electromagnetic interference level of the current device under different operating conditions in real time, and a second electromagnetic interference distribution diagram is obtained. Based on the simulation results, a path with minimal interference and optimal bandwidth resource utilization is selected from among the several low-interference transmission paths determined in step S2, specifically including: Different operating states include different business transmission requirements and electromagnetic interference environment data; 3.1) The electromagnetic interference level prediction is to draw a network topology diagram of the power Internet of Things based on a multi-level routing optimization model, marking the device nodes and the connection paths between them; at the same time, the predicted second electromagnetic interference distribution map is superimposed on the network topology map; 3.2) Based on the simulation results, the network topology diagram of the power Internet of Things is superimposed on the second electromagnetic interference distribution diagram to determine the transmission path with minimal interference and optimal bandwidth resource utilization.

5. The low-latency communication routing method based on the power network according to claim 4, characterized in that: Generate a comprehensive evaluation index, including: The maximum amount of data transmission currently monitored is marked as CSM, and the allowed delay of data transmission is marked as CSY; The conducted emission, radiated emission, conducted immunity and radiated immunity currently monitored are marked as CF1, CF2, CF3 and CF4 respectively; The normalized output values ​​corresponding to the parameters contained in the business transmission requirements and electromagnetic interference environment data are adjusted to the range of (0, 1) by scaling and offsetting; x j ∈{CSM, CSY, CF1, CF2, CF3, CF4} are the adjusted parameter values; When j takes the values ​​of 1, 2, 3, 4, 5, and 6, they represent CSM, CSY, CF1, CF2, CF3, and CF4; The comprehensive evaluation index is defined as CEI, and the calculation formula is as follows: Among them, x j is the jth parameter value, e is the base of the natural logarithm, α is the adjustment parameter, 0.12≤α≤0.68, α is used to control the decay speed of the exponential function; η1 is a positive constant; 0.02≤η1≤0.11; Set the effective value range of the comprehensive evaluation index CEI to (0,1); When 0.5≤CEI<1, it is a high priority interval, indicating that the device has high transmission requirements and excellent electromagnetic compatibility; When 0.2≤CEI<0.5, it is a medium priority interval, indicating that the equipment has medium transmission requirements and electromagnetic compatibility; When 0<CEI<0.2, it is a low priority interval, indicating that the device has low-level device transmission requirements or poor electromagnetic compatibility.

6. The low-latency communication routing method based on the power network according to claim 5, characterized in that: The transmission delay index and the comprehensive evaluation index are combined and analyzed to generate a comprehensive priority index for dynamically adjusting the optimal path in step S3, specifically including: The transmission delay index and the comprehensive evaluation index are combined, and the generated comprehensive priority index is defined as CPI. The calculation formula is as follows: Among them, 0.01≤η2≤0.14; when CPI>1, it means that the currently selected optimal path is a low priority path, avoid using it, and reselect from the remaining several low-interference transmission paths; When 0.5≤CPI≤1, it means that the currently selected optimal path is the medium priority path. As the second-best choice, the optimal one is reselected from the remaining several low-interference transmission paths; When CPI is less than 0.5, it indicates that the currently selected optimal path is a high priority path and is selected as a priority.

7. A low-latency communication routing system based on a power network, characterized in that: The system is used to execute the low-latency communication routing method based on the power network according to any one of claims 1 to 8, comprising: Data acquisition module: used to collect the business transmission requirements and electromagnetic interference environment data of the current device corresponding to the power Internet of Things, the electromagnetic interference environment data including the electromagnetic interference level and the electromagnetic compatibility parameters of the device; and based on the collected electromagnetic interference environment data, construct a first electromagnetic interference distribution map; Optimization model building module: used to introduce electromagnetic compatibility as a constraint condition, create an optimization objective function according to the first electromagnetic interference distribution map, and the optimization objective function is that the ratio of resource utilization and electromagnetic interference level is less than a preset threshold, so as to determine several low-interference transmission paths, and finally build a multi-level routing optimization model, and comprehensively calculate the transmission delay index according to the output of the multi-level routing optimization model; Simulation prediction module: It is used to predict the electromagnetic interference level by using electromagnetic field simulation software based on the multi-level routing optimization model, so as to simulate the electromagnetic interference level of the current equipment under different operating conditions in real time, obtain the second electromagnetic interference distribution map, and select the path with the least interference and the best bandwidth resource utilization from the determined several low-interference transmission paths based on the simulation results; Dynamic adjustment module: used to monitor the business transmission requirements and electromagnetic interference environment data of the current equipment corresponding to the power Internet of Things in real time, and analyze and process them to generate a comprehensive evaluation index. The transmission delay index is combined with the comprehensive evaluation index for analysis to generate a comprehensive priority index for dynamic adjustment of the optimal path.

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