A data communication method for power dual-mode

Abstract

The present application discloses a data communication method for electric power dual-mode, which relates to the field of communication technology, including: obtaining all sub-transmission paths based on preset transmission paths and network nodes, and selecting an initial communication channel for each sub-transmission path based on a target evaluation value; obtaining original transmission data, dividing the original transmission data into a number of basic data packets, selecting corresponding initial communication channels and sub-transmission paths according to the basic data packets, and forming a transmission scheme; obtaining a state value of each sub-transmission path based on a load monitoring mechanism, obtaining an optimization level according to the state value and a preset benchmark value, and readjusting the transmission scheme according to the optimization level and an unloading mechanism; generating a transmission scheme by reasonably cutting the original transmission data and combining it with the real-time channel status, monitoring in real time and setting an unloading mechanism to dynamically optimize and adjust the transmission scheme, thereby achieving the effect of improving data transmission efficiency and stability.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and in particular to a data communication method for power dual-mode. Background Art

[0002] A single communication network can no longer meet people's communication needs. For example, a single power line carrier network uses lines to connect various communication networks, so that communication between each network can only be carried out along a predetermined path. In addition, in the case of a relatively harsh physical environment, the connection relationship between nodes in the network is easily greatly affected, making it unsuitable for long-distance communication. At the same time, when the communication channel noise is relatively large, the communication success rate and communication quality are easily greatly affected.

[0003] Chinese invention patent application number 202410518216.0 discloses a data communication method between dual-mode systems for power grids, which obtains all sub-transmission paths and corresponding unique marking information, obtains the target evaluation values ​​of the two channels on each sub-transmission path according to the historical channel evaluation table, determines the communication channel of each sub-transmission path, and transmits the first data between the source node and the target node.

[0004] In communication networks, there are many factors that affect communication quality and data transmission efficiency. However, in the existing technology, the transmission channel is selected only based on the target evaluation value obtained from the historical channel evaluation table, ignoring the influence of other factors, reducing data transmission efficiency, and at the same time reducing the stability and flexibility of data communication. Summary of the Invention

[0005] This application solves the problem of low data transmission efficiency caused by a single fixed evaluation selection channel in the prior art by providing a data communication method for power dual-mode, and achieves the technical effect of adjusting the data transmission mode based on multi-dimensional factors to improve data transmission efficiency, communication stability and flexibility.

[0006] The present application provides a data communication method for power dual-mode, comprising:

[0007] S100: Dividing all sub-transmission paths based on the preset transmission path and network nodes, obtaining target evaluation values ​​of two channels on each sub-transmission path according to the historical channel evaluation table, and selecting an initial communication channel for each sub-transmission path based on the target evaluation values;

[0008] S200: Obtaining original transmission data, dividing the original transmission data into a number of basic data packets, selecting corresponding initial communication channels and sub-transmission paths according to the basic data packets, and forming a transmission plan;

[0009] S300: Obtaining a status value of each sub-transmission path based on a load monitoring mechanism, obtaining an optimization level based on the status value and a preset benchmark value, and re-adjusting the transmission plan based on the optimization level and the offloading mechanism;

[0010] Step S300 further includes: S310: marking a sub-transmission path whose state value is greater than a reference value as a deviation path, marking the corresponding network node as a deviation node, determining the total number of deviation paths, and obtaining an optimization level according to the difference between the state value and the reference value;

[0011] S320: Obtain the real-time load and unloading resources of each deviation node, obtain the principle indicator set of the deviation path where the unloading resources overlap, obtain the corresponding scheduling value, determine the unloading order according to the scheduling value and the optimization level, and adjust the transmission plan according to the unloading order.

[0012] Furthermore, the original transmission data is divided into several basic data packets, including: preliminary division according to different logical structures in the original transmission data to form initial data packets; obtaining corresponding processing values ​​based on the historical status value of each network node; and obtaining several basic data packets using a fine-grained packetization mechanism based on the initial data packets and the processing values.

[0013] Furthermore, the processing value refers to the maximum amount of data that each network node processes in a data packet; the fine-grained packet subdivision mechanism is: performing the first matching and cutting based on the initial data packet and the processing value, automatically cutting and matching again the initial data packet that has not been successfully matched, until all the initial data packets are cut.

[0014] Furthermore, the unloading mechanism includes: establishing an adaptive unloading model to adjust the current unloading rate in real time, and setting a hierarchical unloading strategy to determine the unloading order and unloading time according to the priority of the basic data packet; setting a sharing mechanism to determine the unloading tendency path according to the sharing mechanism; and readjusting the transmission plan based on the current unloading rate, unloading order, unloading time and unloading tendency path.

[0015] Furthermore, the apportionment mechanism is: obtaining the radiation path of the sub-transmission path that currently needs to be unloaded, and determining the unloading tendency path according to the unloading rate and the state value of the radiation path; the number of the radiation paths is greater than the number of the apportionment paths.

[0016] Furthermore, the radiation path of the sub-transmission path that currently needs to be unloaded is obtained, including: establishing a network topology map based on all network nodes and sub-transmission paths, performing feasibility detection and analysis on all sub-transmission paths based on the network topology map, and obtaining detection results; based on the network topology map and the detection results, all paths starting from the network nodes of the sub-transmission path that currently needs to be unloaded are obtained and marked as radiation paths.

[0017] Furthermore, the unloading tendency path is determined according to the unloading rate and the state value of the radiation path, including: determining the number of unloading tendency paths according to the unloading rate, arranging the state value of each radiation path in descending order, and selecting the radiation paths as the unloading tendency paths in order according to the number of unloading tendency paths.

[0018] Furthermore, the method also includes: S400: connecting all deviation nodes to form a detection node line array; when the detection node line array detects a deviation node, dynamically adjusting the decomposition granularity of the original transmission data to form an unloading path combination; defining a path combination evaluation index, and forming a priority queue based on the path combination evaluation index result; determining the unloading order based on the priority queue.

[0019] Furthermore, the method also includes: S500: obtaining historical data unloading records, establishing a load abnormality pattern library, dynamically updating network node status data in real time, detecting critical load values, and predicting potentially congested network nodes; based on potentially congested network nodes, pre-setting unloading resources and executing step S400.

[0020] Furthermore, the path combination evaluation index includes: complementarity between paths, transmission efficiency after path combination, and load balancing after combination.

[0021] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0022] By reasonably cutting the original transmission data and generating a transmission plan based on the real-time channel conditions, real-time monitoring and setting up an offload mechanism to dynamically optimize and adjust the transmission plan, the effect of improving data transmission efficiency and stability is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 The figure is a flow chart of a data communication method for power dual-mode according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] To facilitate understanding of the present invention, the present application will be described more comprehensively below with reference to the relevant drawings; the drawings show preferred embodiments of the present invention, but the present invention can be implemented in many different forms and is not limited to the embodiments described herein; on the contrary, the purpose of providing these embodiments is to enable a more thorough and comprehensive understanding of the disclosed content of the present invention.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains; the terms used herein in the specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention; the term "and / or" used herein includes any and all combinations of one or more of the associated listed items.

[0026] Example 1: Figure 1 As shown in Figure 1, the dual-mode system for power grids is based on power line broadband carrier and micropower wireless communication. All network nodes support both power line broadband carrier and micropower wireless communication modes, corresponding to carrier channels and wireless channels, respectively. The network nodes can include communication devices, smart meters, and servers.

[0027] During data communication, the geographic location of all network nodes is relatively fixed and does not change arbitrarily. However, due to geographic constraints, there may be situations where two network nodes (source and destination nodes) cannot communicate with each other. For such nodes, they need to connect to one or more other network nodes to achieve communication between them. Therefore, a predetermined transmission path exists for data communication between the source and destination nodes. Due to geographical factors, for example, in a dual-mode communication system, some network nodes are located in the basement of a large building. Power line broadband carrier communication is feasible for these network nodes. However, due to the multi-level routing and signal penetration limitations, micropower wireless communication results in a communication rate that is too low to meet the actual needs of service data transmission. In this case, these network nodes can communicate with each other via power line broadband carrier communication. When cabling between any communicative network nodes is difficult, such as when network nodes are located on opposite sides of a river, where cabling is particularly difficult and expensive, these network nodes can communicate with each other via micropower wireless communication. When two network nodes can communicate via power line broadband carrier communication or micropower wireless communication, the communication method with better communication quality can be preferred. Through the mutual complementation of power line broadband carrier and micro-power wireless communication, the network coverage is expanded and efficient and reliable data transmission functions are achieved.

[0028] like Figure 1 As shown, a data communication method for power dual-mode, the method comprising:

[0029] S100: Dividing all sub-transmission paths based on the preset transmission path and network nodes, obtaining target evaluation values ​​of two channels on each sub-transmission path according to the historical channel evaluation table, and selecting an initial communication channel for each sub-transmission path based on the target evaluation values;

[0030] In some embodiments, a dual-mode system establishes a dual-mode communication network with a source node and a destination node for transmitting data from the source node to the destination node, marking the data initially transmitted as the original transmission data. The preset transmission path is based on the transmission path from the source node to the destination node, and all sub-transmission paths are obtained by dividing the preset transmission path according to all adjacent network nodes, and each sub-transmission path is assigned unique tag information. The number of sub-transmission paths is the number of network nodes in the preset transmission path minus 1, and the unique tag information of each sub-transmission path is composed of the device numbers corresponding to the starting and ending network nodes of the sub-transmission path. For example, if the device numbers corresponding to the starting and ending network nodes of a sub-transmission path are A and B, respectively, the unique tag information of the sub-transmission path is AB.

[0031] In some embodiments, the historical channel evaluation table includes several storage units consisting of unique identification information for each sub-transmission path, a communication period, a communication time type, and evaluation values ​​corresponding to two channels. The communication period refers to the time period after the starting node of the corresponding sub-transmission path sends the original transmission data. Each storage unit is bound to the unique identification information of the corresponding sub-transmission path. The communication time type is defined based on the load status of the power grid and can include peak period, off-peak period, off-peak period, and special period.

[0032] In some embodiments, obtaining the target evaluation value specifically includes: obtaining the attribute parameters of each channel in the corresponding communication time period, and the attribute parameters include the communication success rate, the load transmission rate, and the channel quality. The communication success rate is calculated based on the message receiving and sending information of the sub-transmission path within a predetermined time interval, and the message receiving and sending information includes the number of messages sent by the starting node of the sub-transmission path and the number of messages successfully received by the ending node. The load transmission rate is determined by the ratio of the load data length to the time used to transmit the load data. The channel quality is determined by CQI, which is an information indicator of channel quality, used to indicate the quality of the current channel. The value range is 0 to 31. The higher the value, the better the channel quality.

[0033] Weights are assigned based on the weights of the communication success rate, payload transmission rate, and channel quality in the channel measurement. A weighted average of these values ​​is calculated based on the weights, and this average is used as the target evaluation value for the corresponding channel of the sub-transmission path. The communication channel for each sub-transmission path is determined by comparing the target evaluation values ​​corresponding to the two channels of the sub-transmission path. The communication channel with the higher target evaluation value is selected as the communication channel for the corresponding sub-transmission path.

[0034] Based on the communication requirements between the source node and the target node in the dual-mode communication network, a preset transmission path is obtained, for example, the path from the source node S to the target node T is SABCT. According to the connection relationship of all adjacent network nodes in the preset transmission path, several sub-transmission paths are obtained, such as SA, AB, BC, and CT. The starting and ending network nodes of each sub-transmission path are extracted, and the device numbers corresponding to the starting and ending network nodes are obtained, for example, S is numbered 001 and A is numbered 002. The device numbers of the starting and ending network nodes are combined according to the preset rules to generate unique tag information for each sub-transmission path, for example, the unique tag information of SA is 001-002. If the starting and ending network node device numbers of the sub-transmission path are A and B respectively, the unique tag information is determined to be 002-003. Based on the unique tag information of the sub-transmission path, a mapping relationship between the sub-transmission path and the starting and ending network nodes is established, for example, 001-002 corresponds to SA, and 002-003 corresponds to AB. The unique tag information of the sub-transmission path is stored in a preset database for use in the generation and optimization of subsequent transmission plans. For example, tag information such as 001-002 and 002-003 is stored in the database. Based on the unique tag information of the sub-transmission path, the historical channel evaluation table corresponding to each sub-transmission path is obtained. For example, the historical channel evaluation table for 001-002 is extracted from the database. From the historical channel evaluation table, the communication success rate, payload transmission rate, and channel quality data of the two channels on each sub-transmission path are extracted. For example, the communication success rate of channel 1 of 001-002 is 95%, the payload transmission rate is 100 Mbps, and the channel quality is 90.

[0035] S200: Obtaining original transmission data, dividing the original transmission data into a number of basic data packets, selecting corresponding initial communication channels and sub-transmission paths according to the basic data packets, and forming a transmission plan;

[0036] The original transmission data refers to all the data that needs to be transmitted. The original transmission data is divided according to the cutting mechanism, and is divided by setting a fixed-size segmentation base. It is divided into several basic data packets according to the size of the original transmission data; preferably, different cutting strategies are set in combination with the data type of the original transmission data, and no specific restrictions are made in this embodiment.

[0037] In some embodiments, for each basic data packet, an optimal transmission channel is selected based on its type, size, and real-time channel conditions. A corresponding sub-transmission path is determined based on the determined transmission channel for transmission. After all basic data packets and corresponding sub-transmission paths are determined, a transmission plan is generated. The transmission plan includes the basic data packet, the transmission channel, the corresponding sub-transmission path, the initial state value of the transmission channel, the transmission start time, and the expected transmission end time.

[0038] Specifically, the process obtains raw transmission data, extracts its size and data type, and obtains basic information about the raw transmission data. Based on the size of the raw transmission data, the raw transmission data is segmented using a fixed-size segmentation radix to obtain a number of basic data packets. If the data type of the raw transmission data is a specific type, a segmentation strategy is set based on the characteristics of the data type to adjust the segmentation method for the basic data packets. The type, size, and real-time channel status of each basic data packet are obtained to obtain transmission attribute information for the basic data packet. Based on the type, size, and real-time channel status of the basic data packet, the optimal initial communication channel is selected and the transmission channel for each basic data packet is determined. Based on the determined transmission channel, the corresponding sub-transmission path is selected to obtain sub-transmission path information for each basic data packet. The initial state value of the transmission channel is obtained, the transmission start time is recorded, and the estimated transmission end time is calculated to obtain the state and time information of the transmission channel. The basic data packet, transmission channel, sub-transmission path, initial state value of the transmission channel, transmission start time, and estimated transmission end time are integrated to generate a transmission plan. According to the generated transmission plan, the transmission process of the basic data packet is executed to complete the data transmission task.

[0039] Specifically, the original transmission data is obtained, and the data size and data type are extracted. For example, the data size is read from the data header information as 1024MB, and the data type is a video stream, to obtain the basic information of the original transmission data. Based on the size of the original transmission data, a fixed-size segmentation base is adopted, for example, the size of each basic data packet is 10MB, and the original transmission data is segmented to obtain 102 basic data packets. If the data type of the original transmission data is a specific type, such as a video stream, a corresponding segmentation strategy is set based on the characteristics of the data type, and a frame-based segmentation method is adopted to adjust the segmentation method of the basic data packets. The type, size, and real-time channel status of each basic data packet are obtained. For example, the bandwidth of the current channel is obtained as 100Mbps through the channel monitoring module, and the transmission attribute information of the basic data packet is obtained. Based on the type, size, and real-time channel status of the basic data packet, the optimal initial communication channel is selected. Based on the determined transmission channel, the corresponding sub-transmission path is selected, for example, path A is selected by matching the routing table to obtain the sub-transmission path information of each basic data packet. Obtain the initial state of the transmission channel. For example, assume the channel delay is 10ms, record the transmission start time as 10:00:00 on October 1, 2024, and calculate the estimated transmission end time as 10:01:40 on October 1, 2024. This will determine the state and time of the transmission channel. The basic data packet, transmission channel, sub-transmission path, initial state of the transmission channel, transmission start time, and estimated transmission end time are combined to generate a transmission plan. Based on the generated transmission plan, execute the basic data packet transmission process to complete the data transmission task.

[0040] S300: Obtaining a status value of each sub-transmission path based on a load monitoring mechanism, obtaining an optimization level according to the status value and a preset benchmark value, and readjusting the transmission plan according to the optimization level and the offloading mechanism.

[0041] A pre-configured load monitoring mechanism monitors the load of each sub-transmission path in real time, collecting load monitoring data, including metrics such as transmission rate, latency, jitter, packet loss rate, and bandwidth. Based on this load monitoring data, a status value is calculated for each sub-transmission path. The status value is a comprehensive metric, obtained by weighted summing the different load monitoring data. The specific weighted summation of the monitored data metrics will depend on the actual situation, and this application does not impose any specific restrictions.

[0042] A reference value is pre-set, and the optimization level of each sub-transmission path is determined based on the status value and the reference value. The optimization level is set based on the difference between the status value and the reference value. The larger the difference, the higher the optimization level. Preferably, the obtained differences are sorted in descending order and then graded. The optimization level is divided into three levels: high, medium, and low, corresponding to the three situations of needing urgent adjustment, needing attention, and being in good condition, respectively.

[0043] Develop appropriate adjustment strategies based on the optimization level. For example, for sub-transmission paths with high optimization levels, the path re-partitioning process needs to be immediately triggered to reselect the optimal communication channel. The load ratio of each sub-transmission path is monitored in real time. The load ratio is the ratio of the current load to the maximum load capacity. When a sub-transmission path is overloaded or its quality degrades, the data traffic on that path needs to be smoothly offloaded to other available paths to implement an offloading mechanism. The offloading process is based on historical channel assessment values ​​and real-time test results. By calculating the load capacity and current status of each path, the optimal offloading strategy is formulated. The adjustment strategy is implemented to ensure the stability and reliability of data transmission.

[0044] Specifically, the benchmark values ​​include threshold ranges for transmission rate, latency, and packet loss rate. Based on a load monitoring mechanism, each sub-transmission path is monitored in real time, collecting load monitoring data such as transmission rate, latency, and packet loss rate. A weighted summation of the load monitoring data for each sub-transmission path is performed to calculate a status value for each sub-transmission path. The status value of each sub-transmission path is compared with a preset benchmark value to determine whether it exceeds the threshold range of the benchmark value. If the status value exceeds the threshold range of the benchmark value, the optimization level for that sub-transmission path is determined to be high; if the status value is close to the threshold range of the benchmark value, the optimization level is determined to be medium; if the status value is within the threshold range of the benchmark value, the optimization level is determined to be low. Based on the optimization level, a corresponding adjustment strategy is generated: a high optimization level corresponds to an emergency adjustment strategy, a medium optimization level corresponds to a focus strategy, and a low optimization level corresponds to a good status strategy. For sub-transmission paths with a high optimization level, the path repartitioning process is immediately triggered to reselect the optimal communication channel. For sub-transmission paths with a medium optimization level, the load carrying capacity and current status of each path are calculated based on historical channel assessment values ​​and real-time test results, and the optimal offloading strategy is formulated. Execute adjustment strategies to smoothly offload data traffic on sub-transmission paths with high load or degraded quality to other available paths, ensuring the stability and reliability of data transmission.

[0045] In this embodiment, several basic data packets are generated based on the characteristics of the original transmission data and the real-time channel conditions; at the same time, the load of each sub-transmission path is monitored in real time, and an unloading mechanism is set to adjust the transmission plan; data splitting and unloading are fully integrated to solve the problem of unreasonable transmission plan, which leads to unstable transmission and low transmission efficiency.

[0046] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0047] This application achieves the effect of improving data transmission efficiency and stability by reasonably cutting the original transmission data, generating a transmission plan based on the real-time channel conditions, and real-time monitoring and setting an unloading mechanism to dynamically optimize and adjust the transmission plan.

[0048] Embodiment 2: In embodiment 1, the transmission scheme is dynamically optimized and adjusted by cutting the original transmission data and setting an offload mechanism. However, during the cutting process, the fixed cutting method reduces the flexibility of data transmission and affects the transmission efficiency.

[0049] In some embodiments, the original transmission data is divided into several basic data packets, including: preliminary division according to different logical structures in the original transmission data to form initial data packets; obtaining corresponding processing values ​​based on the historical status value of each network node; and obtaining several basic data packets based on the initial data packets and the processing values ​​using a fine-grained packetization mechanism.

[0050] The processing value refers to the maximum amount of data that each network node can process in a data packet; specifically, the hardware configuration information of the network node is obtained, including the processor model, number of cores, and main frequency parameters. Based on the processor model and main frequency parameters, the theoretical processing speed of the network node is calculated to obtain the amount of data that can be processed per second. The cache capacity information of the network node is obtained, including the memory size and cache allocation strategy. Based on the cache capacity and allocation strategy, the maximum number of data packet caches that the network node can support is calculated. Combining the theoretical processing speed and the maximum number of caches, the maximum amount of data that the network node can process per unit time is calculated. Based on the maximum data volume and the limitations of the network transmission protocol, the upper limit of the size of a single data packet is determined. If the data packet size exceeds the upper limit, an adaptive packetization algorithm is used to decompose the original data into multiple data packets that meet the upper limit. A unique identifier is generated for each decomposed data packet for subsequent management and tracking. Based on the processing capacity of the network node and the upper limit of the data packet size, the parallel offloading mechanism is optimized to distribute data packets to multiple available paths.

[0051] The fine-grained packet subdivision mechanism is as follows: first matching and cutting is performed based on the initial data packet and the processing value, and the initial data packet that is not successfully matched is automatically cut and matched again until all the initial data packets are cut.

[0052] In some embodiments, the logical structure of the original transmitted data is analyzed to ensure the logical integrity of the data during the packetization process. The processing capabilities of network nodes, including processing speed and cache size, are assessed to determine the upper limit of the data packet size. The bandwidth characteristics of the transmission path, including transmission rate, latency, and packet loss rate, are monitored to adjust the data packet size in real time. A fine-grained packetization mechanism is established to dynamically adjust the data packet size based on real-time network conditions (such as path congestion and transmission rate stability). For example, if the path is congested, the data packet size is reduced to reduce transmission latency and packet loss rate; if the path is high-speed and stable, the data packet size is increased to improve transmission efficiency.

[0053] A fine-grained packetization mechanism is applied to accurately decompose the original transmission data into multiple data packets of appropriate size; each data packet is assigned a unique identifier for subsequent management and tracking; the optimal sub-transmission path and initial communication channel are selected based on the type, size and real-time channel conditions of the data packet; and a mapping relationship between data packets and transmission paths is established to ensure that each data packet can be transmitted through the optimal path.

[0054] The unloading mechanism includes: establishing an adaptive unloading model to adjust the current unloading rate in real time, setting a hierarchical unloading strategy, and determining the unloading order and unloading time according to the priority of the basic data packet; setting an allocation mechanism, and determining the unloading preference path according to the allocation mechanism; and readjusting the transmission plan based on the current unloading rate, unloading order, unloading time and unloading preference path.

[0055] The apportionment mechanism involves obtaining the radial paths of the sub-transmission path currently requiring offloading, and determining the offloading-favoring path based on the offloading rate and the state value of the radial path. The number of radial paths is greater than the number of apportionment paths. The radial paths are sub-transmission paths capable of offloading data, and the offloading-favoring path is the optimal path for offloading data.

[0056] Obtaining the radial paths of the sub-transmission path currently requiring offloading includes: establishing a network topology map based on all network nodes and sub-transmission paths; performing feasibility probing analysis on all sub-transmission paths based on the network topology map to obtain probing results; and obtaining all paths from the network nodes of the sub-transmission path currently requiring offloading based on the network topology map and the probing results, marking them as radial paths. The network topology map describes the connections and transmission relationships between all devices and sub-transmission paths. The feasibility probing analysis involves using a network probing tool to probe the sub-transmission paths, randomly selecting specific data for transmission testing. For example, using the ping command to test the reachability of a target device or the traceroute command to trace the path from the source to the destination, analyzing the probing results, and recording information such as the number of hops, latency, and bandwidth of each path for feasibility probing analysis. The network topology map and probing results are combined to analyze all possible paths from the same source. Paths are screened and ranked based on information such as the number of hops, latency, and bandwidth. Paths with better performance are prioritized as radial paths.

[0057] Determining the unloading preference path based on the unloading rate and the status value of the radial path includes: determining the number of unloading preference paths based on the unloading rate, sorting the status value of each radial path in descending order, and selecting radial paths as the unloading preference paths in order of the number of unloading preference paths. Different unloading rates correspond to different numbers of paths, which needs to be dynamically set and adjusted based on actual conditions. Alternatively, an automatic adaptive algorithm can be used to automatically select the number of paths based on the current amount of data to be unloaded and the unloading rate.

[0058] In some embodiments, the unloading speed is dynamically adjusted based on the real-time load status of the target path. For example, when the target path load is low, the unloading speed is increased to fully utilize bandwidth resources; when the target path load is high, the unloading speed is reduced to avoid causing new congestion.

[0059] Preferably, a hierarchical unloading strategy is set to set high priority for key data packets and time-sensitive content and unload them first; set low priority for ordinary data packets and flexibly arrange unloading time according to bandwidth resources.

[0060] In some embodiments, the real-time load status of the target path is obtained, and load-related indicator data is extracted. Based on the load indicator data, it is determined whether the load of the target path is lower than a preset threshold. If the load of the target path is lower than the preset threshold, an algorithm for increasing the unloading rate is used to calculate a new unloading rate. If the load of the target path is higher than the preset threshold, an algorithm for reducing the unloading rate is used to calculate a new unloading rate. Based on the load status of the target path and the calculated unloading rate, a dynamically adjusted unloading rate value is generated. The radiation path of the current system is obtained, and the paths whose load status meets the parallel unloading conditions are filtered out. Based on the availability of the filtered paths and the priority of the data packets, the unloading tasks are assigned to multiple paths. A parallel unloading mechanism is used to send data packets to multiple paths at the same time to execute the unloading tasks. The execution status of the unloading tasks is monitored, the unloading rate is updated in real time according to the changes in the path load, and the unloading strategy is adjusted.

[0061] In some embodiments, a parallel offloading mechanism is designed to distribute offloading pressure across multiple available paths simultaneously, improving offloading efficiency. A parallel offloading algorithm is implemented to allocate offloading tasks based on path availability and packet priority. During the offloading process, packets are encoded and compressed to reduce the actual amount of data transmitted. A comprehensive adjustment strategy is formulated based on the optimization level, offloading rate adaptation model, hierarchical offloading strategy, and parallel offloading mechanism. This adjustment strategy is implemented to ensure stable and reliable data transmission.

[0062] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0063] This application ensures the logical integrity of data through a fine-grained packet subpackaging mechanism, and dynamically adjusts the data packet size according to the real-time network conditions, thereby improving the flexibility and efficiency of data transmission; sets up an adaptive offloading model, a hierarchical offloading strategy, and a distribution mechanism, and dynamically adjusts and optimizes the transmission scheme according to the processing capacity of the network nodes and the real-time network conditions; and effectively disperses the offloading pressure and improves the offloading efficiency by dynamically adjusting the offloading speed and the parallel offloading mechanism.

[0064] Example 3: In the above embodiment, a comprehensive adjustment strategy is formulated based on the optimization level, unloading rate adaptive model, hierarchical unloading strategy and parallel unloading mechanism. However, when multiple sub-transmission paths need to be unloaded, automatic allocation cannot be achieved, resulting in unloading between multiple paths affecting data transmission efficiency.

[0065] Based on the load monitoring mechanism, the status value of each sub-transmission path is obtained, and the optimization level is obtained according to the status value and the pre-set benchmark value. The transmission plan is readjusted according to the optimization level and the unloading mechanism.

[0066] The method further includes: S310: marking a sub-transmission path having a state value greater than a reference value as a deviation path, marking a corresponding network node as a deviation node, determining the total number of deviation paths, and obtaining an optimization level according to a difference between the state value and the reference value;

[0067] S320: Obtain the real-time load and unloading resources of each deviation node, obtain the principle indicator set of the deviation path where the unloading resources overlap, obtain the corresponding scheduling value, determine the unloading order according to the scheduling value and the optimization level, and adjust the transmission plan according to the unloading order.

[0068] The principled indicator set includes a load balancing indicator, a resource availability indicator, and a time sensitivity indicator. The load balancing indicator refers to the load severity of the deviation path, that is, the deviation from the balanced load. If the load is heavy, priority is given to offloading. The resource availability indicator refers to the availability of offloading resources and the importance of the data to be offloaded. The availability of offloading resources refers to the scalability of offloading resources. If the offloading resource availability is low and the current data is more important, the resource availability indicator value is higher. The time sensitivity indicator refers to the time sensitivity of the offloaded data, such as real-time video or audio streams. The higher the time sensitivity, the higher the time sensitivity indicator value, and the corresponding scheduling value. A weight value is pre-set for each indicator, for example, 0.3, 0.3, and 0.4 respectively. Based on the real-time monitored data of each indicator, it is normalized to the same dimension and weighted summed to obtain the scheduling value. During the offloading process, the offloading effect is continuously evaluated, including changes in network load and transmission efficiency improvements. Based on feedback information, the sorting rules and algorithm parameters are dynamically adjusted to optimize the offloading process.

[0069] In this embodiment, through real-time comparison of status values ​​with benchmark values, deviation paths are automatically marked, manual intervention is reduced, and decision-making efficiency is improved; the principle indicator set and scheduling value calculation are used to intelligently adjust the unloading order, set a parallel unloading mechanism, avoid multi-path resource conflicts, improve overall throughput, give priority to high-load paths, reduce local congestion risks, and reduce delays and packet loss; realize automatic allocation of unloading of multiple sub-transmission paths, and maximize transmission efficiency through dynamic priority scheduling and parallel control.

[0070] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0071] This application automatically marks deviation paths through real-time comparison of status values ​​with benchmark values, intelligently adjusts the unloading order, sets a parallel unloading mechanism, avoids multi-path resource conflicts, realizes automatic allocation of multi-sub transmission path unloading, and maximizes transmission efficiency through dynamic priority scheduling and parallel control.

[0072] Example 4: This example makes further improvements based on the above content.

[0073] The method further includes: S400: connecting all deviation nodes to form a detection node line; when the detection node line detects a deviation node, dynamically adjusting the decomposition granularity of the original transmission data to form an offloading path combination; defining a path combination evaluation index, forming a priority queue based on the path combination evaluation index result; and determining an offloading order based on the priority queue;

[0074] The path combination evaluation metrics include: complementarity between paths, transmission efficiency after path combination, and load balancing after combination. Priority queues refer to: Complementarity refers to differences in bandwidth, latency, packet loss rate, and other aspects between paths; greater differences indicate stronger complementarity. Offload path combination refers to the organic combination of offload-prone paths. The combination form is determined by the adjusted decomposition granularity of the original transmission data; smaller decomposition granularity results in more combinations.

[0075] S500: Obtain historical data offloading records, establish a load anomaly pattern library, dynamically update network node status data in real time, detect critical load values, and predict potential congested network nodes; based on potential congested network nodes, pre-set offloading resources and execute step S400.

[0076] In some embodiments, all deviation nodes are connected, where the deviation nodes in the historical data are obtained, and detection node line column data is generated. The detection node line column data is obtained to detect whether there are deviation nodes in the new network nodes. The number of deviation nodes is determined by the detection results, and it is determined whether the decomposition granularity of the original transmission data should be adjusted. Based on the adjusted decomposition granularity, the unloading path combination form is generated. The unloading path combination form is obtained, and the path combination evaluation index is defined. The priority queue is generated based on the calculation results of the path combination evaluation index. The unloading order is determined based on the priority queue sorting. The historical data unloading records are obtained and a load anomaly pattern library is established. The real-time network node status data is matched with the load anomaly pattern library to determine the potential congested network nodes.

[0077] Using the network topology, the deviant nodes are sequentially connected to form a line-column structure. Detection node line-column data is obtained to detect any deviant nodes. Anomaly detection algorithms, such as the Isolation Forest algorithm, are used with a threshold of 0.15 to identify outliers. The number of deviant nodes is determined based on the detection results. If the number of deviant nodes exceeds the threshold of 5, the granularity of the original transmitted data is adjusted from 100KB per packet to 50KB per packet. Based on the adjusted granularity, offload path combinations are generated, increasing the number of possible path combinations from 3 to 6. The offload path combinations are obtained and path combination evaluation metrics are defined, including path delay, bandwidth utilization, and node load balance, with weights of 0.4, 0.3, and 0.3, respectively. Based on the calculated path combination evaluation metrics, a priority queue is generated, for example, using a weighted scoring method, with the priority queues being Path A, Path B, and Path C. The offload order is determined based on the priority queue ranking, with Path A being the preferred choice for data offload. Obtain historical data offloading records and build a load anomaly pattern library. For example, use the K-means clustering algorithm to classify historical data into three categories: normal, mild anomaly, and severe anomaly. Use the load anomaly pattern library to match real-time network node status data to identify potentially congested network nodes. For example, if the match between real-time data and severe anomaly patterns exceeds 0.8, the node is identified as potentially congested.

[0078] In some embodiments, path combination evaluation metrics are defined, including path complementarity, transmission efficiency, and load balancing. A weighted comprehensive scoring method is used to determine the path combination evaluation metric results. Based on the path combination evaluation metric results, a priority scheduling algorithm is used to determine the priority queue, ensuring that paths with a score above 90 are prioritized. Based on the priority queues, a FIFO queue model is used to determine the offloading order, ensuring that high-priority paths are executed first.

[0079] The technical solutions in the above embodiments of the present application have at least the following technical effects or advantages:

[0080] This application improves the flexibility and efficiency of data offloading by dynamically adjusting the decomposition granularity of the original transmission data and forming an offloading path combination; by defining path combination evaluation indicators and forming priority queues, it ensures priority processing of high-priority paths and optimizes the utilization of network resources; by establishing a load anomaly pattern library and predicting potential congested network nodes, measures can be taken in advance to avoid the occurrence of network congestion, thereby improving the stability and reliability of the network.

[0081] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Various modifications and variations are readily apparent to those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A data communication method for power dual-mode, characterized in that: include: S100: Dividing all sub-transmission paths based on the preset transmission path and network nodes, obtaining target evaluation values ​​of two channels on each sub-transmission path according to the historical channel evaluation table, and selecting an initial communication channel for each sub-transmission path based on the target evaluation values; S200: Obtaining original transmission data, dividing the original transmission data into a number of basic data packets, selecting corresponding initial communication channels and sub-transmission paths according to the basic data packets, and forming a transmission plan; S300: Obtaining a status value of each sub-transmission path based on a load monitoring mechanism, obtaining an optimization level based on the status value and a preset benchmark value, and re-adjusting the transmission plan based on the optimization level and the offloading mechanism; The offloading mechanism includes: establishing an adaptive offloading model to adjust the current offloading rate in real time, setting a hierarchical offloading strategy to determine the offloading order and offloading time according to the priority of the basic data packets; setting an allocation mechanism to determine the offloading preference path according to the allocation mechanism; and re-adjusting the transmission plan based on the current offloading rate, offloading order, offloading time and offloading preference path; The apportionment mechanism is as follows: obtaining the radiation path of the sub-transmission path currently requiring offloading, and determining the offloading tendency path according to the offloading rate and the state value of the radiation path; the number of the radiation paths is greater than the number of the apportionment paths; A network topology is established based on all network nodes and sub-transmission paths. Feasibility detection and analysis of all sub-transmission paths is performed based on the network topology to obtain detection results. Based on the network topology and detection results, all paths starting from the network node of the sub-transmission path that currently needs to be offloaded are obtained and marked as radial paths. Determine the number of unloading tendency paths according to the unloading rate, sort the state values ​​of each radial path in descending order, and select the radial paths as unloading tendency paths in order of the number of unloading tendency paths; Step S300 further includes: S310: marking a sub-transmission path whose state value is greater than a reference value as a deviation path, marking the corresponding network node as a deviation node, determining the total number of deviation paths, and obtaining an optimization level according to the difference between the state value and the reference value; S320: Obtain the real-time load and unloading resources of each deviation node, obtain the principle indicator set of the deviation path where the unloading resources overlap, obtain the corresponding scheduling value, determine the unloading order according to the scheduling value and the optimization level, and adjust the transmission plan according to the unloading order.

2. A data communication method for power dual-mode according to claim 1, characterized in that: The original transmission data is divided into several basic data packets, including: preliminary division according to different logical structures in the original transmission data to form initial data packets; obtaining corresponding processing values ​​based on the historical status value of each network node; and obtaining several basic data packets based on the initial data packets and processing values ​​using a fine-grained packetization mechanism.

3. A data communication method for power dual-mode according to claim 2, characterized in that: The processing value refers to the maximum amount of data that each network node processes in a data packet; the fine-grained packet subdivision mechanism is: based on the initial data packet and the processing value, the initial data packet that is not successfully matched is automatically cut and matched again until all initial data packets are cut.

4. The data communication method for power dual-mode according to claim 1, characterized in that: The method further includes: S400: connecting all deviation nodes to form a detection node line array; when the detection node line array detects a deviation node, dynamically adjusting the decomposition granularity of the original transmission data to form an unloading path combination; defining a path combination evaluation index, and forming a priority queue based on the path combination evaluation index result; and determining the unloading order based on the priority queue.

5. The data communication method for power dual-mode according to claim 1, characterized in that: The method further includes: S500: obtaining historical data unloading records, establishing a load anomaly pattern library, dynamically updating network node status data in real time, detecting critical load values, and predicting potentially congested network nodes; pre-setting unloading resources based on potentially congested network nodes, and executing step S400.

6. A data communication method for power dual-mode according to claim 4, characterized in that: The path combination evaluation indicators include: complementarity between paths, transmission efficiency after path combination, and load balancing after combination.

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