A power distribution box state priority transmission method and system based on edge computing

Abstract

The application discloses an edge-computing-based power distribution box state priority transmission method and system, and relates to the technical field of power distribution box monitoring.The method comprises the following steps: obtaining multi-dimensional operation data of a target power distribution box and detecting a topology communication state; extracting electrical mutation features and environmental degradation features in the multi-dimensional operation data for cross comparison to obtain a cross-domain coupling risk value; determining a dynamic transmission priority based on the cross-domain coupling risk value; matching a target transmission channel according to the dynamic transmission priority and the topology communication state; broadcasting a bandwidth requisition frame to a neighboring edge computing node when the dynamic transmission priority satisfies a highest priority trigger condition and a direct uplink state is a disconnected state; receiving feedback channel release information and establishing a cascaded communication channel as the target transmission channel, and then transmitting the multi-dimensional operation data.The application avoids the stagnation of key early warning data in extreme situations such as local link disconnection, and improves the transmission timeliness of power distribution box state data.

Description

Technical Field

[0001] This invention relates to the field of distribution box monitoring technology, specifically to a distribution box status priority transmission method and system based on edge computing. Background Technology

[0002] With the rapid development of smart grid technology, edge computing nodes have become crucial hubs for monitoring the status of distribution boxes and transmitting data. The dimensions and types of monitoring data are constantly expanding, and systems can collect multi-dimensional operational data, including electrical and environmental data, through edge nodes. Distribution box status data serves as a vital basis for improving grid security and fault early warning capabilities; its accurate assessment and timely transmission have a significant impact on the stable operation of the power system.

[0003] Currently, the transmission method of distribution box status data mainly relies on fixed rules for classifying single data types. By identifying single data types such as routine telemetry or over-limit alarms, priorities and transmission queues are determined, and data is uploaded using the node's own direct communication link to meet the needs of status monitoring.

[0004] However, relying solely on fixed rules for classifying a single data type and its own direct connection links makes it difficult to accurately assess the true urgency of complex and dangerous situations. This results in critical early warning data being retained in extreme cases such as local link disconnection, thereby reducing the timeliness of power distribution box status data transmission. Summary of the Invention

[0005] To address the aforementioned shortcomings, a method and system for prioritizing the transmission of distribution box status based on edge computing is provided.

[0006] In a first aspect, the present invention provides a distribution box status priority transmission method based on edge computing, applied to edge computing nodes, the method comprising:

[0007] Acquire multidimensional operational data of the target distribution box and detect the topology communication status of the area where the edge computing node is located. The multidimensional operational data includes electrical data and environmental data, and the topology communication status includes the status of direct uplink and the status of available links of adjacent edge computing nodes.

[0008] Electrical mutation features are extracted from the electrical data and environmental degradation features from the environmental data. The electrical mutation features and environmental degradation features are cross-compared to obtain cross-domain coupling risk values.

[0009] Based on the cross-domain coupling risk value, the dynamic transmission priority of the multi-dimensional operational data is determined;

[0010] Based on the dynamic transmission priority and the topology communication state, a target transmission channel is matched for the multidimensional operational data;

[0011] When the dynamic transmission priority meets the preset triggering condition corresponding to the highest priority and the direct uplink is in a disconnected state, a bandwidth requisition frame is broadcast to the adjacent edge computing node.

[0012] The system receives channel handover information from adjacent edge computing nodes with dynamic transmission priorities lower than the preset highest priority, based on the bandwidth requisition frame, and establishes a cascaded communication channel according to the channel handover information, using the cascaded communication channel as the target transmission channel.

[0013] The multidimensional operational data is transmitted through the target transmission channel.

[0014] By employing the above technical solutions, multi-dimensional operational data of the target distribution box is acquired, and the topology communication status of the area where the edge computing node is located is detected. This provides a comprehensive understanding of the internal and external operating conditions of the distribution box and the distribution of surrounding network resources. Electrical mutation characteristics are extracted from electrical data, and environmental degradation characteristics are extracted from environmental data. Cross-comparison of these two data points yields a cross-domain coupling risk value, accurately quantifying the comprehensive danger level under the interaction of internal equipment anomalies and harsh external environments. This overcomes the deficiency of single data types in accurately assessing the true urgency of complex dangerous states. Based on the cross-domain coupling risk value, the dynamic transmission priority of multi-dimensional operational data is determined, giving priority to data reflecting true emergency dangerous states. Target transmission channels are matched to the multi-dimensional operational data according to the dynamic transmission priority and topology communication status, realizing data urgency assessment. The system rationally allocates available network resources; when the dynamic transmission priority meets the triggering condition corresponding to the preset highest priority and the direct uplink is disconnected, it broadcasts a bandwidth requisition frame to adjacent edge computing nodes, enabling proactive cross-node communication support in extreme emergencies where the local network is paralyzed; it receives channel relinquishment information from adjacent edge computing nodes with dynamic transmission priorities lower than the preset highest priority based on the bandwidth requisition frame, and establishes a cascaded communication channel as the target transmission channel based on the channel relinquishment information, prompting low-priority tasks to release communication resources to build an emergency transmission path; finally, it transmits multi-dimensional operational data through the target transmission channel, ensuring that critical early warning data can still be delivered in a timely manner in extreme situations such as local link disconnection, avoiding the retention of critical early warning data, and improving the timeliness of power distribution box status data transmission.

[0015] Secondly, an edge computing-based distribution box status priority transmission system, the system comprising:

[0016] The data acquisition and detection module is used to acquire multi-dimensional operational data of the target distribution box and detect the topology communication status of the area where the edge computing node is located. The multi-dimensional operational data includes electrical data and environmental data, and the topology communication status includes the status of direct uplink and the status of available links of adjacent edge computing nodes.

[0017] The feature extraction and comparison module is used to extract electrical mutation features from the electrical data and environmental degradation features from the environmental data, and to cross-compare the electrical mutation features and the environmental degradation features to obtain cross-domain coupling risk values.

[0018] The priority determination module is used to determine the dynamic transmission priority of the multidimensional operational data based on the cross-domain coupling risk value.

[0019] The channel matching module is used to match a target transmission channel for the multidimensional running data according to the dynamic transmission priority and the topology communication state;

[0020] The bandwidth requisition broadcast module is used to broadcast a bandwidth requisition frame to the adjacent edge computing node when the dynamic transmission priority meets the preset triggering condition corresponding to the highest priority and the direct uplink status is disconnected.

[0021] The cascaded channel establishment module is used to receive channel handover information fed back by adjacent edge computing nodes with dynamic transmission priority lower than the preset highest priority based on the bandwidth requisition frame, and to establish a cascaded communication channel according to the channel handover information, and to use the cascaded communication channel as the target transmission channel.

[0022] The data transmission module is used to transmit the multidimensional operational data through the target transmission channel.

[0023] Thirdly, the present invention provides an electronic device, including a memory and a processor;

[0024] The memory is used to store computer programs;

[0025] The processor is configured to implement the above-described edge computing-based distribution box status priority transmission method when executing the computer program.

[0026] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when read and run by a processor, implements the above-described edge computing-based distribution box status priority transmission method. Attached Figure Description

[0027] Figure 1A flowchart illustrating a distribution box status priority transmission method based on edge computing, provided for an embodiment of the present invention;

[0028] Figure 2 This is a schematic diagram illustrating the principle of cross-domain coupling risk assessment and priority determination provided in an embodiment of the present invention;

[0029] Figure 3 This is a schematic diagram illustrating a scenario of bandwidth requisition and cascaded communication establishment under extreme operating conditions provided by an embodiment of the present invention.

[0030] Figure 4 This is a structural block diagram of a distribution box status priority transmission system based on edge computing, provided for an embodiment of the present invention. Detailed Implementation

[0031] The principles and features of the present invention are described below with reference to the accompanying drawings. The examples given are only for explaining the present invention and are not intended to limit the scope of the present invention.

[0032] Example 1

[0033] like Figure 1 As shown, a distribution box status priority transmission method based on edge computing is applied to edge computing nodes. The method includes:

[0034] Acquire multi-dimensional operational data of the target distribution box and detect the topology communication status of the area where the edge computing node is located. The multi-dimensional operational data includes electrical data and environmental data, and the topology communication status includes the status of the direct uplink and the status of the available links of adjacent edge computing nodes.

[0035] Electrical mutation features are extracted from electrical data and environmental degradation features from environmental data. The electrical mutation features and environmental degradation features are cross-compared to obtain cross-domain coupling risk values.

[0036] Based on cross-domain coupling risk values, the dynamic transmission priority of multi-dimensional operational data is determined;

[0037] Match the target transmission channel for multi-dimensional operational data based on dynamic transmission priority and topology communication status;

[0038] When the dynamic transmission priority meets the preset triggering condition corresponding to the highest priority and the direct uplink is in the disconnected state, a bandwidth requisition frame is broadcast to the adjacent edge computing node.

[0039] Receive channel handover information from adjacent edge computing nodes with dynamic transmission priority lower than the preset highest priority based on bandwidth requisition frames, and establish a cascaded communication channel based on the channel handover information, and use the cascaded communication channel as the target transmission channel.

[0040] Multidimensional operational data is transmitted through the target transmission channel.

[0041] Specifically, electronic devices are deployed as edge computing nodes at the target distribution box. During system operation, the system first acquires multi-dimensional operational data of the target distribution box and simultaneously detects the topology communication status of the area where the edge computing node is located. The multi-dimensional operational data comprehensively covers electrical data reflecting the electrical working condition of the equipment and environmental data reflecting the external environment, such as real-time fluctuations in current and voltage and temperature and humidity data around the box. At the same time, the topology communication status includes not only the direct uplink status of the current node's connection to the cloud master station, but also the available link status of neighboring edge computing nodes, so that the system can fully grasp the distribution of local and surrounding communication resources.

[0042] After acquiring the aforementioned basic data, the system further extracts electrical mutation features from electrical data and environmental degradation features from environmental data. Then, it cross-compares the electrical mutation features and environmental degradation features to obtain cross-domain coupling risk values. For example, when an abnormal current mutation occurs inside the distribution box and the external ambient temperature rises sharply, the cross-domain coupling risk value obtained from the cross-compare will increase significantly, thereby accurately quantifying the real degree of danger brought about by the superposition of internal and external factors. Subsequently, based on the cross-domain coupling risk value, the dynamic transmission priority of multi-dimensional operational data is determined, so that emergency warning data with higher risk values ​​can be assigned higher priority. And according to the dynamic transmission priority and topology communication status, the target transmission channel is matched for multi-dimensional operational data, thereby realizing the reasonable scheduling and preliminary mapping of data urgency and available communication resources.

[0043] When the assessment finds that the dynamic transmission priority meets the preset triggering condition corresponding to the highest priority and the direct uplink is disconnected, it means that the current distribution box is facing an extreme emergency and the local network has been paralyzed. At this time, the system will actively broadcast a bandwidth requisition frame to adjacent edge computing nodes to seek communication support across nodes. To achieve distributed collaborative arbitration, the system stipulates in the underlying communication protocol that the highest priority identifier of the current multidimensional running data must be forcibly encapsulated in the frame header control field of the bandwidth requisition frame. Then, it receives channel relinquishment information from adjacent edge computing nodes whose dynamic transmission priority is lower than the preset highest priority based on the bandwidth requisition frame. Specifically, the underlying execution logic of this step is as follows: after listening to the broadcast frame, the surrounding adjacent nodes trigger their local priority preemption assessment mechanism, parse out the highest priority identifier and compare it with the task priority of their current pending queue; only when the adjacent node determines that its own task priority is lower than the highest priority will it trigger a local suspension command, actively release the communication frequency band resources it occupies, and unicast a channel relinquishment information back to the initiating node. After receiving the information, the initiating node establishes a cascaded communication channel based on the channel handover information, uses the cascaded communication channel as the target transmission channel, and finally transmits the multi-dimensional operation data through the target transmission channel. This ensures that even under extreme conditions of local link interruption, extremely urgent power distribution box status warning data can still be delivered in a timely manner through the handover links of surrounding nodes.

[0044] Example 2

[0045] As a preferred embodiment of the present invention, based on Example 1, electrical mutation characteristics and environmental degradation characteristics are cross-compared to obtain a cross-domain coupling risk value, including:

[0046] The transient abrupt change gradient of electrical parameters in the electrical abrupt change characteristics is calculated based on the electrical abrupt change characteristics, and the trend deterioration slope of environmental parameters in the environmental deterioration characteristics is calculated based on the environmental deterioration characteristics.

[0047] The transient mutation gradient and the trend deterioration slope are mapped by matrix to obtain the environmental sensitivity weight;

[0048] The transient mutation gradient is weighted and corrected using environmental sensitivity weights to generate a corrected electrical risk base.

[0049] The corrected electrical risk baseline is compared with the preset risk assessment baseline to output the cross-domain coupling risk value.

[0050] Specifically, the electronic device first calculates the rate of change of electrical parameters per unit time based on the extracted electrical abrupt change characteristics to obtain the transient abrupt change gradient, and then calculates the rate of continuous deterioration of environmental parameters within a set time window based on environmental degradation characteristics to obtain the trend degradation slope. For example, when the current inside the distribution box fluctuates abnormally and the external ambient temperature continues to rise, the instantaneous rise gradient of the current and the continuous rise slope of the temperature are calculated respectively. Then, the transient abrupt change gradient and the trend degradation slope obtained above are input into a pre-constructed mapping matrix for matrix mapping. Specifically, a two-dimensional sensitivity mapping matrix is ​​pre-constructed. row index The column index corresponds to the quantification range of the trend deterioration slope (e.g., the temperature rise slope is divided into three ranges: gentle, moderate, and sharp). For the quantization interval corresponding to the transient gradient change, the values ​​of the matrix elements are the preset amplification coefficients. Based on the currently calculated slope and gradient values, the system looks up the corresponding row and column indices in the matrix and extracts the corresponding matrix element values ​​as environmental sensitivity weights to quantify the degree of environmental impact.

[0051] The transient mutation gradient is then weighted and corrected using the obtained environmental sensitivity weights, i.e., by multiplying the transient mutation gradient by the environmental sensitivity weights (e.g., the corrected electrical risk base). ,in For transient abrupt gradients, The environmental sensitivity weights are obtained by looking up a table, which integrates the deterioration factors of the external environment into the abrupt change assessment of electrical parameters, generating a corrected electrical risk base that can truly reflect the overall risk level.

[0052] Finally, the corrected electrical risk baseline is compared with the pre-set risk assessment baseline representing different risk levels. Based on the comparison results, the current risk level is determined and the final cross-domain coupling risk value is output. Through the above process, the comprehensive risk level under the interaction of internal equipment failure and external harsh environment is accurately quantified, providing reliable data support for the subsequent determination of dynamic transmission priority.

[0053] Combination Figure 2As shown in the diagram, this invention provides a schematic diagram of the principle of cross-domain coupling risk assessment and priority determination. As can be seen from the diagram, the system does not process data in isolation, but rather constructs a dual-track cross-assessment model. The left track extracts the transient gradient of electrical data (such as current and voltage), while the right track extracts the trend deterioration slope of environmental data (such as temperature and humidity). Both converge in the core sensitivity mapping matrix. Environmental sensitivity weights are obtained through matrix lookup, and then the electrical risks are weighted and corrected. Finally, the cross-domain coupling risk value is output and mapped to a dynamic transmission priority queue. This non-linear cross-assessment architecture effectively avoids false alarms or false negatives caused by a single threshold judgment, ensuring the accuracy of the assessment results.

[0054] Example 3

[0055] As a preferred embodiment of the present invention, based on Example 1, detecting the topology communication status of the area where the edge computing node is located includes:

[0056] Send topology probe messages to adjacent edge computing nodes within the region;

[0057] Receive link status response messages returned by adjacent edge computing nodes, and extract the channel margin and forwarding delay of adjacent edge computing nodes;

[0058] The link availability score of adjacent edge computing nodes is calculated based on channel margin and forwarding delay;

[0059] The links of adjacent edge computing nodes whose link availability scores are greater than a preset score threshold are marked as available links.

[0060] Specifically, the electronic device first broadcasts or unicasts topology probe messages to each adjacent edge computing node in its area via a wireless communication interface to actively perceive the distribution of surrounding network resources. It then waits for and receives link status response messages from these adjacent edge computing nodes after receiving the probe request, and extracts channel margin reflecting the node's current communication load and forwarding delay reflecting data transmission efficiency from these messages. For example, when an adjacent node has a large remaining bandwidth and a small amount of data waiting to be sent, its extracted channel margin is high and its forwarding delay is low. Then, considering both the extracted channel margin and forwarding delay, a preset weighted evaluation algorithm is used to calculate the link availability score of that adjacent edge computing node. The specific calculation formula is as follows:

[0061]

[0062] Where S is the link availability score, and C is the extracted channel margin. Let D be the maximum theoretical bandwidth of the channel, and D be the extracted forwarding delay. The maximum tolerable delay threshold is defined by α and β, which are preset positive and negative weighting coefficients, respectively (e.g., α=0.6, β=0.4). Therefore, channel margin is positively correlated with the score, while forwarding delay is negatively correlated with the score.

[0063] After obtaining the scores of each neighboring node, the calculated link availability score is compared one by one with the preset score threshold representing the qualified standard of communication quality. The neighboring edge computing nodes with link availability scores greater than the preset score threshold are selected and their corresponding communication links are marked as available links. In this way, inferior links that are congested or have severe signal attenuation are eliminated, thereby accurately identifying high-quality neighboring nodes with forwarding assistance capabilities in the current area. This provides reliable alternative routing resources for quickly establishing cascaded communication channels in emergency situations such as the disconnection of local direct links.

[0064] Example 4

[0065] As a preferred embodiment of the present invention, based on Embodiment 1, a bandwidth requisition frame is broadcast to adjacent edge computing nodes, including:

[0066] Obtain the spatial coordinates of the edge computing node in its local area;

[0067] Calculate the spatial cascading distance based on the spatial location coordinates and the preset cloud access point location;

[0068] The maximum number of forwarding hops for bandwidth-requisitioned frames is determined based on spatial concatenation distance;

[0069] Extract the data volume identifier of the multidimensional operational data, encapsulate the maximum forwarding hop count, dynamic transmission priority, and the data volume identifier of the multidimensional operational data into a bandwidth requisition frame, and broadcast it to adjacent edge computing nodes.

[0070] Specifically, the electronic device first obtains the spatial coordinates of the edge computing node within its current area through its built-in positioning module or node deployment configuration information. Then, it extracts the pre-set cloud access point location and uses a spatial geometric distance algorithm to calculate the physical span or topological path length between the obtained spatial coordinates and the pre-set cloud access point location, thus obtaining an accurate spatial concatenation distance. For example, when the edge computing node is deployed in a remote area and far from the cloud access point, the calculated spatial concatenation distance is relatively large. Then, based on this spatial concatenation distance, a pre-set distance-hop count mapping relationship is used to determine the maximum number of hops that a bandwidth-requisitioned frame is allowed to be relayed in the network. This ensures that data can successfully reach the cloud while effectively preventing network broadcast storms caused by unlimited forwarding.

[0071] After determining the maximum forwarding hop count, the multi-dimensional operational data that needs to be transmitted urgently is parsed to extract the data volume identifier representing its size. The determined maximum forwarding hop count, the previously evaluated dynamic transmission priority, and the data volume identifier of the multi-dimensional operational data are then uniformly encapsulated into a bandwidth requisition frame according to a preset underlying communication protocol format. Finally, the bandwidth requisition frame is broadcast to adjacent edge computing nodes within the communication coverage area through the wireless communication interface. This allows the adjacent nodes that receive the frame to quickly assess whether they have the ability to relinquish the channel and assist in forwarding based on the priority and data volume information carried in the frame. In this way, the cross-node communication resource requisition process can be efficiently initiated in the extreme case of local direct link disconnection.

[0072] Example 5

[0073] As a preferred embodiment of the present invention, based on Embodiment 1, channel handover information fed back by adjacent edge computing nodes with dynamic transmission priorities lower than the preset highest priority based on bandwidth requisition frames is received, and a cascaded communication channel is established according to the channel handover information, using the cascaded communication channel as the target transmission channel, including:

[0074] The channel handover confirmation message received by the neighboring edge computing node based on the bandwidth requisition frame is used as channel handover information. The channel handover confirmation message is generated by the neighboring edge computing node after it determines that its own dynamic transmission priority is lower than the preset highest priority and suspends the local transmission task.

[0075] Parse the channel handover confirmation message and extract the communication frequency band information released by adjacent edge computing nodes;

[0076] Establish cascaded communication channels based on the released communication frequency band information;

[0077] Configure the cascaded communication channel as the target transmission channel for multidimensional operational data.

[0078] Specifically, the electronic device first enters a listening state to receive channel relinquishment confirmation messages from neighboring edge computing nodes based on previously broadcast bandwidth requisition frames. This confirmation message is directly used as channel relinquishment information. These confirmation messages are generated by neighboring edge computing nodes after receiving a broadcast request, internally comparing and determining that the dynamic transmission priority of their current data to be sent is lower than the preset highest priority. Consequently, they proactively suspend their local transmission tasks to free up network resources. For example, when a neighboring node is preparing to send regular periodic status monitoring packets, if it detects that the received requisition frame has the highest priority, it will pause the transmission of regular packets and reply with a confirmation message to the initiator. Subsequently, it performs protocol parsing on the received channel relinquishment confirmation message to accurately extract the communication frequency band information proactively released by the neighboring edge computing node in response to an emergency transmission.

[0079] After successfully extracting the aforementioned frequency band parameters, the local wireless radio frequency transceiver frequency and channel parameters are adjusted according to the released communication frequency band information, thereby establishing a stable and dedicated cascaded communication channel with the adjacent edge computing node. The successfully established cascaded communication channel is then configured as the target transmission channel for the multi-dimensional operational data that urgently needs to be sent. In the extreme predicament of a disconnected local direct uplink, this cleverly utilizes the available communication resources of neighboring nodes processing low-priority tasks to quickly establish an emergency relay transmission path to the cloud master station. This ensures that high-priority warning data generated by the distribution box in complex and dangerous situations can be safely and promptly relayed, effectively preventing the retention of critical data.

[0080] Combination Figure 3 As shown, this invention provides a schematic diagram of a bandwidth requisition and cascaded communication establishment scenario under extreme operating conditions. Figure 3 As shown, when the edge computing node (central node) where the target distribution box is located experiences a direct uplink disconnection (the dashed line crossed out in the diagram) and is at the highest risk priority, the node broadcasts a bandwidth requisition frame. Upon receiving this frame, neighboring nodes within the communication coverage area trigger an internal priority arbitration mechanism. The diagram shows two adjacent nodes: node A, handling a low-priority task, actively suspends its local task and releases its frequency band, establishing a cascaded communication channel with the central node (solid line); while node B, possibly handling an equally high-priority task, does not relinquish its bandwidth. Through this distributed resource preemption and requisition mechanism, an emergency lifeline to the cloud is dynamically reconstructed in the physically damaged network topology.

[0081] Example 6

[0082] As a preferred embodiment of the present invention, based on Embodiment 1, multidimensional operational data is transmitted through a target transmission channel, including:

[0083] When the target transmission channel contains multiple cascaded communication channels, the multidimensional operational data is redundantly encoded to generate multiple redundant data fragments.

[0084] Assign a corresponding cascaded communication channel to each piece of redundant data;

[0085] Multiple redundant data fragments are sent concurrently through multiple cascaded communication channels;

[0086] Monitor the transmission acknowledgment receipts of redundant data fragments and trigger a retransmission mechanism if no acknowledgment receipt is received.

[0087] Specifically, when the electronic device determines that the target transmission channel being constructed contains multiple cascaded communication channels, it first uses algorithms such as forward error correction to redundantly encode the multi-dimensional operational data that urgently needs to be transmitted. This process splits and expands the original complete data into multiple redundant data fragments. For example, when three adjacent nodes have relinquished channel resources to establish three cascaded paths, the system encodes and divides an urgent cross-domain coupling risk alarm data into three redundant data fragments with verification information. Then, based on the bandwidth capacity and current load characteristics of each cascaded communication channel, the system rationally allocates the corresponding cascaded communication channel to each redundant data fragment to ensure that the fragment size matches the channel transmission capacity.

[0088] Subsequently, the underlying communication transceiver module concurrently sends the aforementioned redundant data fragments through multiple cascaded communication channels. This utilizes the spatial diversity characteristics of multiple physical paths to resist signal fading and sudden interference during wireless transmission. Simultaneously with data transmission, the system starts an internal timer and continuously monitors the transmission acknowledgment returned by the receiver for each redundant data fragment. If no acknowledgment is received within the set timeout window, it is determined that the fragment has been lost or damaged in the corresponding transmission path. A retransmission mechanism is then immediately triggered for the lost fragment. This combination of multi-path concurrency and redundant retransmission significantly improves the reliability and resilience of high-priority early warning data transmission in extreme environments, ensuring that critical status information from the distribution box reaches the cloud completely and accurately.

[0089] Example 7

[0090] As a preferred embodiment of the present invention, based on Embodiment 1, after matching the target transmission channel for the multidimensional operational data according to the dynamic transmission priority and topology communication state, it further includes:

[0091] When the dynamic transmission priority does not meet the triggering condition corresponding to the highest priority and the direct uplink is in a congested state, extract the periodic heartbeat feature from the multidimensional operation data.

[0092] The multidimensional operational data with periodic heartbeat characteristics is compressed using a preset spatial data compression algorithm to generate aggregated status messages.

[0093] Aggregated status messages are cached in the local storage queue of the edge computing node;

[0094] When the direct uplink status is detected to have returned to an idle state, the aggregated status message is sent in batches as the data to be transmitted on the target transmission channel.

[0095] Specifically, after matching the target transmission channel, if the electronic device determines that the dynamic transmission priority of the current multidimensional operational data does not meet the preset trigger condition corresponding to the highest priority, and detects that its direct uplink is in a congested state with data backlog, it will perform feature analysis on the current multidimensional operational data to extract the periodic heartbeat features. For example, when the distribution box is in a normal and stable operation phase, the conventional temperature and humidity telemetry data or equipment online status packets it generates are usually of low priority and highly repetitive in the time dimension. At this time, the system will accurately identify and extract these data with periodic heartbeat features, and then use a preset spatial data compression algorithm to reduce the dimensionality of the multidimensional operational data with periodic heartbeat features. Specifically, the system first compares the data packets in adjacent periods, extracts static fields that remain unchanged (such as device ID, location code) and slowly changing environmental parameters with a change amplitude below the preset dead zone threshold (such as stable room temperature data), and removes these redundant and repetitive fields; then, it retains only the core status bits that have exceeded the limit or reversed the state, and reassembles the retained status bits using a bitmap encoding format. During bitmap encoding, the system constructs a mask vector corresponding to the feature dimensions of the multi-dimensional running data. When a certain dimension of data undergoes a valid change, the corresponding position in the mask vector is set to 1; otherwise, it is set to 0. The final aggregated status message consists only of "mask vector + incremental value of the changed field". Through the above process of eliminating redundant and repetitive fields and background information with high spatiotemporal correlation, it is simplified to generate a smaller aggregated status message that contains core status information.

[0096] The generated aggregated status messages are then cached in the local storage queue of the edge computing node for queuing. This effectively releases valuable communication bandwidth resources during network congestion, preventing the forced transmission of low-priority routine data and further exacerbating network congestion. During caching, the system continuously monitors the load of directly connected network links. Once the system detects that the status of the directly connected uplink has returned from congestion to idle, it immediately triggers the release mechanism of the cache queue, sending the accumulated aggregated status messages in the local storage queue as data to be transmitted on the target transmission channel in batches. Through this peak-shaving transmission strategy combining congestion reduction caching and idle batch transmission, not only is the communication pressure on edge nodes greatly alleviated during peak network periods, but the overall network bandwidth utilization efficiency and the transmission throughput of routine data are also significantly improved, ensuring the integrity of the overall monitoring data of the distribution box.

[0097] Example 8

[0098] like Figure 4 As shown in the figure, an embodiment of the present invention provides a distribution box status priority transmission system based on edge computing. The system includes:

[0099] The data acquisition and detection module is used to acquire multi-dimensional operational data of the target distribution box and detect the topology communication status of the area where the edge computing node is located. The multi-dimensional operational data includes electrical data and environmental data, and the topology communication status includes the status of the direct uplink and the status of the available links of adjacent edge computing nodes.

[0100] The feature extraction and comparison module is used to extract electrical mutation features from electrical data and environmental degradation features from environmental data. The electrical mutation features and environmental degradation features are cross-compared to obtain cross-domain coupling risk values.

[0101] The priority determination module is used to determine the dynamic transmission priority of multi-dimensional operational data based on cross-domain coupling risk values.

[0102] The channel matching module is used to match the target transmission channel for multi-dimensional running data based on dynamic transmission priority and topology communication status.

[0103] The bandwidth requisition broadcast module is used to broadcast bandwidth requisition frames to adjacent edge computing nodes when the dynamic transmission priority meets the preset triggering condition corresponding to the highest priority and the direct uplink status is disconnected.

[0104] The cascaded channel establishment module is used to receive channel handover information fed back by adjacent edge computing nodes with dynamic transmission priority lower than the preset highest priority based on bandwidth requisition frames, and to establish a cascaded communication channel based on the channel handover information, and use the cascaded communication channel as the target transmission channel.

[0105] The data transmission module is used to transmit multidimensional operational data through the target transmission channel.

[0106] Example 9

[0107] An electronic device, including a memory and a processor;

[0108] Memory, used to store computer programs;

[0109] The processor is used to implement the above-described edge computing-based distribution box status priority transmission method when executing a computer program.

[0110] Example 10

[0111] A computer-readable storage medium storing a computer program, which, when read and run by a processor, implements the aforementioned edge computing-based distribution box status priority transmission method.

[0112] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for prioritizing the transmission of distribution box status based on edge computing, characterized in that, Applied to edge computing nodes, the method includes: Acquire multidimensional operational data of the target distribution box and detect the topology communication status of the area where the edge computing node is located. The multidimensional operational data includes electrical data and environmental data, and the topology communication status includes the status of direct uplink and the status of available links of adjacent edge computing nodes. Electrical mutation features are extracted from the electrical data and environmental degradation features from the environmental data. The electrical mutation features and environmental degradation features are cross-compared to obtain cross-domain coupling risk values. Based on the cross-domain coupling risk value, the dynamic transmission priority of the multi-dimensional operational data is determined; Based on the dynamic transmission priority and the topology communication state, a target transmission channel is matched for the multidimensional operational data; When the dynamic transmission priority meets the preset triggering condition corresponding to the highest priority and the direct uplink is in a disconnected state, a bandwidth requisition frame is broadcast to the adjacent edge computing node. The system receives channel handover information from adjacent edge computing nodes with dynamic transmission priorities lower than the preset highest priority, based on the bandwidth requisition frame, and establishes a cascaded communication channel according to the channel handover information, using the cascaded communication channel as the target transmission channel. The multidimensional operational data is transmitted through the target transmission channel.

2. The method for prioritizing the transmission of distribution box status based on edge computing as described in claim 1, characterized in that, The step of cross-comparing the electrical mutation characteristics with the environmental degradation characteristics to obtain a cross-domain coupling risk value includes: The transient abrupt change gradient of the electrical parameters in the electrical abrupt change characteristics is calculated based on the electrical abrupt change characteristics, and the trend deterioration slope of the environmental parameters in the environmental deterioration characteristics is calculated based on the environmental deterioration characteristics. The environmental sensitivity weights are obtained by performing a matrix mapping between the transient mutation gradient and the trend deterioration slope. The transient mutation gradient is weighted and corrected using the environmental sensitivity weights to generate a corrected electrical risk base. The corrected electrical risk baseline is compared with the preset risk assessment baseline, and the cross-domain coupling risk value is output.

3. The method for prioritizing the transmission of distribution box status based on edge computing as described in claim 1, characterized in that, The detection of the topology communication status of the area where the edge computing node is located includes: Send topology probe messages to adjacent edge computing nodes within the region; Receive the link status response message returned by the adjacent edge computing node, and extract the channel margin and forwarding delay of the adjacent edge computing node; Calculate the link availability score of the adjacent edge computing nodes based on the channel margin and the forwarding delay; The links of adjacent edge computing nodes whose link availability scores are greater than a preset score threshold are marked as available links.

4. The method for prioritizing the transmission of distribution box status based on edge computing as described in claim 1, characterized in that, The broadcasting of bandwidth requisition frames to the adjacent edge computing nodes includes: Obtain the spatial coordinates of the edge computing node in its location area; The spatial cascading distance is calculated based on the spatial location coordinates and the preset cloud access point location; The maximum number of forwarding hops for the bandwidth requisition frame is determined based on the spatial concatenation distance. Extract the data volume identifier of the multidimensional operation data, encapsulate the maximum forwarding hop count, the dynamic transmission priority, and the data volume identifier of the multidimensional operation data into the bandwidth requisition frame, and broadcast it to the adjacent edge computing nodes.

5. The edge computing-based distribution box status priority transmission method as described in claim 1, characterized in that, The process of receiving channel handover information from adjacent edge computing nodes with a dynamic transmission priority lower than the preset highest priority based on the bandwidth requisition frame, establishing a cascaded communication channel according to the channel handover information, and using the cascaded communication channel as the target transmission channel includes: The channel handover confirmation message fed back by the adjacent edge computing node based on the bandwidth requisition frame is received as the channel handover information. The channel handover confirmation message is generated by the adjacent edge computing node after determining that its own dynamic transmission priority is lower than the preset highest priority and suspending the local transmission task. Parse the channel handover confirmation message and extract the communication frequency band information released by the adjacent edge computing nodes; The cascaded communication channel is established based on the released communication frequency band information; Configure the cascaded communication channel as the target transmission channel for the multidimensional operational data.

6. The method for prioritizing the transmission of distribution box status based on edge computing as described in claim 1, characterized in that, The transmission of the multidimensional operational data through the target transmission channel includes: When the target transmission channel contains multiple cascaded communication channels, the multidimensional operational data is redundantly encoded to generate multiple redundant data fragments. Assign a corresponding cascaded communication channel to each of the aforementioned redundant data fragments; The multiple redundant data fragments are sent concurrently through multiple cascaded communication channels; Monitor the transmission acknowledgment receipts of the redundant data fragments, and trigger a retransmission mechanism if no acknowledgment receipt is received.

7. The method for prioritizing the transmission of distribution box status based on edge computing as described in claim 1, characterized in that, After matching the target transmission channel for the multidimensional operational data according to the dynamic transmission priority and the topology communication state, the method further includes: When the dynamic transmission priority does not meet the triggering condition corresponding to the preset highest priority, and the direct uplink status is congested, the periodic heartbeat feature in the multidimensional operation data is extracted. The multidimensional operational data with the periodic heartbeat characteristics is compressed using a preset spatial data compression algorithm to generate an aggregated status message. The aggregated status message is cached in the local storage queue of the edge computing node; When the direct uplink status is detected to have returned to an idle state, the aggregated status message is sent in batches as data to be transmitted on the target transmission channel.

8. A distribution box status priority transmission system based on edge computing, characterized in that, The system includes: The data acquisition and detection module is used to acquire multi-dimensional operational data of the target distribution box and detect the topology communication status of the area where the edge computing node is located. The multi-dimensional operational data includes electrical data and environmental data, and the topology communication status includes the status of direct uplink and the status of available links of adjacent edge computing nodes. The feature extraction and comparison module is used to extract electrical mutation features from the electrical data and environmental degradation features from the environmental data, and to cross-compare the electrical mutation features and the environmental degradation features to obtain cross-domain coupling risk values. The priority determination module is used to determine the dynamic transmission priority of the multidimensional operational data based on the cross-domain coupling risk value. The channel matching module is used to match a target transmission channel for the multidimensional running data according to the dynamic transmission priority and the topology communication state; The bandwidth requisition broadcast module is used to broadcast a bandwidth requisition frame to the adjacent edge computing node when the dynamic transmission priority meets the preset triggering condition corresponding to the highest priority and the direct uplink status is disconnected. The cascaded channel establishment module is used to receive channel handover information fed back by adjacent edge computing nodes with dynamic transmission priority lower than the preset highest priority based on the bandwidth requisition frame, and to establish a cascaded communication channel according to the channel handover information, and to use the cascaded communication channel as the target transmission channel. The data transmission module is used to transmit the multidimensional operational data through the target transmission channel.

9. An electronic device, characterized in that, Including memory and processor; The memory is used to store computer programs; The processor is configured to, when executing the computer program, implement the edge computing-based distribution box status priority transmission method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when read and run by a processor, implements the edge computing-based distribution box status priority transmission method as described in any one of claims 1-7.

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