Communication route optimization method, system and equipment suitable for power distribution network

Abstract

The invention relates to the technical field of wireless communication networks, in particular to a communication route optimization method, system and equipment suitable for a power distribution network, and the method comprises the steps: determining an abnormal node in power distribution network nodes according to the disconnection duration of the power distribution network nodes and the data deviation degree in the power distribution network nodes; determining the routing fault influence degree on the abnormal node by using the unresponded communication sequence in the node path of the abnormal node; determining the routing selection priority of the abnormal nodes by using the routing fault influence degree, and obtaining the optimal sequence of the nodes of the power distribution network; and determining a target routing connection in the power distribution network by using the optimal sequence of the nodes of the power distribution network. Based on the main technical means in the invention, better routing connection of the power distribution network nodes can be more accurately and efficiently selected, so that efficient communication of the power distribution network is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communication networks, and particularly relates to a communication routing optimization method, system and device applicable to a distribution network. Background Art

[0002] With the development of smart grids and the improvement of the automation level of power systems, optimizing the communication routing of distribution networks is of great significance in ensuring the safety and stability of power systems, improving maintenance efficiency, reducing maintenance costs, and enhancing power consumption safety. In a smart distribution network, real-time and reliable information acquisition is a key factor for stable power transmission. Wireless sensor networks, with their unique low power consumption, fast self-organization, and superior coordination, are considered to have broad application prospects in the fields of remote monitoring of power equipment, fault diagnosis, and wireless long-distance meter reading in smart distribution networks.

[0003] Due to the routing selection of existing distribution networks, which is usually based on the detection of network link node failures and the prediction of the communication status of the network according to changes in the network topology, and the dynamic decision of the routing path is realized. The wireless sensor network in the distribution network is different from other common wireless networks and has its own characteristics, especially the self-organization characteristic: the distribution and deployment of the network do not depend on any fixed network equipment, and nodes coordinate their monitoring and control behaviors through communication protocols and node algorithms. Nodes can quickly self-organize into a complete wireless network. The characteristics of self-organizing network nodes' autonomous movement and dynamic network formation in it are likely to cause frequent changes in the network topology, which may mask some node failure phenomena (such as intermittent disconnection being difficult to distinguish from normal movement), increasing the difficulty of real-time fault detection, especially having a greater impact on the routing ability of a single node, making it difficult to judge the fault condition, and thus affecting the accuracy and efficiency of communication routing selection. Summary of the Invention

[0004] In order to solve the technical problem that it is difficult to distinguish node failures from normal movement in the routing selection of existing distribution networks, resulting in low accuracy and efficiency of communication routing selection, the purpose of the present invention is to provide a communication routing optimization method, system and device applicable to a distribution network. The specific technical solutions adopted are as follows: The present invention provides a communication routing optimization method applicable to a distribution network, and the method includes: Determining abnormal nodes in the distribution network nodes by using the disconnection duration of the distribution network nodes and the degree of data deviation therein; Determining the influence degree of routing faults on the abnormal nodes by using the unresponsive communication sequences in the node paths of the abnormal nodes; Determining the routing selection priority of the abnormal nodes by using the influence degree of routing faults and obtaining the preferred order of the distribution network nodes; Determine the target route connection in the distribution network by using the preferred order of the nodes in the distribution network; Wherein, the unresponsive communication sequence represents the communication data time sequence when an abnormal node does not respond to an access request in its node path; the routing fault impact degree represents the communication impact degree of the abnormal node on its node path.

[0005] Further, the method for determining the abnormal nodes in the distribution network nodes by using the disconnection duration and data deviation degree of the distribution network nodes includes: Calculate the data abnormality degree of the distribution network nodes by using the disconnection duration and data deviation degree of the distribution network nodes; Compare the data abnormality degree with a preset abnormality threshold, and regard the distribution network nodes with the data abnormality degree greater than or equal to the preset abnormality threshold as abnormal nodes.

[0006] Further, the method for calculating the data abnormality degree of the distribution network nodes by using the disconnection duration and data deviation degree of the distribution network nodes includes: Determine the data mean value of the target data and the corresponding normal value range within a preset sampling period; Calculate the data deviation degree in the distribution network nodes by using the data mean value and the normal value range; Calculate the data abnormality degree of the distribution network nodes by using the disconnection duration and data deviation degree of the distribution network nodes.

[0007] Further, the method for determining the routing fault impact degree on the abnormal node by using the unresponsive communication sequence in the node path of the abnormal node includes: Determine the node path where communication data is transmitted with the abnormal node, and obtain the unresponsive communication sequence based on the communication data during the unresponsive process of the abnormal node on the node path; Determine the routing fault impact degree on the abnormal node by using the unresponsive communication sequence and path information in the node path.

[0008] Further, the method for determining the routing fault impact degree on the abnormal node by using the unresponsive communication sequence and path information in the node path includes: Use the unresponsive communication sequence in the node path to linearly fit to obtain the corresponding sequence slope; Determine the routing fault impact degree on the abnormal node by using the sequence slope and path information.

[0009] Further, the method for determining the routing fault impact degree on the abnormal node by using the sequence slope and path information includes: Determine the number of node paths and the length of the node paths in the path information; The impact degree of routing failure on an abnormal node is calculated by using the sequence slope, the number of node paths, and the length of node paths.

[0010] Further, determining the routing selection priority on the abnormal node by using the impact degree of routing failure includes: The routing selection priority on the abnormal node is determined by using the impact degree of routing failure of the abnormal node and its adjacent network respectively.

[0011] Further, determining the routing selection priority on the abnormal node by using the impact degree of routing failure of the abnormal node and its adjacent network respectively includes: Determine the first average value of the impact degree of routing failure and the second average value of the impact degree of routing failure of the adjacent network before and after the failure of the abnormal node; The routing selection priority on the abnormal node is calculated by using the impact degree of routing failure of the abnormal node, the first average value of the impact degree of routing failure, and the second average value of the impact degree of routing failure.

[0012] The present invention provides a communication routing optimization system applicable to a distribution network, which is used to implement the communication routing optimization method applicable to the distribution network described in any one of the above; the system includes: A node detection module, which is used to determine the abnormal nodes in the distribution network nodes by using the disconnection duration of the distribution network nodes and the data deviation degree therein; A fault analysis module, which is used to determine the impact degree of routing failure on the abnormal node by using the unresponsive communication sequence in the node path of the abnormal node; A preference analysis module, which is used to determine the routing selection priority of the abnormal node by using the impact degree of routing failure and obtain the preference order of the distribution network nodes; A connection module, which is used to determine the target routing connection in the distribution network by using the preference order of the distribution network nodes; Wherein, the unresponsive communication sequence represents the communication data time sequence when the abnormal node does not respond to the access request in its node path; the impact degree of routing failure represents the impact degree of the abnormal node on the communication in its node path.

[0013] The present invention also provides a communication routing optimization device applicable to a distribution network. The device includes a processor, a memory, and a communication routing optimization program applicable to the distribution network that can be executed by the processor and stored on the memory. Wherein, when the communication routing optimization program applicable to the distribution network is executed by the processor, the steps of the communication routing optimization method applicable to the distribution network described in any one of the above are realized.

[0014] The present invention has the following beneficial effects: The present invention first starts from multiple dimensions of analyzing the disconnection duration and data deviation degree of the nodes in the distribution network, accurately identifies the abnormal nodes among them, and then, based on the communication connection influence relationship between the abnormal nodes and the neighborhood nodes, considering the overall communication situation of the neighborhood network, accurately determines the influence degree of the routing failure of the abnormal nodes on the communication path. Finally, based on the influence degree of the routing failure, the routing selection priority of each abnormal node is determined, and the overall optimal order of the distribution network nodes is obtained according to different routing selection priorities, so as to be able to more accurately and efficiently select a better routing connection for the distribution network nodes, thereby realizing the efficient communication of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0016] Figure 1 It is a flowchart of the steps of a communication routing optimization method applicable to a distribution network provided by an embodiment of the present invention; Figure 2 It is a refined flowchart of step S1 in a communication routing optimization method applicable to a distribution network provided by an embodiment of the present invention; Figure 3 It is a refined flowchart of step S11 in a communication routing optimization method applicable to a distribution network provided by an embodiment of the present invention; Figure 4 It is a refined flowchart of step S2 in a communication routing optimization method applicable to a distribution network provided by an embodiment of the present invention; Figure 5 It is a schematic structural diagram of the hardware operating environment of a communication routing optimization device applicable to a distribution network involved in the embodiment solution of the present invention; Figure 6 It is a schematic framework diagram of a communication routing optimization system applicable to a distribution network involved in the embodiment solution of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] To further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following specifically describes, in conjunction with the accompanying drawings and preferred embodiments, a communication routing optimization method applicable to a distribution network according to the present invention, including its specific implementation manner, structure, features, and effects. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0019] The following specifically describes, in conjunction with the accompanying drawings, the specific solution of a communication routing optimization method applicable to a distribution network provided by the present invention.

[0020] Embodiment 1: For a communication routing optimization method applicable to a distribution network provided by the present invention, please refer to Figure 1 , which shows the flowchart of the steps of a communication routing optimization method applicable to a distribution network provided by an embodiment of the present invention.

[0021] The method includes: Step S1, determining abnormal nodes in the distribution network nodes by using the disconnection duration and data deviation degree of the distribution network nodes; In an intelligent distribution network, to monitor the key parameters of the power system, the following sensors and their installation methods are usually configured: Environmental sensors such as temperature, humidity, and air pressure are built into the distribution network nodes (abbreviated as nodes), and raw data is obtained through periodic sampling (such as once per second); Power parameters (such as voltage fluctuations and harmonic contents) are measured in real time through high-precision voltage / current transformers, and the sampling rate is set according to service requirements (at least 10 ms-level sampling is required for distribution automation); The node dynamically selects a communication protocol according to the network load: low-bandwidth data (such as environmental data) is transmitted through HPLC (High-Performance Line Communication, high-speed power line communication) power line carrier; high-real-time data (such as electrical fault signals) is switched to a 5G URLLC (Ultra-Reliable Low-Latency Communication) slice; Based on dynamic topology information (such as the neighbor node status table), the minimum-hop or lowest-latency path is selected, and the routing decision is calculated in real time by the edge computing gateway; After the placement of sensing elements (sensors) in the transmission nodes of the intelligent distribution network is completed, data during the operation of the electrical equipment in the transmission nodes of the intelligent distribution network can be collected and sensed in real time.

[0022] Due to the routing selection on the distribution network nodes, the first thing to ensure is the stable condition of the distribution network nodes. Especially for the nodes that have failed (abnormal nodes), the selection of other communicable routing nodes should be a routing optimization carried out on the premise of ensuring the stability of the communication route. And the wireless sensor network is distributed in a divergent manner in the monitoring area. The nodes have the same working process and it is a relatively balanced and peer-to-peer network. Each node only interacts and links with the neighboring nodes around itself. The wireless sensor network uses the cooperation between neighboring nodes for data communication and has strong adaptability. Therefore, for the perception of node conditions, it is necessary to analyze from multi-dimensional data such as electricity and environment, as well as changes in the distribution network topology structure between nodes.

[0023] Specifically, please refer to Figure 2 , the step S1 includes: Step S11, using the disconnection duration of the distribution network node and the degree of data deviation therein, calculate the data abnormality degree of the distribution network node; Please refer to Figure 3 , the step S11 specifically includes: Step S111, determine the data mean value of the target data and the normal value range corresponding to the target data within the preset sampling period; Step S112, using the data mean value and the normal value range, calculate the degree of data deviation in the distribution network node; Step S113, using the disconnection duration of the distribution network node and the degree of data deviation therein, calculate the data abnormality degree of the distribution network node.

[0024] The wireless distribution network adopts a self-organizing network architecture. Nodes such as smart meters and distributed power controllers need to dynamically adjust the communication path according to the network state, resulting in frequent topology reconstruction. The movement of nodes including mobile energy storage devices or changes in network load, such as the access / withdrawal of distributed photovoltaics, will trigger the routing request and path update of the routing protocol AODV (Ad-hoc On-Demand Distance Vector), which is similar to the disconnection behavior caused by node failures at the protocol layer; while the disconnection caused by actual node hardware device failures is more related to abnormal manifestations in different dimensions. For example, during the actual operation of many electrical devices in the nodes of the distribution network, due to the flow of current and voltage, some heat may be generated, and the abnormal changes in temperature and humidity will have corresponding associated conditions at the same time period; therefore, when the environmental conditions tend to be stable, it is more in line with the disconnection condition of the distribution network topology structure.

[0025] Analyze the multi-dimensional target data extracted from the data collected by various types of sensors installed in the distribution network, including data factors such as temperature, humidity, current, and voltage. The abnormal condition of this type of target data is represented by the degree to which the data mean within the preset sampling period deviates from the normal value range, that is, the data deviation degree of this target data at the distribution network node: ; Represents the data deviation degree, Represents the data mean of the target data within the preset sampling period, Represents the upper and lower limit values of the normal value range corresponding to this target data, which is the range limit value closest to the . Comparatively speaking, if the data mean is greater than the upper limit value, then Represents the upper limit value. If the data mean is less than the lower limit value, then Represents the lower limit value. Represents the normalization calculation.

[0026] For the on / off performance of the node path, it is represented by the disconnection duration of this node path within the preset sampling period , and the node path is the communication path connected to this node.

[0027] The th data abnormality degree of the th distribution network node within the th preset sampling period is: Among them, Represents the data abnormality degree of the th distribution network node within the th preset sampling period, Represents the data deviation degree, Represents the disconnection duration. Use the () function to perform direct proportional normalization on the value. If the ratio is larger, it means that the abnormal performance of this type of target data in the th sampling period is more obvious.

[0028] Step S12: Compare the data abnormality degree with the preset abnormality threshold, and regard the distribution network nodes with the data abnormality degree greater than or equal to the preset abnormality threshold as abnormal nodes.

[0029] Similarly, obtain the data abnormality degrees of all types of data within each sampling period, and use a preset abnormality threshold (such as 0.53, which can be adjusted according to the actual situation) to screen the nodes with different data abnormality degrees. Nodes greater than or equal to the preset abnormality threshold are considered abnormal nodes, and vice versa are considered normal nodes.

[0030] Step S2: Use the unresponsive communication sequence in the node path of the abnormal node to determine the impact degree of the routing failure on the abnormal node; In this embodiment, the unresponsive communication sequence represents the communication data time series when the abnormal node does not respond to the access request in its node path; the impact degree of the routing failure represents the impact degree of the abnormal node on the communication in its node path.

[0031] Due to the characteristics of autonomous movement and dynamic network formation of nodes in the ad hoc network, the network topology changes frequently, which will cover up some node failure phenomena, that is, the node failure occurs during the gap of network changes, resulting in the node failure being considered as a normal network structure relinking process.

[0032] Therefore, for a single node on the power distribution network, for all other nodes that have data transmission with it during the monitoring time (sampling period), there are changes in the transmission status in multiple sampling periods on all paths, that is, the probability of disconnection will show an increasing trend, and the corresponding routing failure status of this node will be more obvious.

[0033] Specifically, please refer to Figure 4 , and the step S2 includes: Step S21: Determine the node paths where communication data is transmitted with the abnormal node, and obtain the unresponsive communication sequence based on the communication data during the unresponsive process of the abnormal node on the node path; Obtain all the node paths where the th node has communication data transmission within all sampling periods, and extract the corresponding timestamps of all access requests that occur on its node path but the node does not respond, and arrange them in chronological order into a communication sequence, denoted as the unresponsive communication sequence of the th node on the th node path ; Step S22: Use the unresponsive communication sequence and path information in the node path to determine the impact degree of the routing failure on the abnormal node.

[0034] The step S22 specifically includes: Use the unresponsive communication sequence in the node path to linearly fit to obtain the corresponding sequence slope; Use the sequence slope and path information to determine the impact degree of the routing failure on the abnormal node.

[0035] Among them, the path information includes the number of node paths and the length of node paths. Using the sequence slope, the number of node paths, and the length of node paths, the influence degree of routing faults on abnormal nodes is calculated.

[0036] On the unresponsive communication sequences of different node communication paths should be the same manifestation associated with the fault manifestation, that is, the lengths of different communication sequences are different. Perform linear fitting on their respective communication sequences to obtain the sequence slope , and then obtain the influence degree of routing faults on the th node of the smart distribution network: Among them, represents the influence degree of routing faults on the th node of the smart distribution network; represents the th node, and represents the unresponsive communication sequence of the th node communication path of the linear fitting sequence slope , represents the number of node paths with communication data transmission to the th node during all sampling periods, represents the average value of the lengths of node paths with communication data transmission to the th node during all sampling periods;

[0037] Step S3: Use the influence degree of routing faults to determine the routing selection priority of abnormal nodes and obtain the preferred order of distribution network nodes; Step S4: Use the preferred order of distribution network nodes to determine the target routing connection in the distribution network.

[0038] According to the obtained routing fault influence performance, since the distribution and expansion of the network do not depend on any fixed network devices, nodes coordinate their respective monitoring and control behaviors through communication protocols and node algorithms. Nodes can quickly self-organize into a complete wireless network. Correspondingly, considering from the wireless communication structure of the distribution network, the self-organization feature will automatically allocate communication nodes to weaken the network communication impact caused by a single node failure. Therefore, the routing selection should be a path selection from integrity to stable communication.

[0039] Specifically, the step S3 includes: Use the influence degree of routing faults of abnormal nodes and their adjacent networks respectively to determine the routing selection priority of abnormal nodes.

[0040] More specifically: Determine the average value of the first routing fault impact degree and the average value of the second routing fault impact degree of the adjacent network before and after the abnormal node fails; Using the routing fault impact degree of the abnormal node, the average value of the first routing fault impact degree, and the average value of the second routing fault impact degree, calculate the routing selection priority on the abnormal node.

[0041] Regarding the routing fault impact performance (routing fault impact degree) of all distribution network routing nodes as the degree of structural impact analyzed from their slave nodes, the more consistent the routing fault impact performance of the corresponding node is with the structural changes under the self-organization characteristics analyzed as a whole, the stronger the necessity of the node as a stable node on the communication path.

[0042] In a single distribution network subnet, for any single distribution network node, including abnormal nodes, obtain the routing fault impact performance of the nodes directly associated with it.

[0043] When a certain node fails, its nearby nodes will spontaneously connect according to the operating mechanism. Then, the overall difference in the routing fault impact degree of the adjacent network of the abnormal node before and after the failure is expressed as the routing selection priority of the node : Among them, represents the routing selection priority of the th node of the intelligent distribution network, represents the routing fault impact degree of the th type of data on the th node of the intelligent distribution network at the th monitoring time point (preset sampling period), represents the average value of the routing fault impact degree of the adjacent network of the th node of the intelligent distribution network before the node fails (the average value of the first routing fault impact degree), represents the average value of the routing fault impact degree of the adjacent network of the th node of the intelligent distribution network after the node fails (the average value of the second routing fault impact degree), measures the overall difference in the routing fault impact degree of the adjacent network of the node before and after the failure. The smaller the difference, the more stable the path performance of the node is proved; Based on the routing selection priorities of all the obtained nodes (including abnormal nodes and normal nodes, where the priority value of normal nodes is 1, and the priority value of abnormal nodes calculated by the above formula is less than 1), take them as the node priorities, update the order of the adjacent nodes of the nodes, that is, the nodes update their local neighbor tables and routing tables, and regularly send small-scale link keep-alive messages (Keep-Alive packets) to confirm that the neighbor nodes are still active. If a node does not receive the Keep-Alive packet from a neighbor node for several consecutive periods (such as 3 times), it is determined that the neighbor has a fault or is offline, and the faulty node is removed from it. According to the sorting order, the routing nodes are preferably selected, thereby realizing the optimal selection of communication routes in the distribution network.

[0044] The present invention first starts from multiple dimensions of analyzing the disconnection duration and data deviation degree of distribution network nodes, accurately identifies the abnormal nodes among them, and then based on the communication connection influence relationship between the abnormal nodes and the neighborhood nodes, considering the overall communication situation of the neighborhood network, accurately determines the influence degree of the routing failure of the abnormal nodes on the communication path. Finally, based on the influence degree of the routing failure, the routing selection priority of each abnormal node is determined, and the overall optimal order of the distribution network nodes is obtained according to different routing selection priorities, so as to be able to more accurately and efficiently select a better routing connection of the distribution network nodes, thereby realizing the efficient communication of the distribution network.

[0045] Embodiment 2: The embodiment of the present invention also proposes a communication routing optimization device applicable to a distribution network. The communication routing optimization device applicable to a distribution network can be a data calculation and processing device such as a computer, a server, or a combination of multiple devices.

[0046] As Figure 5 shown, Figure 5 is a schematic structural diagram of the hardware operating environment of the communication routing optimization device applicable to the distribution network according to the embodiment of the present invention.

[0047] As Figure 5As shown in the figure, the communication routing optimization device applicable to the distribution network may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, and a communication bus 1002. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display and an input unit such as a control panel. Optionally, the user interface 1003 may further include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WIFI interface). The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001. The memory 1005, as a computer storage medium, may include a communication routing optimization program applicable to the distribution network.

[0048] Those skilled in the art can understand that Figure 5 the hardware structure shown in the figure does not constitute a limitation on the device, and it may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0049] Continuing to refer to Figure 5 , Figure 5 the memory 1005, as a computer-readable storage medium, may include an operating system, a user interface module, a network communication module, and a communication routing optimization program applicable to the distribution network.

[0050] In Figure 5 , the network communication module is mainly used to connect to the server and can communicate with the server for data. And the processor 1001 can call the communication routing optimization program stored in the memory 1005 and execute the steps in the above various embodiments.

[0051] Based on the above hardware structure of the communication routing optimization device applicable to the distribution network, various embodiments for implementing the communication routing optimization method of the present invention are realized.

[0052] In addition, the present invention also provides a communication routing optimization system applicable to the distribution network. Please refer to Figure 6 , the communication routing optimization system applicable to the distribution network includes: a node detection module A10, which is used to determine abnormal nodes in the distribution network nodes by using the disconnection duration of the distribution network nodes and the data deviation degree therein; a fault analysis module A20, which is used to determine the influence degree of the routing fault on the abnormal nodes by using the unresponsive communication sequences in the node paths of the abnormal nodes; The preferred analysis module A30 is used to determine the routing selection priority of abnormal nodes and obtain the preferred order of the nodes in the distribution network by using the influence degree of routing faults; The connection module A40 is used to determine the target routing connection in the distribution network by using the preferred order of the nodes in the distribution network; Wherein, the unresponsive communication sequence represents the communication data time sequence when the abnormal node does not respond to the access request in its node path; the influence degree of the routing fault represents the communication influence degree of the abnormal node in its node path.

[0053] The specific implementation manner of the communication routing optimization system applicable to the distribution network of the present invention is basically the same as that of the above-mentioned embodiments of the communication routing optimization method applicable to the distribution network, and will not be repeated here.

[0054] In addition, the present invention also provides a computer-readable storage medium. A communication routing optimization program applicable to the distribution network is stored on the computer-readable storage medium of the present invention. When the communication routing optimization program applicable to the distribution network is executed by a processor, the steps of the communication routing optimization method as described above are implemented.

[0055] Among them, the method implemented when the communication routing optimization program applicable to the distribution network is executed can refer to the various embodiments of the communication routing optimization method applicable to the distribution network of the present invention, and will not be repeated here.

[0056] It should be noted that: the above sequence of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0057] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from the reference embodiment.

[0058] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0059] The above are only the preferred embodiments of the present invention, and thus do not limit the protection scope of the present invention. Any equivalent structure / method transformation made under the inventive concept of the present invention by using the content of the specification and drawings of the present invention, or any direct / indirect application in the relevant technical fields is included in the protection scope of the present invention.

Claims

1. A communication routing optimization method applicable to a distribution network, characterized in that, The method includes: Determining abnormal nodes in the distribution network nodes by using the disconnection duration and data deviation degree of the distribution network nodes; Determining the influence degree of routing faults on the abnormal nodes by using the unresponsive communication sequences in the node paths of the abnormal nodes; Determining the routing selection priority of the abnormal nodes and obtaining the preferred order of the distribution network nodes by using the influence degree of routing faults; Determining the target routing connection in the distribution network by using the preferred order of the distribution network nodes; Wherein, the unresponsive communication sequence represents the communication data time sequence when the abnormal node does not respond to the access request in its node path; the influence degree of routing faults represents the influence degree of the abnormal node on the communication in its node path.

2. The communication routing optimization method applicable to a distribution network according to claim 1, wherein The step of determining abnormal nodes in the distribution network nodes by using the disconnection duration and data deviation degree of the distribution network nodes includes: Calculating the data abnormality degree of the distribution network nodes by using the disconnection duration and data deviation degree of the distribution network nodes; Comparing the data abnormality degree with a preset abnormality threshold, and taking the distribution network nodes with the data abnormality degree greater than or equal to the preset abnormality threshold as abnormal nodes.

3. The communication routing optimization method applicable to a distribution network according to claim 2, wherein The step of calculating the data abnormality degree of the distribution network nodes by using the disconnection duration and data deviation degree of the distribution network nodes includes: Determining the data mean value of the target data and the corresponding normal value range within a preset sampling period; Calculating the data deviation degree in the distribution network nodes by using the data mean value and the normal value range; Calculating the data abnormality degree of the distribution network nodes by using the disconnection duration and data deviation degree of the distribution network nodes.

4. The communication routing optimization method applicable to a distribution network according to claim 1, characterized in that The step of determining the influence degree of routing faults on the abnormal nodes by using the unresponsive communication sequences in the node paths of the abnormal nodes includes: Determining the node paths with communication data transmission to the abnormal nodes, and obtaining the unresponsive communication sequences based on the communication data during the non-response process of the abnormal nodes on the node paths; Determining the influence degree of routing faults on the abnormal nodes by using the unresponsive communication sequences and path information in the node paths.

5. The communication routing optimization method applicable to a distribution network according to claim 4, characterized in that The step of determining the influence degree of routing faults on the abnormal nodes by using the unresponsive communication sequences and path information in the node paths includes: Linearly fitting the unresponsive communication sequences in the node paths to obtain the corresponding sequence slope; Determining the influence degree of routing faults on the abnormal nodes by using the sequence slope and path information.

6. The communication routing optimization method applicable to a distribution network according to claim 5, wherein The step of determining the influence degree of routing faults on the abnormal nodes by using the sequence slope and path information includes: Determining the number of node paths and the length of node paths in the path information; Calculating the influence degree of routing faults on the abnormal nodes by using the sequence slope, the number of node paths and the length of node paths.

7. The communication routing optimization method applicable to a distribution network according to claim 1, characterized in that The step of determining the routing selection priority of the abnormal nodes by using the influence degree of routing faults includes: Determining the routing selection priority of the abnormal nodes by using the influence degree of routing faults of the abnormal nodes and their adjacent networks respectively.

8. The communication routing optimization method applicable to a distribution network according to claim 7, wherein The step of determining the routing selection priority of the abnormal nodes by using the influence degree of routing faults of the abnormal nodes and their adjacent networks respectively includes: Determining the first average value of the influence degree of routing faults and the second average value of the influence degree of routing faults of the adjacent networks before and after the failure of the abnormal nodes; The routing selection priority on the abnormal node is calculated by using the influence degree of the routing fault of the abnormal node, the average value of the first routing fault influence degree, and the average value of the second routing fault influence degree.

9. A communication routing optimization system applicable to a distribution network, characterized in that, The system is used to implement the communication routing optimization method applicable to the distribution network according to any one of claims 1 to 8; the system includes: A node detection module, configured to determine abnormal nodes in the distribution network nodes by using the disconnection duration of the distribution network nodes and the data deviation degree therein; A fault analysis module, configured to determine the influence degree of the routing fault on the abnormal node by using the unresponsive communication sequence in the node path of the abnormal node; A preference analysis module, configured to determine the routing selection priority of the abnormal node by using the influence degree of the routing fault and obtain the preference order of the distribution network nodes; A connection module, configured to determine the target routing connection in the distribution network by using the preference order of the distribution network nodes; Wherein, the unresponsive communication sequence represents the communication data time sequence when the abnormal node does not respond to the access request in its node path; the influence degree of the routing fault represents the influence degree of the abnormal node on the communication in its node path.

10. A communication routing optimization device applicable to a distribution network, characterized in that, The device includes a processor, a memory, and a communication routing optimization program applicable to the distribution network stored on the memory and executable by the processor. When the communication routing optimization program applicable to the distribution network is executed by the processor, the steps of the communication routing optimization method applicable to the distribution network according to any one of claims 1 to 8 are implemented.

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