Method for enhancing data transmission reliability of time-sensitive network

Abstract

The invention relates to a method for enhancing data transmission reliability of a time-sensitive network, and belongs to the technical field of industrial control. The method comprises the following steps: searching all alternative paths in a TSN network, and calculating a working path Pw based on path reliability; selectively deploying a frame replication and frame elimination node FN according to the node reliability; extracting an alternative redundant path set, and determining a redundant path combination Pr in the alternative redundant path set according to the redundancy; and outputting the combination FN of the frame copy node and the elimination node, and the optimal main redundant path combination P. The method comprises the following steps of: firstly, selectively deploying nodes with frame copying and eliminating functions by utilizing the thought of segment protection, and inclining protection resources to other paths while meeting the reliability requirement, so that the efficient utilization of the resources is realized; secondly, by considering the influence of link and node attributes on data delivery reliability, an optimized redundant path is extracted under the condition that the requirement of data redundancy is met, so that the reliability of data transmission is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of industrial control and relates to a method for enhancing the reliability of data transmission in a time-sensitive network. Background Art

[0002] Traditional Ethernet technology is based on the "best effort" transmission principle and lacks guarantees for low latency, low jitter, and high reliability. It is also unable to effectively implement traffic priority control, which are key elements for the successful operation of time-critical real-time applications.

[0003] The Time Sensitive Networking (TSN) standard provides deterministic communication based on traditional Ethernet technology. Its goal is to support real-time applications by adding time synchronization, traffic scheduling, queue management, and data redundancy functions to the existing Ethernet technology, and to provide deterministic services for critical business data, ensuring low latency, low jitter, and high reliability for critical data transmission.

[0004] The Frame replication and elimination for reliability (FRER) mechanism proposed by IEEE 802.1CB enhances the reliability of traditional Ethernet. This mechanism uses spatial redundancy to generate and encode sequence numbers for each data through the source node (Talker) or proxy node using the sequencing function (Seq), and then uses the stream splitting function (Split) to copy it to two or more non-intersecting redundant paths according to the redundancy level of the data. Then, the independent recovery function (Rec) is used at the convergence of the working path and the redundant path to discard the original data or redundant data that arrives later, and finally reaches the target node (Listener). The implementation of the FRER mechanism in the TSN network is as follows: Figure 1 shown.

[0005] Although the FRER mechanism uses spatial redundancy to achieve seamless redundancy of data transmission in the TSN network and improve the reliability of data transmission, the replication of frames and the elimination of redundant frames at the source and destination nodes will cause unnecessary bandwidth consumption; at the same time, in the path calculation link, the traditional FRER mechanism uses the shortest path algorithm to calculate the working path and redundant path without considering the link attributes. Summary of the invention

[0006] In view of this, an object of the present invention is to provide a method for enhancing the reliability of time-sensitive network data transmission.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] A method for enhancing the reliability of time-sensitive network data transmission, the method comprising the following steps:

[0009] S1. Search all alternative paths in the TSN network and calculate the working path P based on the path reliability. w ;

[0010] S2. Selectively deploy frame replication and frame elimination nodes FN according to node reliability;

[0011] S3, extracting a set of candidate redundant paths, and determining a redundant path combination P in the set of candidate redundant paths according to redundancy r ;

[0012] S4. Output the combination FN of the frame duplication node and the elimination node, and the optimal primary-redundant path combination P.

[0013] Further, in step S1, the following steps are included:

[0014] S11, using the backtracking method to search for all possible paths between the source and destination nodes as candidate paths, which includes:

[0015] S111, initialize the predecessor node array: for each node i in the TSN network topology, maintain a predecessor node array predecessor[], which is used to record the previous node of i on the path from the starting point s to the node i;

[0016] S112, path backtracking: starting from the destination node d, use the predecessor[] array to backtrack to the source node s; during the backtracking process, the visited nodes are pushed into the path stack pathStack in sequence;

[0017] S113, output path: pop up the nodes in pathStack in sequence to form a path from the starting point s to the destination node d; add the constructed path to the path set KP(s,d);

[0018] S12, calculating the probability of all link and node failure states that may cause the TSN data flow to be disconnected;

[0019] S13, define path reliability and link weight function, assign values ​​to all links through link weight function, and then calculate the optimal path according to path reliability, and use the optimal path as the working path P w .

[0020] Further, in step S12, all candidate paths between the source node s and the destination node d form a routing graph R = {V, E}, where E represents the link set in R and V represents the node set in P; both links and nodes have failure probabilities, and thus the failure conditions are divided into link failure, node failure, and simultaneous failure of nodes and links, and their probabilities are expressed as follows:

[0021] 1) Link failure probability: The failure probability PLR of link data transmission in the TSN network (i,j) Related to the status and attributes of the link:

[0022]

[0023] in, represents the consumed bandwidth of link (i, j), represents the total working capacity of link (i, j), q (i,j) represents the probability that link (i, j) works normally, α (i,j) represents the ratio of the bandwidth consumed by link (i, j) to the total working capacity of the link, p (i,j) represents the probability of link (i, j) failure;

[0024] 2) Node failure probability: The failure probability PLR of data transmission on the node in the TSN network i Related to the state and properties of the node, then:

[0025]

[0026] in, represents the consumed bandwidth of node i, represents the total working capacity of node i, q i represents the probability that node i works normally, β i represents the ratio of the cache consumed by node i to the total working capacity of the node, p i represents the probability of node i failure.

[0027] Further, in step S13, the following steps are included:

[0028] S131. Define path reliability: Path reliability is related to both link failure probability and node failure probability, as shown below:

[0029]

[0030] Among them, PLR k The failure probability of node k, PLR (i,j) is the failure probability of link (i, j);

[0031] S132, define link weight function: link weight W in routing graph R = {V, E} i,j The function is expressed as follows:

[0032]

[0033] The weighted sum of each link of path P in the path set KP(s,d) is:

[0034]

[0035] Where E(P) is all the nodes in the path P; r P is the reliability of path P, that is:

[0036]

[0037] When the sum of the selected path weights is smaller, the path reliability is higher;

[0038] After assigning values ​​to all links in the routing graph r = {V, E} according to the link weight function, the Dijkstra path algorithm based on reliability cost calculates an optimal path P1 from the source node s to the destination node d, and uses path P1 as the working path P w .

[0039] Further, in step S2, the following steps are specifically included:

[0040] S21. Calculate TSN working path P w The evaluation index of each node i, including node proximity PD i , node degree centrality DC i , Betweenness Centrality BC i , node failure probability Average link failure probability

[0041] S22, using the entropy weight method to determine the weights of the corresponding indicators affecting the frame replication node and the frame elimination node, and then determine the node reliability E i , and then evaluate E according to the node reliability i The nodes are sorted to obtain the nodes FN={r,e} as the frame replication and frame elimination nodes.

[0042] Further, in step S21, let the working path in TSN be P w , the node set on the working path is V w , then:

[0043] 1) For node proximity PD i: The degree of proximity between a node and the source node or the destination node; when calculating the frame replication node r, the node proximity between the node and the source node needs to be considered; when calculating the frame elimination node e, the node proximity between the node and the destination node is considered.

[0044]

[0045] Where d(i,s / d) is the shortest path length from node i to source node s or destination node d;

[0046] 2) For node degree centrality DC i : reflects the relationship between a node and surrounding nodes;

[0047]

[0048] Among them, γ ij represents the number of links between nodes i and j;

[0049] 3) For betweenness centrality BC i :Based on working path P w The centrality measure of node i is:

[0050]

[0051] Among them, g (s,t) represents the number of shortest paths from node i to node j, Represents the number of shortest paths from node s to node t that pass through node i;

[0052] 4) For the node failure probability Related to the state and properties of the node:

[0053]

[0054] Among them, β i represents the ratio of the cache consumed by node i to the total working capacity of the node, p i represents the probability of node i failing;

[0055] 5) For the average link failure probability The average PLR ​​of the links connected to node i:

[0056]

[0057] Where m is the number of links around node i, represents the failure probability of the link (i, j) connected to node i.

[0058] Furthermore, in step S22, firstly, the reliability indicators of several nodes are normalized:

[0059]

[0060] Among them, a ij is the original value of index k at node i, a i ′ j The normalized value of index j at node i;

[0061] Calculate the proportion p of the index value of the i-th node under the j-th index ij :

[0062]

[0063] Then calculate the evaluation input entropy e j and the entropy weight w of index j j :

[0064]

[0065] Finally, the reliability evaluation E of node i is obtained i for:

[0066]

[0067] According to the node reliability evaluation E i The nodes are sorted to obtain nodes FN = {r, e} as frames for replication and elimination.

[0068] Further, in step S3, a redundant path combination is determined from the candidate redundant path set D(s, d) according to the redundancy It includes the following steps:

[0069] S31, extracting a set of candidate redundant paths D(s, d): removing the working path P from the original routing graph P = {V, E} w All links of the routing graph R ′ =RE P , create a set of alternative redundant paths D(s,d), using the new routing graph R ′ Find all possible paths that contain the path segment (s, r) from the source node to the frame copy node and the path segment (e, d) from the frame elimination node to the destination node, then traverse all paths and check whether the current path intersects with any path in D(s, d) between the frame copy and elimination nodes. If they do not intersect, add the current path to the set D(s, d);

[0070] S32, according to the path redundancy N, calculate the reliability index R of the combination of N-1 redundant paths, and ′After assigning values ​​to all links using the link weight function, the N-1 optimal redundant path combinations are calculated based on the reliability index R.

[0071] Further, in step S32, the path reliability from the starting point s to the node i is first calculated.

[0072]

[0073] in, is the link weight between node u and node v, u is the predecessor node of v, and link (u, v) belongs to link (s, i); then the reliability index R of the combination of N-1 redundant paths is expressed as:

[0074]

[0075] in, represents the sum of the path reliability costs from the starting point to each node i;

[0076] Normalize the reliability index R:

[0077]

[0078] Among them, k represents the number of overlapping links, n represents the number of intersecting nodes, m represents the number of links between the intersecting nodes and the target nodes, and R is the TSN network transmission reliability index of N-1 paths;

[0079] In the new routing graph R ′ After assigning values ​​to all links according to the link weight function, the Dijkstra path algorithm based on reliability cost calculates N-1 optimal redundant path combinations according to different data redundancy N.

[0080] Further, in step S4, the combination of frame replication nodes and elimination nodes in TSN FN = {r, e} and the optimal primary and redundant path combination in the routing graph are output According to the combination of frame replication nodes and elimination nodes FN = {r, e} deployment scheme and the optimal primary and redundant path combination Perform data transmission.

[0081] The beneficial effects of the present invention are:

[0082] The present invention performs path selection and node deployment based on a reliability assessment model and a segmented protection strategy. It utilizes the idea of ​​segmented protection to selectively deploy nodes with frame replication and elimination functions. On the premise of ensuring that the reliability of some paths is met, it can tilt protection resources to the remaining paths, thereby achieving efficient resource utilization. And by considering the impact of link and node attributes on data delivery reliability and meeting the requirements of data redundancy, a set of optimized redundant paths that meet reliability requirements are selected. This avoids the problem of unreliable data transmission caused by path failures during data transmission. At the same time, the method has strong flexibility and scalability. When the network topology or data transmission requirements change, the method can quickly recalculate and adjust the path and node deployment plan to adapt to the new network environment.

[0083] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0084] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:

[0085] Figure 1 Schematic diagram of the implementation process of the traditional FRER mechanism in the TSN network;

[0086] Figure 2 Schematic diagram of link and node failure in TSN network;

[0087] Figure 3 This is a schematic diagram comparing the difference between end-to-end protection and segment protection;

[0088] Figure 4 It is a schematic diagram of possible path combinations when the redundancy N=3 under the embodiment;

[0089] Figure 5 It is a schematic diagram of possible path combinations when the redundancy N=4 under the embodiment. DETAILED DESCRIPTION

[0090] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0091] Among them, the drawings are only used for illustrative explanations, and they only represent schematic diagrams rather than actual pictures, and should not be understood as limitations on the present invention. In order to better illustrate the embodiments of the present invention, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of actual products. For those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0092] The same or similar numbers in the drawings of the embodiments of the present invention correspond to the same or similar parts; in the description of the present invention, it should be understood that if the terms "upper", "lower", "left", "right", "front", "rear", etc. indicate the orientation or position relationship, they are based on the orientation or position relationship shown in the drawings, which is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation. Therefore, the terms describing the position relationship in the drawings are only used for illustrative purposes and cannot be understood as limiting the present invention. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0093] See also Figure 2 to Figure 5 , which is a method to enhance the reliability of data transmission in time-sensitive networks.

[0094] Example

[0095] This embodiment proposes a method for enhancing the reliability of data transmission in a time-sensitive network, and in particular, a specific implementation method of a method for enhancing the reliable transmission of data along a primary path and an intersecting redundant path in a time-sensitive network, which includes the following steps:

[0096] S1. Calculate the working path based on the reliability evaluation model in the alternative paths of the TSN network. First, use the backtracking method to search all possible alternative paths between the source and destination nodes in the TSN network to obtain an alternative path set. Then, in order to further distinguish the differences between the paths, evaluate the path reliability of the alternative paths in the path set, and finally select a path with the highest reliability as the normal working path.

[0097] The work path calculation based on the reliability evaluation model in S1 is divided into the following three steps:

[0098] S11. Use the backtracking method to search for all possible paths between the source and destination nodes:

[0099] S111. Initialize the predecessor node array: For each node i in the TSN network topology, maintain a predecessor node array predecessor[] to record the previous node of i on the path from the starting point s to the node i.

[0100] S112, path backtracking: starting from the destination node d, use the predecessor[] array to backtrack to the source node s; during the backtracking process, the visited nodes are pushed into the path stack pathStack in sequence.

[0101] S113, output path: pop up the nodes in pathStack in sequence to form a path from the starting point s to the destination node d; add the constructed path to the path set KP(s,d) for subsequent reliability evaluation.

[0102] S12. List all link and node failure states that may cause TSN data flow disconnection:

[0103] All routes of each TSN data stream transmitted between the source node s and the destination node d constitute a routing graph R, R = {V, E} (E represents the link set in R, V represents the node set in R). Each node that the TSN data stream passes through represents a node in the TSN network, with a given node failure probability; each link represents a physical link, with a given link failure probability, which is expressed as a weighted percentage in the TSN network. The simultaneous failure probability can be divided into three cases, including only link failure, only node failure, and both node failure and link failure, such as Figure 2 shown.

[0104] 1) For link failure probability: Failure probability PLR of link data transmission in TSN network (i,j) It is related to the status and properties of the link and can be expressed as follows:

[0105]

[0106] in, represents the consumed bandwidth of link (i, j), represents the total working capacity of link (i, j), q (i,j) represents the probability that link (i, j) works normally, α (i,j) represents the ratio of the bandwidth consumed by link (i, j) to the total working capacity of the link, p (i,j)represents the probability of link (i, j) failure, and E represents the set of links in the routing graph R.

[0107] 2) For node failure probability: the failure probability PLR of data transmission on the node in the TSN network i Related to the state and properties of the node, it can be expressed as follows:

[0108]

[0109] in, represents the consumed bandwidth of node i, represents the total working capacity of node i, q i represents the probability that node i works normally, β i represents the ratio of the cache consumed by node i to the total working capacity of the node, p i represents the probability of node i failure, and V represents the set of nodes in the routing graph R.

[0110] S13, the process of calculating the working path includes:

[0111] S131. Definition of path reliability: The reliability of traffic transmission on a path consists of two aspects: links and nodes. It is related to both the link failure probability and the node failure probability, and can be expressed as follows:

[0112]

[0113] Among them, PLR k The failure probability of node k, PLR (i,j) is the failure probability of link (i,j).

[0114] S132. Define the link weight function: take all links and nodes at both ends of the links in the TSN network as paths, and use path reliability as a metric to assign values ​​to all links in the routing graph. The link weight W in the routing graph R = {V, E} i,j The function can be expressed as follows:

[0115]

[0116] After processing, the reliability attribute of the path is presented in the form of additivity on the link weight in the routing graph R, and the smaller the link weight of the selected path, the greater the reliability of the path.

[0117] The weighted sum of each link of path P in the path set KP(s,d) is:

[0118]

[0119] Where R P is the reliability of path P, that is:

[0120]

[0121] The smaller the sum of the selected path weights is, the higher the path reliability is.

[0122] After assigning values ​​to all links in the routing graph R = {V, E} according to the link weight function, the Dijkstra path algorithm based on reliability cost calculates an optimal path P1 from the source node s to the destination node d. P1 is the path with the highest reliability attribute from s to d in the graph R. Path P1 is used as the working path P w .

[0123] S2. Using the idea of ​​segment protection, by considering the reliability requirements of the working path nodes, nodes with frame replication and elimination functions are selectively deployed. Segment protection can tilt the protection resources to the remaining paths while ensuring the reliability of some paths. The difference between end-to-end protection and segment protection is as follows: Figure 3 As shown in the figure, end-to-end protection replicates data in the form of frames at node S and eliminates data at node D. Segment protection replicates data at node R and eliminates data at node D, which is part of end-to-end protection. Under the premise of meeting reliability requirements, adopting segment protection to deploy frame replication and node elimination can balance efficient resource utilization and ensure different reliability requirements.

[0124] In the process of deploying frame replication and eliminating nodes with segmented protection in S2, the TSN working path P is first calculated. w The evaluation index of each node i is used to deploy frame replication and frame elimination nodes FN = {r, e} according to the node evaluation index, where r is the frame replication node and e is the frame elimination node. The deployment of FN is based on the reliability evaluation E of each node. i Decide.

[0125] S21. Calculate TSN working path P w Evaluation index of each node i: node reliability evaluation E i The following six evaluation indicators are comprehensively considered: 1. The replication and elimination nodes should be as close to the source and destination nodes as possible to ensure the multi-path forwarding process to the greatest extent; 2. The replication and elimination nodes should try to select nodes with a large number of connected links (large degree centrality) to achieve load balancing; 3. The replication and elimination nodes should try to select nodes with the most shortest paths to ensure fast forwarding of frames; 4. The replication and elimination nodes should try to select nodes with a low probability of failure to ensure the reliability of the nodes; 5. The replication and elimination nodes should try to select nodes with a low average probability of link failure to ensure normal forwarding of frames.

[0126] The working path in TSN is denoted as P w , the node set on the working path is V w .

[0127] 1) For node proximity (PD i ): The degree of proximity between a node and the source node or the destination node; when calculating the frame replication node r, the node proximity between the node and the source node needs to be considered; when calculating the frame elimination node e, the node proximity between the node and the destination node is considered.

[0128]

[0129] Where d(i,s / d) is the shortest path length from node i to source node s or destination node d.

[0130] 2) For node degree centrality (DC i ): reflects the relationship between a node and surrounding nodes;

[0131]

[0132] Among them, γ ij represents the number of links between nodes i and j;

[0133] 3) For betweenness centrality (BC i ): Based on the working path P w After the centrality measurement of node i;

[0134]

[0135] Among them, g (s,t) represents the number of shortest paths from node i to node j, Represents the number of shortest paths from node s to node t that pass through node i.

[0136] 4) For the node failure probability Related to the state and properties of the node;

[0137]

[0138] Among them, β i represents the ratio of the cache consumed by node i to the total working capacity of the node, p i represents the probability of node i failing.

[0139] 5) For the average link failure probability The average PLR ​​of the links connected to node i;

[0140]

[0141] Where m is the number of links around node i, represents the failure probability of the link (i, j) connected to node i.

[0142] S22. Use the entropy weight method to determine the weights of the five indicators that affect the frame replication node and the frame elimination node. The entropy value is used to determine the degree of dispersion of each indicator. The greater the degree of dispersion of the indicator, the greater the weight of the indicator in the comprehensive evaluation. The above indicators are all positive indicators. The greater the value they reach, the higher the probability that the node is selected as FN.

[0143] In order to eliminate the dimensional impact between indicators, the data needs to be normalized to solve the comparability between indicators. The normalization calculation of each node indicator is as follows:

[0144]

[0145] Among them, a ij is the original value of index j at node i, a i ′ j The normalized value of index j at node i.

[0146] The proportion of the index value of the i-th node under the j-th index (p ij ) is calculated as:

[0147]

[0148] Evaluate the input entropy (e j )for:

[0149]

[0150] And the entropy weight of index j (w j ):

[0151]

[0152] Finally, the reliability evaluation E of node i is obtained i for:

[0153]

[0154] The frame replication and elimination node deployment is based on the probability of a node being deployed as a frame replication and elimination node. When calculating the frame replication node r, the node proximity between the node and the source node needs to be considered; when calculating the frame elimination node e, the node proximity between the node and the destination node is considered. i The nodes are sorted to obtain nodes FN = {r, e} that are suitable for frame replication and elimination.

[0155] S3. Sort the redundant candidate paths using the redundant path combination reliability index to determine the redundant path P r To transmit the duplicate frame.

[0156] In S3, it is necessary to consider the impact of link and node reliability on data delivery, and to select a set of optimized redundant paths that meet the reliability requirements while meeting the data redundancy N requirements, so as to avoid the problem of unreliable data transmission caused by errors during data transmission. Figure 4 and Figure 5 These are the possible path combinations corresponding to the redundancy N=3 and the redundancy N=4 respectively.

[0157] In S3, the main implementation is to determine the redundant path combination according to the redundancy requirements in the candidate redundant path set D(s,d). The process is mainly divided into the following steps:

[0158] S31. Extract a set of candidate redundant paths D(s, d).

[0159] Remove the working path P from the original routing graph R = {V, E} w All links of the routing graph R ′ =RE P , create a set of alternative redundant paths D(s,d), using the new routing graph R ′ Find all possible paths that contain the path segment (s, r) from the source node to the frame copy node and the path segment (e, d) from the frame elimination node to the destination node, then traverse all paths and check whether the current path intersects with any path in D(s, d) between the frame copy and elimination nodes. If they do not intersect, add the current path to the set D(s, d).

[0160] S32. According to the path redundancy N (1 main path plus N-1 redundant path combinations), calculate the reliability index R of the N-1 redundant path combinations.

[0161] In the method of enhancing the reliable transmission of data in time-sensitive networks, the number and quality of redundant paths are crucial to the reliable transmission of data in time-sensitive networks. If the number of redundant paths is too small, the requirements of data transmission cannot be met. If the quality of redundant paths is too poor, data transmission errors or losses may occur.

[0162] According to the path reliability formula obtained in S1 The path reliability from the starting point s to the node i can be calculated It can be expressed as follows:

[0163]

[0164] in, is the link weight between node u and node v, u is the predecessor node of v, and link (u, v) belongs to link (s, i).

[0165] Then the reliability index R of the N-1 path combination can be expressed as follows:

[0166]

[0167] in, Represents the sum of the path reliability costs from the starting point to each node i.

[0168] All possible paths are sorted according to the sum of path reliability costs. To optimize the redundant path combination, the objective function is normalized, as shown in the formula.

[0169]

[0170] Among them, k represents the number of overlapping links, n represents the number of intersecting nodes, m represents the number of links between the intersecting nodes and the target nodes, and R is the TSN network transmission reliability index of N-1 paths.

[0171] In the new routing graph R ′ After assigning values ​​to all links according to the link weight function, the Dijkstra path algorithm based on reliability cost calculates N-1 optimal redundant path combinations according to different data redundancy N. The path As a redundant path combination P r .

[0172] S4, the combination of frame duplication nodes and elimination nodes in the output TSN FN = {r, e} and the optimal primary and redundant path combination in the routing graph According to the combination of frame replication nodes and elimination nodes FN = {r, e} deployment scheme and the optimal primary and redundant path combination Perform data transmission.

[0173] The output results in S4 can all be obtained from the previous steps. In S1, a working path that meets the reliability requirements is obtained; in S2, frame replication nodes and frame elimination nodes are screened; in S3, a redundant path that meets the reliability requirements of all data flows is obtained.

[0174] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. A method for enhancing the reliability of time-sensitive network data transmission, characterized in that: The method comprises the following steps: S1. Search all alternative paths in the TSN network and calculate the working path P based on the path reliability. w ; S2. Selectively deploy frame replication and frame elimination nodes FN according to node reliability; S3, extracting a set of candidate redundant paths, and determining a redundant path combination P in the set of candidate redundant paths according to redundancy r ; S4. Output the combination FN of the frame duplication node and the elimination node, and the optimal primary-redundant path combination P.

2. The method for enhancing the reliability of time-sensitive network data transmission according to claim 1, characterized in that: In step S1, the following steps are included: S11, using the backtracking method to search for all possible paths between the source and destination nodes as candidate paths, which includes: S111, initialize the predecessor node array: for each node i in the TSN network topology, maintain a predecessor node array predecessor[], which is used to record the previous node of i on the path from the starting point s to the node i; S112, path backtracking: starting from the destination node d, use the predecessor[] array to backtrack to the source node s; during the backtracking process, the visited nodes are pushed into the path stack pathStack in sequence; S113, output path: pop up the nodes in pathStack in sequence to form a path from the starting point s to the destination node d; add the constructed path to the path set KP(s,d); S12, calculating the probability of all link and node failure states that may cause the TSN data flow to be disconnected; S13, define path reliability and link weight function, assign values ​​to all links through link weight function, and then calculate the optimal path according to path reliability, and use the optimal path as the working path P w .

3. The method for enhancing the reliability of time-sensitive network data transmission according to claim 2, characterized in that: In step S12, all candidate paths between the source node s and the destination node d form a routing graph R = {V, E}, where E represents the link set in R and V represents the node set in R; both links and nodes have failure probabilities, and thus the failure conditions are divided into link failure, node failure, and simultaneous failure of nodes and links, and their probabilities are expressed as follows: 1) Link failure probability: The failure probability PLR of link data transmission in the TSN network (i,j) Related to the status and attributes of the link: in, represents the consumed bandwidth of link (i, j), represents the total working capacity of link (i, j), q (i,j) represents the probability that link (i, j) works normally, α (i,j) represents the ratio of the bandwidth consumed by link (i, j) to the total working capacity of the link, p (i,j) represents the probability of link (i, j) failure; 2) Node failure probability: The failure probability PLR of data transmission on the node in the TSN network i Related to the state and properties of the node, then: in, represents the consumed bandwidth of node i, represents the total working capacity of node i, q i represents the probability that node i works normally, β i represents the ratio of the cache consumed by node i to the total working capacity of the node, p i represents the probability of node i failure.

4. The method for enhancing the reliability of time-sensitive network data transmission according to claim 3, characterized in that: In step S13, the following steps are included: S131. Define path reliability: Path reliability is related to both link failure probability and node failure probability, as shown below: Among them, PLR k The failure probability of node k, PLR (i,j) is the failure probability of link (i, j); S132, define link weight function: link weight W in routing graph R = {V, E} i,j The function is expressed as follows: The weighted sum of each link of path P in the path set KP(s,d) is: Where E(P) is all the nodes in path P; R P is the reliability of path P, that is: When the sum of the selected path weights is smaller, the path reliability is higher; After assigning values ​​to all links in the routing graph R = {V, E} according to the link weight function, the Dijkstra path algorithm based on reliability cost calculates an optimal path P1 from the source node s to the destination node d, and uses path P1 as the working path P w .

5. The method for enhancing the reliability of time-sensitive network data transmission according to claim 2, characterized in that: In step S2, the following steps are specifically included: S21. Calculate TSN working path P w The evaluation index of each node i, including node proximity PD i , node degree centrality DC i , Betweenness Centrality BC i , node failure probability Average link failure probability S22, using the entropy weight method to determine the weights of the corresponding indicators affecting the frame replication node and the frame elimination node, and then determine the node reliability E i , and then evaluate E according to the node reliability i The nodes are sorted to obtain the nodes FN={r,e} as the frame replication and frame elimination nodes.

6. The method for enhancing the reliability of time-sensitive network data transmission according to claim 5, characterized in that: In step S21, let the working path in TSN be P w , the node set on the working path is V w , then: 1) For node proximity PD i : The degree of proximity between a node and the source node or the destination node; when calculating the frame replication node r, the node proximity between the node and the source node needs to be considered; when calculating the frame elimination node e, the node proximity between the node and the destination node is considered; Where d(i,s / d) is the shortest path length from node i to source node s or destination node d; 2) For node degree centrality DC i : reflects the relationship between a node and surrounding nodes; Among them, γ ij represents the number of links between nodes i and j; 3) For betweenness centrality BC i :Based on working path P w The centrality measure of node i is: Among them, g (s,t) represents the number of shortest paths from node i to node j, Represents the number of shortest paths from node s to node t that pass through node i; 4) For the node failure probability Related to the state and properties of the node: Among them, β i represents the ratio of the cache consumed by node i to the total working capacity of the node, p i represents the probability of node i failing; 5) For the average link failure probability The average PLR ​​of the links connected to node i: Where m is the number of links around node i, represents the failure probability of the link (i, j) connected to node i.

7. The method for enhancing the reliability of time-sensitive network data transmission according to claim 6, characterized in that: In step S22, firstly, the reliability indicators of several nodes are normalized: Among them, a ij is the original value of index j at node i, a i ' j The normalized value of index j at node i; Calculate the proportion p of the index value of the i-th node under the j-th index ij : Then calculate the evaluation input entropy e j and the entropy weight w of index j j : Finally, the reliability evaluation E of node i is obtained i for: According to the node reliability evaluation E i The nodes are sorted to obtain nodes FN = {r, e} as frames for replication and elimination.

8. The method for enhancing the reliability of time-sensitive network data transmission according to claim 5, characterized in that: In step S3, a redundant path combination is determined from the candidate redundant path set D(s, d) according to the redundancy It includes the following steps: S31, extracting a set of candidate redundant paths D(s, d): removing the working path P from the original routing graph R = {V, E} w All links of the routing table are obtained, and the new routing graph R′=RE P , create a set of candidate redundant paths D(s,d), use the new routing graph R′ to find all possible paths that contain the path segment (s,r) from the source node to the frame replication node and the path segment (e,d) from the frame elimination node to the destination node, then traverse all paths and check whether the current path intersects with any path in D(s,d) between the frame replication and elimination nodes. If they do not intersect, add the current path to the set D(s,d); S32, according to the path redundancy N, calculate the reliability index of N-1 redundant path combinations, after assigning values ​​to all links in the routing graph R′ using the link weight function, calculate the N-1 optimal redundant path combinations according to the reliability index R 9. The method for enhancing the reliability of time-sensitive network data transmission according to claim 8, characterized in that: In step S32, the path reliability from the starting point s to the node i is first calculated. in, is the link weight between node u and node v, u is the predecessor node of v, and link (u, v) belongs to link (s, i); Then the combined reliability index R of N-1 redundant paths is expressed as: in, represents the sum of the path reliability costs from the starting point to each node i; Normalize the reliability index R: Among them, k represents the number of overlapping links, n represents the number of intersecting nodes, m represents the number of links between the intersecting nodes and the target nodes, and R is the TSN network transmission reliability index of the combination of N-1 redundant paths; After assigning values ​​to all links in the new routing graph R′ according to the link weight function, the Dijkstra path algorithm based on reliability cost calculates N-1 optimal redundant path combinations according to different data redundancy N.

10. The method for enhancing the reliability of time-sensitive network data transmission according to claim 8, characterized in that: In step S4, the combination of frame replication nodes and elimination nodes in TSN FN = {r, e} and the optimal primary and redundant path combination in the routing graph are output. According to the combination of frame replication nodes and elimination nodes FN = {r, e} deployment scheme and the optimal primary and redundant path combination Perform data transmission.

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