Novel topological algorithm for improving communication efficiency of switched Ethernet in rail transit

Abstract

The invention discloses a novel topological algorithm for improving the communication efficiency of a switched Ethernet in rail transit, which relates to the field of rail transit communication, and comprises the following steps of: establishing a train switched Ethernet model which comprises nodes, calculating a communication traffic weight A between the nodes, constructing a bipartite graph, and calculating the communication traffic weight A between the nodes; the number of switches is determined according to the number of nodes in each section of the train, all the nodes are divided into different areas according to the weights from high to low on the basis of the communication traffic weights between the nodes, and the nodes with the similar and adjacent weight numbers in each section of the train are divided into the same area. The nodes in the area with the nodes with the high weight number are connected to the marshalling switch, the nodes in the area with the nodes with the low weight number are connected to the sub-switches, matching optimization from the nodes to the switches is completed, and the transmission speed of communication data between the nodes is increased.

Description

Technical Field

[0001] The invention relates to the field of pearl cotton processing technology, and in particular to a new topology algorithm for improving the communication efficiency of rail transit switched Ethernet. Background Art

[0002] With the development of information technology, the train communication network has gradually developed from a single monitoring function to the current integrated control of monitoring, diagnosis, control and multi-professional bearing, and the train formation has also developed from fixed formation to dynamic reconnection and flexible formation. In 2020, the "Outline for the Development of Smart Urban Rail Transit in China" issued by the China Urban Rail Transit Association proposed "smart trains", that is, urban rail transit trains with multi-system control integration and multi-resource information sharing. In order to provide more convenient, safe and efficient riding services, TCMS (train network control system) is no longer limited to the control of trains and the monitoring of train operation status, but needs to become a comprehensive carrier of multiple services such as integrated operation control, video monitoring, multimedia playback, and intelligent operation and maintenance. Traditional TCMS uses TCN (train communication network) technology based on the IEC61375 standard, with a single network topology and poor networking flexibility; relying on MVB / WTB (multi-function vehicle bus / twisted pair train bus) for data transmission, its transmission bandwidth is only 1.5Mbit / s, and the process data update cycle is 32ms. Therefore, the network transmission bandwidth of traditional TCMS is insufficient to support the comprehensive carrying of multiple services of the train. The amount of network transmission data cannot support the operation, maintenance and single-point update of the train. The real-time performance of control data is low, which is not conducive to real-time and precise control, and can no longer meet the development needs of train informatization and intelligence.

[0003] Switched Ethernet has the advantages of high speed, high bandwidth, and good compatibility, and has become the main development direction of train communication networks. The use of switched Ethernet can make the various subsystems of the vehicle organically form a whole, so that TCMS has multi-system carrying capacity and can provide a more convenient and efficient application mode for train operation and maintenance. In the communication system based on switched Ethernet, the network topology can directly affect the communication performance of the network. Improperly designed topology will not only increase the network delay, but also reduce the reliability of the network, affect the performance of the overall network, and even cause security problems.

[0004] The topological structures used in train communication networks mainly include ring network topology and link redundant closed ring network topology. First, the ring network topology has the least impact on network performance, but it does not improve the real-time performance of network communication efficiency and reduce network latency. Secondly, in the link redundant closed ring network topology, by adding routing methods, the location of the routing when the network performance is optimal is obtained, which improves the communication efficiency of the network, but does not have much effect on improving network performance. The introduction of existing Ethernet technology into the rail transit communication network will lead to problems of insufficient network reliability and real-time performance, and increase the cost of network equipment.

[0005] At present, advanced technologies such as artificial intelligence, big data, cloud computing, and the Internet of Things are continuously and deeply integrated with rail transit equipment. Trains embody the core characteristics of intelligence and informatization. In addition to carrying control data, train communication networks need to generate, integrate, transmit, and process more sources, larger quantities, and higher-dimensional operation and service data to achieve integrated transmission of multi-business data. Summary of the invention

[0006] In order to solve the above technical problems, the present invention provides a new topology algorithm for improving the communication efficiency of switched Ethernet in rail transit, which can improve the communication data transmission efficiency between various communication device nodes in the switched Ethernet communication network for trains.

[0007] To achieve the purpose of the present invention, the present invention re-arranges and distributes the equipment in the train, and constructs a new three-layer topology of the train communication network based on switched Ethernet. The three-layer topology is as follows: the first layer is the train-level backbone network, the second layer is the vehicle-level marshaling network, and the third layer is the related train equipment network; a train switched Ethernet model is established, and the equipment control layer in the network topology is analyzed. The equipment nodes of the equipment control layer include CCU central control unit, VCU vehicle control unit, BCU brake control unit, TCU traction control unit, ACU auxiliary control unit, DCU door control unit, HVAC air conditioning system, PIS passenger information system, ATC automatic control system, ER M event recording module, HMI human-machine interaction interface and RIOM other network interfaces, taking into account the special characteristics of the train communication network, such as relatively limited equipment layout, small and fixed network scale, and relatively clear communication relationship between devices, according to the actual data communication between network devices in the train, a bipartite graph allocation algorithm based on communication volume weight is formulated to calculate the communication volume weight between nodes and construct a bipartite graph; then the number of nodes in each car section determines the number of switches required in the car section, and the area where each switch is located is regarded as an independent local area network; finally, based on the communication volume weight between nodes, all nodes are divided into different areas according to the weight from high to low, and the entire network topology optimization is completed. The specific method is as follows:

[0008] First, a switched Ethernet model is established. Considering that there are a large number of network nodes in the switched Ethernet, in order to improve the real-time performance of the network, they need to be assigned to different switch subnets. Assume that there are I nodes and J switches in the entire train network. The I×J matrix W is used to represent the assignment of nodes to switches in the communication network, see formula (1). If node I is assigned to switch J, then the element WI×J in the matrix is ​​1; otherwise, WI×J is 1.

[0009]

[0010] Considering that data interaction is required between nodes, the actual communication volume between nodes is introduced and represented by matrix R, as shown in formula (2). The element Ril in matrix R represents the actual communication volume sent by node I to node L, and Ril = Lil / Til, where Lil and Til represent the length and period of data sent by node I to node L, respectively. Since there is no data interaction between nodes themselves, Rii = 0.

[0011]

[0012] Since the data transmitted in the train communication network has different real-time requirements, in order to facilitate the comparison of the importance of the actual communication volume between each node, the communication volume weight between nodes is introduced and represented by matrix A:

[0013]

[0014] Where max{RIL} is the maximum value of the elements in matrix A.

[0015] Finally, the device node allocation algorithm based on the communication volume weighted bipartite graph is designed. Let G = (V, E) be an undirected graph. If the vertex set G can be divided into two non-intersecting subsets (I, J), and the two vertices M∈I, N∈J associated with each edge (M, N) in the graph, then the graph G is called a bipartite graph. On this basis, by combining the bipartite graph with the communication volume between nodes in the train, the communication volume weight between nodes is introduced, and the allocation of nodes to switches is completed based on the size of the weight. The steps of the device node allocation algorithm based on the bipartite graph are as follows:

[0016] 1) The number of switches is determined by the number of nodes in each vehicle section, and the area where the nodes connected to the same switch are located is considered to be an independent local area network. Among them, the number of switches J should not be less than the ratio of the number of nodes I in the vehicle section to the number of switch ports K. Since the switch port should also reserve two link input / output ports, the number of switches is as shown in formula (4):

[0017]

[0018] 2) Calculate the communication volume weight between nodes according to formula (2) and formula (3);

[0019] 3) Number the device nodes and construct a bipartite graph with communication weights. Abstract the network into a bipartite graph G = (I, L) consisting of a node set I = {I1, I2, ..., In} and a link set L = {α12, α13, ..., αn, n-1} with communication weights;

[0020] 4) According to the size of the weight, merge the nodes with similar weights and adjacent nodes from high to low, and divide them into the same area, but ensure that the node allocation meets the constraints of formula (5). Among them, the nodes with similar weights in each vehicle are divided into the same area, and the internal nodes of the area with high-weight nodes are connected to the marshaling switch, while the internal nodes of the area with low-weight nodes are connected to the sub-switch. The constraints are as follows:

[0021]

[0022] In formula (5), En represents the set of nodes in the Nth area, that is, the number of nodes connected to a switch; Kn represents the number of ports of the nth switch; C1 indicates that each node can only be assigned to one area, that is, each node can only be connected to one switch; C2 indicates that all nodes are assigned to different areas. In addition, nodes cannot communicate directly with each other and need to communicate through the switch; C3 indicates that the number of nodes assigned to each area cannot exceed the number of ports of the switch.

[0023] 5) Repeat the process in 4) until all nodes are divided into different areas.

[0024] In summary, the beneficial technical effects of the present invention are:

[0025] By constructing a bipartite graph, the number of switches is determined according to the number of nodes in each section of the train. Based on the communication volume weight between each node, all nodes are divided into different areas according to the weight from high to low. Nodes with similar and adjacent weights in each section of the train are divided into the same area. Nodes inside the area with high-weight nodes are connected to the marshaling switch, and nodes inside the area with low-weight nodes are connected to the sub-switch, completing the node-to-switch matching optimization and improving the transmission speed of communication data between nodes. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a three-layer topology of the train communication network based on switched Ethernet;

[0027] Figure 2 This is a schematic diagram of the network segment after topology optimization;

[0028] Figure 3 Assign a flow chart to a node;

[0029] Figure 4 To improve the communication efficiency of network topology and traditional network structure. DETAILED DESCRIPTION

[0030] The present invention will be further described below in conjunction with the embodiments of the present invention and comparative examples, and the technical solution of the present invention will be clearly and completely described. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] Example 1

[0032] like Figures 1 to 3 A new topology algorithm is shown to improve the efficiency of switched Ethernet communication in rail transit.

[0033] In this embodiment, a train switched Ethernet model is established with the device nodes within the driving cab vehicle and the passenger compartment vehicle of an EMU as optimization objects. The device node names and corresponding English abbreviations are shown in Table 1, and the node list and its numbering are shown in Table 2.

[0034]

[0035] Table 1 Device node names and corresponding English abbreviations

[0036]

[0037] Table 2 Node list and its number

[0038] As attached Figure 2 As shown in the network segment diagram, the number of ports of each switch in this embodiment is 8. The number of switches in the driver's cab and the passenger compartment can be calculated by formula (5). Considering the actual situation of vehicle wiring and the number of network nodes, the number of switches in the two vehicles is 3 and 2 respectively. Among them, one switch in each vehicle is a vehicle-level marshaling switch, and the others are sub-switches.

[0039] The round-trip data communication volume between two nodes in the matrix R is equal, that is, αin = αln. The data frame size of CCU and VCU is 128 bytes, and the period is 4ms; the data frame size of PIS is 960 bytes, and the period is 150ms. From equations (2) and (3), it can be calculated that the communication volume weight between CCU and VCU is 1; the communication volume weight between VCU and PIS is 0.2. Similarly, the CCU in the cab communicates with various control units VCU, BCU, TCU, ACU and ATC in each vehicle, and their weights are 1, 1, 1, 1 and 0.5 respectively; other equipment DCU, HVAC, PIS and RIOM in each vehicle communicate with the VCU of the vehicle in this section, and their weights are 1, 1, 1, 1 and 0.5 respectively; HMI first exchanges data with CCU through ERM, and the weights are 0.4 and 0.5. The bipartite graph is constructed by the communication volume weights between nodes, and the allocation of all device nodes is completed according to the allocation algorithm. The node allocation flow chart is shown in the attached figure. Figure 3 shown.

[0040] In this embodiment, the site size of the application scenario is set to 400×400m, and 6 subnets are set to represent the 6 vehicles of the train set. Each subnet is connected by a switched Ethernet method improved by the device node allocation algorithm of the communication volume weight bipartite graph based on its internal grouping switch, and each subnet is 50m apart.

[0041] Comparative Example 1

[0042] Compared with Example 1, the site size of the application scenario set in this comparative example is 400×400m, and 6 subnets are set to represent the 6 vehicles of the train set. Each subnet is connected by its internal marshaling switch in a ring topology, and each subnet is 50m apart.

[0043] Comparative Example 2

[0044] Compared with Example 1, the site size of the scenario set in this comparative example is 400×400m, and 6 subnets are set to represent the 6 vehicles of the train set. Each subnet is connected by its internal marshaling switch using a link redundant closed ring network topology, and each subnet is 50m apart.

[0045] like Figure 3 As shown, by comparing the communication efficiency of each train equipment network in Example 1, Comparative Example 1 and Comparative Example 2, the communication efficiency of the switched Ethernet model after the device node allocation algorithm based on the communication volume weighted bipartite graph in Example 1 is improved is better than the traditional ring network topology and the link redundant closed ring network topology, and the communication efficiency of the optimized Ethernet model is significantly improved.

Claims

1. A new topology algorithm for improving the communication efficiency of rail transit switched Ethernet, characterized in that: The following steps are involved: Step S1, establishing a train switched Ethernet model, including a train-level backbone network, a vehicle-level marshaling network, and a train equipment network; Step S2, the train equipment network includes nodes, the communication volume weight A between each of the nodes is calculated, and a bipartite graph is constructed; Step S3, determining the number of switches according to the number of nodes in each vehicle of the train; Step S4, nodes with similar communication volume weights A in each car of the train are divided into the same area, nodes inside the area with high-weight nodes are connected to the marshaling switch, and nodes inside the area with low-weight nodes are connected to the sub-switch.

2. The novel topology algorithm according to claim 1 is characterized in that: In the step S2, the nodes are allocated to different switch subnets; the allocation of the nodes in the switch subnets is represented by the following matrix formula W; Where I represents the number of nodes in the train switched Ethernet, and J represents the number of switches in the train switched Ethernet.

3. The novel topology algorithm according to claim 2 is characterized in that: The actual communication volume R between the nodes is represented by the following matrix formula: Where R il =L il / T il , L il 、T il Represents the length of the data sent from node I to node L, T il Represents the period of data sent from node I to node L.

4. The novel topology algorithm according to claim 3 is characterized in that: The communication weight A between nodes is expressed by the following matrix formula: Where max{R IL } is the maximum value of the elements in the traffic weight A.

5. The novel topology algorithm according to claim 4 is characterized in that: The number of switches J is calculated by the following formula: Where K represents the number of switch ports.

6. The novel topology algorithm according to claim 5, characterized in that: The nodes are numbered, and the train switched Ethernet is abstracted into a set of nodes I = {I1, I2, ..., I n } and the link set L of the traffic weight A = {α 12 , α 13 , …, α n,n-1 }, the node set and the link set together constitute a bipartite graph G = (I, L); the nodes are arranged according to the size of the communication volume weight A, and the nodes with similar and adjacent communication volume weights A are divided into the same area.

7. The novel topology algorithm according to claim 6, characterized in that: Each of the nodes is connected to only one switch.

8. The novel topology algorithm according to claim 7 is characterized in that: The nodes are allocated to different areas, and the nodes are connected for communication via switches.

9. The novel topology algorithm according to claim 8, characterized in that: The number of nodes allocated in the same area (previous item) cannot exceed the number of ports of the switch.

10. The novel topology algorithm according to claim 9, characterized in that: All the nodes are divided into different areas.

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