Route scheduling method and device for intelligent optical fiber distribution machine cluster

Abstract

The invention provides a route scheduling method and device for an intelligent optical fiber wiring machine cluster, and relates to the technical field of optical fiber communication. The intelligent optical fiber wiring machine cluster is constructed based on a plurality of intelligent optical fiber wiring machines; judging whether the network type of the intelligent optical fiber distribution machine cluster is a centralized control type cluster network or a non-centralized control type cluster network; wherein if the network is a centralized control type cluster network, a central control node is determined; the method comprises the following steps: aiming at a centralized control type cluster network, analyzing internal routing of an intelligent optical fiber distribution machine cluster by adopting a mode of combining a bidirectional BFS traversal algorithm and outward diverging traversal of a central control node to obtain an optical fiber routing path; and generating a fiber core moving instruction according to the optical fiber routing path, and controlling the intelligent optical fiber distribution machine to perform plugging operation on a corresponding optical fiber. Therefore, the problems of transmission channel capacity expansion and efficient routing scheduling when the number of intelligent optical fiber distribution ports is insufficient are efficiently solved.

Description

Technical Field

[0001] This application relates to the field of optical fiber communication technologies, and in particular, to a routing and scheduling method and device for an intelligent optical fiber distribution machine cluster. Background Art

[0002] At present, with the continuous development of optical fiber communication and the continuous growth of optical fiber traffic volume, the port number of intelligent optical fiber distribution machines may not meet the growing needs of users. To solve the problem of insufficient ports, it has become a feasible solution to internally combine multiple intelligent optical fiber distribution machines to form a cluster. However, existing routing algorithms have problems such as low efficiency and slow convergence speed when dealing with complex cluster network topologies, and cannot well meet the needs of intelligent optical fiber distribution machine clusters. Summary of the Invention

[0003] In view of this, the purpose of this application is to provide a routing and scheduling method and device for an intelligent optical fiber distribution machine cluster, which can solve the problems of transmission channel expansion and efficient routing and scheduling when the number of intelligent optical fiber distribution ports is insufficient.

[0004] A routing and scheduling method for an intelligent optical fiber distribution machine cluster provided by an embodiment of this application includes the following steps: Construct an intelligent optical fiber distribution machine cluster based on multiple intelligent optical fiber distribution machines; Determine whether the network type of the intelligent optical fiber distribution machine cluster is a centralized control type cluster network or a non-centralized control type cluster network; wherein, if it is a centralized control type cluster network, determine its central control node; For a centralized control type cluster network, analyze the internal routing of the intelligent optical fiber distribution machine cluster by combining the bidirectional BFS traversal algorithm with the outward divergence traversal from the central control node to obtain the optical fiber routing path; Generate a fiber core movement instruction according to the optical fiber routing path, and control the intelligent optical fiber distribution machine to perform plugging and unplugging operations on the corresponding optical fiber.

[0005] In some embodiments, the determining whether the network type of the intelligent optical fiber distribution machine cluster is a centralized control type cluster network or a non-centralized control type cluster network includes the following steps: Obtain the physical connection relationship of the external ports of each node in the intelligent optical fiber distribution machine cluster, and construct a connectivity matrix; Initialize the central control degree evaluation value according to the connection situation of each node in the intelligent optical fiber distribution machine cluster with other nodes, and form a vector of central control degree initialization evaluation values of all nodes in the intelligent optical fiber distribution machine cluster; Iterate the vector of central control degree initialization evaluation values by using the connectivity matrix to obtain the central control degree evaluation value of each node in the intelligent optical fiber distribution machine cluster; If the central control degree evaluation value of a node in the intelligent optical fiber distribution machine cluster is greater than a preset threshold value, it is determined that the network type of the intelligent optical fiber distribution machine cluster is a centralized control type cluster network. If not, it is determined that the network type of the intelligent optical fiber distribution machine cluster is a non-centralized control type cluster network.

[0006] In some embodiments, the sum of the central control degree evaluation values of all nodes in the intelligent optical fiber distribution machine cluster is 1.

[0007] In some embodiments, the iteration of the initial evaluation value vector of the central control degree by using the connectivity matrix includes the following steps: Based on the differences in the central control degree evaluation values of each node in the adjacent two rounds of iteration results, an iteration end condition is set.

[0008] In some embodiments, the central control node of the intelligent optical fiber distribution machine cluster is determined in the following manner, including the following steps: Nodes with central control degree evaluation values greater than a preset threshold value are used as alternative central control nodes of the intelligent optical fiber distribution machine cluster, and the number of the alternative central control nodes is determined; If the number of the alternative central control nodes is greater than 1, the alternative central control node with the largest central control degree evaluation value is selected as the final central control node of the intelligent optical fiber distribution machine cluster; or the service load rate of each alternative central control node is calculated, and the alternative central control node with the smallest service load rate is used as the final central control node of the intelligent optical fiber distribution machine cluster.

[0009] In some embodiments, for the centralized control type cluster network, the internal routing of the intelligent optical fiber distribution machine cluster is analyzed by combining the bidirectional BFS traversal algorithm and the outward divergence traversal from the central control node to obtain the optical fiber routing path, including the following steps: Starting from the start node, the end node and the central control node respectively, directly connected nodes and the connection sequence of idle fiber core ports are searched, and the corresponding data are stored in the forward routing set, the reverse routing set and the central control routing set; wherein, for dual-core services, the number of connection sequences of idle fiber core ports between nodes is at least 2; The data storage structures of the forward routing set, the reverse routing set and the central control routing set are uniformly defined and initialized; According to the node intersection situation in the forward routing set, the reverse routing set and the central control routing set, the corresponding fiber core port binary tuple sets are spliced to obtain the optical fiber routing path.

[0010] In some embodiments, the method further includes the following steps: For a non-centrally controlled cluster network, the two-way BFS traversal algorithm is used to analyze the internal routing of the intelligent optical fiber distribution machine cluster from the starting node to the ending node simultaneously, and the optical fiber routing path is obtained.

[0011] In some embodiments, a routing scheduling device for an intelligent optical fiber distribution machine cluster is further provided. The device includes: A construction module for constructing an intelligent optical fiber distribution machine cluster based on multiple intelligent optical fiber distribution machines; A judgment module for judging whether the network type of the intelligent optical fiber distribution machine cluster is a centrally controlled cluster network or a non-centrally controlled cluster network; wherein, if it is a centrally controlled cluster network, its central control node is determined; An analysis module for, for a centrally controlled cluster network, analyzing the internal routing of the intelligent optical fiber distribution machine cluster by combining the two-way BFS traversal algorithm with the outward divergence traversal from the central control node to obtain the optical fiber routing path; An execution module for generating a fiber core movement instruction according to the optical fiber routing path and controlling the intelligent optical fiber distribution machine to perform plugging and unplugging operations on the corresponding optical fibers.

[0012] In some embodiments, an electronic device is further provided, including: a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the electronic device runs, the processor communicates with the memory through the bus. When the machine-readable instructions are executed by the processor, the steps of a routing scheduling method for an intelligent optical fiber distribution machine cluster as described in any one of the above are executed.

[0013] In some embodiments, a computer-readable storage medium is further provided. A computer program is stored on the computer-readable storage medium. When the computer program is run by a processor, the steps of a routing scheduling method for an intelligent optical fiber distribution machine cluster as described in any one of the above are executed.

[0014] A routing and scheduling method and device for an intelligent optical fiber distribution machine cluster according to the present application constructs an intelligent optical fiber distribution machine cluster based on multiple intelligent optical fiber distribution machines; determines whether the network type of the intelligent optical fiber distribution machine cluster is a centralized control type cluster network or a non-centralized control type cluster network; wherein, if it is a centralized control type cluster network, its central control node is determined; for the centralized control type cluster network, a two-way BFS traversal algorithm is combined with a divergence traversal from the central control node to analyze the internal routing of the intelligent optical fiber distribution machine cluster to obtain an optical fiber routing path; a core movement instruction is generated according to the optical fiber routing path to control the intelligent optical fiber distribution machine to perform plugging and unplugging operations on the corresponding optical fibers. Thus, when the number of intelligent optical fiber distribution ports is insufficient, the effective expansion of the transmission channel is realized by constructing an intelligent optical fiber distribution machine cluster, and through an optimized routing algorithm, the efficient implementation of the optical fiber routing in the intelligent optical fiber distribution machine cluster is ensured, and the load balance is taken into account to improve the performance of the entire intelligent optical fiber distribution machine cluster. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the accompanying drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present application and should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 Shows a flowchart of the routing and scheduling method of the intelligent optical fiber distribution machine cluster described in the embodiments of the present application; Figure 2 Shows a flowchart of determining whether the network type of the intelligent optical fiber distribution machine cluster is a centralized control type cluster network or a non-centralized control type cluster network described in the embodiments of the present application; Figure 3 Shows a flowchart of determining the central control node of the intelligent optical fiber distribution machine cluster described in the embodiments of the present application; Figure 4 Shows a flowchart of analyzing the internal routing of the intelligent optical fiber distribution machine cluster by combining a two-way BFS traversal algorithm with a divergence traversal from the central control node to obtain an optical fiber routing path for the centralized control type cluster network described in the embodiments of the present application; Figure 5 Shows a schematic structural diagram of the routing and scheduling device of the intelligent optical fiber distribution machine cluster described in the embodiments of the present application; Figure 6 Shows a schematic structural diagram of the electronic device described in the embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the following will clearly and completely describe the technical solutions in the embodiments of this application with reference to the accompanying drawings in the embodiments of this application. It should be understood that the accompanying drawings in this application only serve the purposes of illustration and description, and are not used to limit the protection scope of this application. In addition, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate the operations implemented according to some embodiments of this application. It should be understood that the operations in the flowchart may not be implemented in sequence, and steps without a logical context relationship may be reversed or implemented simultaneously. In addition, those skilled in the art may add one or more other operations to the flowchart or remove one or more operations from the flowchart under the guidance of the content of this application.

[0018] In addition, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. The components of the embodiments of this application usually described and illustrated in the accompanying drawings here may be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of this application to be protected, but only represents the selected embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative efforts belong to the protection scope of this application.

[0019] It should be noted that the term "including" will be used in the embodiments of this application to indicate the existence of the features stated thereafter, but does not exclude the addition of other features.

[0020] In view of the technical problems proposed in the background art, this application provides a routing and scheduling method, device, electronic device, and storage medium for an intelligent optical fiber distribution machine cluster, which can solve the problems of transmission channel expansion and efficient routing and scheduling when the number of intelligent optical fiber distribution ports is insufficient.

[0021] See the attached Figure 1 description of the specification. A routing and scheduling method for an intelligent optical fiber distribution machine cluster provided by this application includes the following steps: S1. Construct an intelligent optical fiber distribution machine cluster based on multiple intelligent optical fiber distribution machines; S2. Determine whether the network type of the intelligent optical fiber distribution machine cluster is a centralized control type cluster network or a non-centralized control type cluster network; among them, if it is a centralized control type cluster network, determine its central control node; S3. For the centralized control type cluster network, analyze the internal routing of the intelligent optical fiber distribution machine cluster by combining the bidirectional BFS traversal algorithm with the outward divergence traversal from the central control node to obtain the optical fiber routing path; S4. Generate a core movement instruction according to the optical fiber routing path, and control the intelligent optical fiber distribution machine to perform plugging and unplugging operations on the corresponding optical fibers.

[0022] To clearly understand the technical solution of the embodiments of the present invention, the intelligent optical fiber distribution machine may be described first. The intelligent optical fiber distribution machine contains a robotic arm inside, which can automatically plug and unplug optical fibers, can automatically perform optical fiber cross-connection and memory connection actions, and feedback the cross-connection results and its own operating status, subverting the current mode of relying on manual on-site optical fiber scheduling, and comprehensively solving the problems of remote automatic control, online monitoring, and resource comprehensive management of the ODN network (the network is the optical distribution network, Optical Distribution Network).

[0023] In step S1, according to different scenario requirements, multiple intelligent optical fiber distribution machines are flexibly configured and combined to form a cluster of intelligent optical fiber distribution machines. The cluster of intelligent optical fiber distribution machines provides overall optical fiber service as a black box device externally, forming an expandable cluster device, and further realizing the port expansion function of the intelligent optical fiber distribution machine, and solving the problem of insufficient core ports of the device.

[0024] In addition, it should be noted that in this application, the nodes in the cluster network of intelligent optical fiber distribution machines are divided into three categories: (1) Starting and ending nodes. The intelligent optical fiber distribution machine where the input port where the specified optical fiber distribution machine needs to open the service is located is used as the transmission starting node; the intelligent optical fiber distribution machine where the output port where the specified optical fiber distribution machine needs to open the service is located is used as the transmission ending node. The starting and ending nodes represent the head and tail node targets that need to open the service, and are also the starting nodes of the bidirectional BFS (Bidirectional Breadth First Search) traversal. Performing a BFS traversal starting from the starting node is called a forward cluster traversal; performing a BFS traversal starting from the ending node is called a reverse cluster traversal. (2) Central control node. It refers to a transfer node in the cluster where a single intelligent optical fiber distribution machine (node) is connected to other surrounding nodes through a core segment, and its correlation degree is significantly higher than that of other nodes. In the cluster network, the correlation degree of a node is determined by the central control degree evaluation value of the node. Optionally, when two or more nodes in the cluster have a high central control degree value, the central control node of this service can be jointly elected according to the external port occupancy rate of the node (the ratio of the number of ports carrying services of the intelligent optical fiber distribution machine to the total number of external ports), considering the service load of the node. (3) Other nodes. Other nodes in the cluster except the starting and ending nodes and the central control node.

[0025] In step S2, in order to complete the analysis of efficient routing, the present application divides the constructed intelligent optical fiber machine wiring machine cluster into a centralized control type cluster network with a central control node and a non-centralized control type cluster network without a central control node. Among them, refer to the appended Figure 2 The method for determining whether the network type of the intelligent optical fiber wiring machine cluster is a centralized control type cluster network or a non-centralized control type cluster network includes the following steps: S201. Obtain the physical connection relationship of the external ports of each node in the intelligent optical fiber wiring machine cluster, and construct a connectivity matrix; S202. Initialize the central control degree evaluation value according to the connection situation of each node in the intelligent optical fiber wiring machine cluster with other nodes, and form a vector of the initial central control degree evaluation values of all nodes in the intelligent optical fiber wiring machine cluster; S203. Iterate the vector of the initial central control degree evaluation values by using the connectivity matrix to obtain the central control degree evaluation value of each node in the intelligent optical fiber wiring machine cluster; S204. If there is a node in the intelligent optical fiber wiring machine cluster whose central control degree evaluation value is greater than a preset threshold, it is determined that the network type of the intelligent optical fiber wiring machine cluster is a centralized control type cluster network; if not, it is determined that the network type of the intelligent optical fiber wiring machine cluster is a non-centralized control type cluster network.

[0026] In step S201, the physical connection relationship of the external ports of each node (intelligent optical fiber wiring machine) in the cluster can be obtained through a pre-constructed database. Suppose there are M nodes in the cluster, and the total number of ports of the nth node (n ≤ M) connecting to other nodes in the cluster is pNum(n), where the number of ports connecting to the pth node is pNum(n - p). Denote the connectivity from node n to node p as pConn(n - p); denote the connectivity from node p to node n as pConn(p - n), then there is: pConn(n - p) = pNum(n - p) / pNum(n) pConn(p - n) = pNum(p - n) / pNum(p) Use an M×M matrix to represent the connectivity connection relationship of the entire undirected graph as: mr = .

[0027] In step S202, first, a matrix definition of the central control degree evaluation values of all nodes in the cluster is given. The central control degree evaluation value of a node indicates the connectivity degree between the node and its surrounding nodes, and the sum of the central control degree evaluation values of all nodes in the cluster is 1. The higher the central control degree evaluation value of each node, the higher the connectivity and the stronger the correlation between the node and its surrounding nodes. Suppose there are M nodes in the cluster, the central control degree evaluation value of the i-th node is mark(i), and the central control degree evaluation value of the m-th node is mark(m). That is, the initial central degree control evaluation value is a 1*M column vector vm(0). According to the above definition, we have: vm(0) = , and .

[0028] In this application, the analysis and calculation of the central control degree evaluation value of nodes are based on the Markov chain model and the connected graph model. This is because the Markov chain model has the property of no aftereffect, that is, the state of the system at a certain moment only depends on the current state, and has nothing to do with the past historical states. In the network of the intelligent optical fiber distribution machine cluster, the state of each node can be regarded as its central control degree evaluation value, and the connection relationship between nodes is similar to the state transition in the Markov chain. The connected graph model is used to describe the connection situation between nodes in the cluster, regarding the cluster network as an undirected connected graph, where each node represents an intelligent optical fiber distribution machine, and the edges between nodes represent their physical connections. The combination of these two models provides an effective framework and method for analyzing the mutual relationship between nodes and calculating the central control degree evaluation value.

[0029] Among them, to obtain the central control degree evaluation value of each node in the cluster, it is necessary to initialize the central control degree evaluation value of each node in the cluster. The initial value is determined by the number of other nodes in the cluster to which the node is connected through the fiber core. Suppose there are M nodes in the cluster, and the number of node connections of the i-th node connected to other nodes through the fiber core is nNum(i). Then the initial central control degree evaluation value of the i-th node in the cluster is mark(i) = nNum(i) / M.

[0030] In step S203, the central control degree initial evaluation value vector vm(0) is iterated through the connectivity matrix mr. Denote the result of the j-th iteration as vm(j), then vm(j) = mr * vm(j - 1).

[0031] According to the model characteristics of the Markov chain model and the connected graph, it can be proved that the calculation of vm is a convergence process. After the k-th round of matrix operations, each component value in vm(k) is compared with that in vm(k - 1), where vm(k - 1, n) represents the value of the central control degree of the n-th node after the (k - 1)-th round of iterative matrix operations, and vm(k, n) represents the value of the central control degree of the n-th node after the k-th round of iterative matrix operations. If for all m element nodes in the matrix calculation result set in the k-th round of iteration, Abs(vm(k, n), vm(k - 1, n)) < δ is satisfied, then the iteration ends. Here, δ is a user-defined constant (the smaller it is, the more accurate the final answer). That is, the iteration end condition is set based on the difference in the evaluation values of the central control degrees of each node in the results of two adjacent rounds of iteration. Furthermore, the evaluation value mark(n) of the central control degree of the n-th node in the cluster is obtained as mark(n) = vm(k, n).

[0032] In step S204, for the evaluation value mark(n) of the central control degree of the n-th node in the cluster, if mark(n) > α * 1 / m is satisfied; where α is a multiple factor (α > 1), the larger this value is, the more obvious the characteristics of the central control node are, and the default value is 2.5. Then it is determined that the network type of the intelligent fiber optic distribution machine cluster is a centralized control type cluster network; if there is no node that satisfies this threshold value, it is determined that the network type of the intelligent fiber optic distribution machine cluster is a non-centralized control type cluster network.

[0033] See the attached instructions Figure 3 , for the centralized control type cluster network, the central control node of the intelligent fiber optic distribution machine cluster is determined in the following way, including the following steps: S205: Nodes with central control degree evaluation values greater than the preset threshold value are used as alternative central control nodes of the intelligent fiber optic distribution machine cluster, and the number of the alternative central control nodes is determined; S206: If the number of the alternative central control nodes is greater than 1, the alternative central control node with the largest central control degree evaluation value is selected as the final central control node of the intelligent fiber optic distribution machine cluster; or calculate the service load rate of each alternative central control node, and use the alternative central control node with the smallest service load rate as the final central control node of the intelligent fiber optic distribution machine cluster.

[0034] In steps S205 and S206, first, nodes with central control degree evaluation values greater than the preset threshold value are used as alternative central control nodes of the intelligent fiber optic distribution machine cluster, and then the final central control node is selected from the alternative central control nodes.

[0035] According to the number of alternative central control nodes, if the number of alternative central control nodes is 1, then the alternative central control node is directly used as the final central control node.

[0036] If the number of alternative central control nodes is greater than or equal to 2, optionally, if the service load of the alternative central control nodes is considered, that is, the service load rate. Suppose node m has pNum(n) external ports, and among them, there are pNum(t) fiber optic ports carrying services. Then the service load rate rload(m) of node m is rload(m) = pNum(t) / pNum(n). From the alternative central control nodes, select the one with the minimum rload as the central control node for this time. That is, the selection of the final central control node satisfies min(rload(m)); if the service load rate is not considered, select the one with the maximum central control degree evaluation value from the alternative central control nodes as the final central control node. That is, the selection of the final formal central control node satisfies max(mark(m)).

[0037] In step S3, the cluster data structure is an undirected connected graph structure. To improve the routing efficiency within the fiber optic distribution machine cluster in complex scenarios, both the centralized control type cluster network and the non - centralized control type cluster network adopt the bidirectional BFS traversal algorithm. Compared with the unidirectional BFS traversal, the bidirectional BFS traversal can perform a two - way analysis of the internal routing of the cluster from the target start and end nodes simultaneously, and its execution efficiency is higher than that of the unidirectional BFS traversal algorithm. Among them, for the centralized control type network, on the basis of the bidirectional BFS traversal algorithm, the outward divergence traversal from the central control node is added, further improving the convergence time of the routing algorithm.

[0038] Next, taking the centralized control type cluster network as an example, the whole process of the algorithm combining bidirectional BFS convergence and outward divergence acceleration convergence from the central control node is described. Specifically, if the cluster is a non - centralized control type cluster network, the algorithm degenerates into a bidirectional BFS convergence algorithm without a central control node.

[0039] See the attached Figure 4 For the centralized control type cluster network, the internal routing of the intelligent fiber optic distribution machine cluster is analyzed by combining the bidirectional BFS traversal algorithm and the outward divergence traversal from the central control node to obtain the fiber optic routing path, including the following steps: S301. Starting from the start node, end node, and central control node respectively, find the directly connected nodes and the connection sequence of idle fiber cores, and store the corresponding data in the forward routing set, reverse routing set, and central control routing set; among them, for the dual - core service, the number of connection sequences of idle fiber cores between nodes is at least 2; S302. Uniformly define the data storage structures of the forward routing set, the reverse routing set, and the central control routing set, and initialize them; S303. According to the node intersection conditions in the forward routing set, the reverse routing set, and the central control routing set, splice the corresponding fiber core port binary group sets to obtain a fiber optic routing path.

[0040] In step S301, starting from the start node, traverse the port relationships of sequentially connected node-node. For example, for node m in the network, find all nodes directly connected to this node, and the idle fiber core port connection sequence item(m, list(n, list(port(r, s)))) between nodes, and add it to the forward routing set list(m, list(n, list(port(r, s)))). Among them, item(m, list(n, list (port(r, s)))) represents the set of binary groups of the fiber core port sequences connected between node m and all nodes n that have a direct connection relationship with it (in the cluster network, two device nodes directly connected by a fiber core). list (port(r, s)) is a set of binary groups of the idle (ports not carrying services) external fiber core port connection sequences of a group of two associated nodes (in the cluster network, two device nodes directly connected by a fiber core) in item. For single-core routing, there is at least one set of external idle fiber core port connection sequences, and for dual-core services, there are at least two sets of external idle fiber core port connection sequences. list(m, list(n, list (port(r, s)))) represents the set of item(m, list(n, list (port(r, s)))) of all nodes in the cluster network.

[0041] Similarly, starting from the termination node, traverse all the node port relationships directly associated with itself. For node e in the network, the traversed result list(e, list(p, list (port(r, s)))) is added to the reverse routing set. And starting from the central control node, traverse all the node port relationships directly associated with itself. For node c in the network, the traversed result list(c, list(d, list (port(r, s)))) is added to the central control routing set.

[0042] In step S302, for the forward routing set, reverse routing set, and central control routing set, their data storage structures are the same, which is list(linkedlist(item(m, n, list(port(r, s))))); where item(m, n, list(port(r, s)) is the external idle fiber core port connection sequence between node m and adjacent node n. linkedlist(item(m, n, list(port(r, s))) is a set of spliced routing sets. The data is a routing of the external idle fiber core port connection sequences of multiple groups of spliced nodes. list(linkedlist(item(m, n, list(port(r, s)))) is a set of linkedlist(item(m, n, list(port(r, s))), storing multiple routings of the external idle fiber core port connection sequences of spliced nodes. And initialize the forward routing set, reverse routing set, and central control point routing set to be empty sets.

[0043] In step S303, perform routing analysis from the cluster in the forward direction, and save the analysis results in the forward routing set. Specifically, starting from the end node of each spliced routing in the forward routing set, if the forward routing set is empty, start from the cluster starting node S as the starting node, denoted as the starting node set list(S). Find the relevant data item(S, list(n, list(port(r, s)))) of the currently analyzed node (the initial value is node S) from the forward set list(S, list(n, list(port(r, s)))). If the routing requirement is a two-fiber service, then from the relevant data item(S, list(n, list(port(r, s)))) of the currently analyzed node, analyze the connection conditions of all nodes adjacent to S. For each node n(S) adjacent to S, the external idle fiber core port connection sequence item(S, n, list (port(r, s))) between node S and adjacent node n needs to satisfy Length(list (port(r, s)))≥2, that is, the two-fiber service requires at least two or more groups of idle fiber core resource connections between node S and adjacent node n. Update the routing splicing result of this time and put it into multiple groups of linkedlist(item(S, n, list(port(r, s)))). And update the result of this forward analysis to the forward routing set list(linkedlist(item(m, n, list(port(r, s)))).

[0044] If the nodes passed through in the forward routing set contain the node u in the reverse routing set, it means that one of the target core routes has been completed. The set of core port pairs formed from the forward route is concatenated with the corresponding set of core port pairs formed from the reverse route to form the final result linkedlist(item(S, n, list(port(r, s)))) and returned, and the routing analysis ends. If the intersection of the nodes in the forward routing set and the reverse routing set is empty, continue the analysis downward.

[0045] If the cluster has a central control node, analyze the central control routing set. Analyze the intersection of the nodes in the forward routing set and the central control routing set. Each intersection node represents that one of the forward routes to the central control route has been completed, and update the corresponding forward routing set and central control routing set of the node. Specifically, the set of core port pairs formed from the forward route is concatenated with the corresponding set of core port pairs in the central control routing set. Update the central control node routing set linkedlist(item(C, n, list(port(r, s))), and at the same time update the above result to the forward routing set linkedlist(item(S, n, list(port(r, s)))). If the intersection of the nodes in the forward routing set and the central control routing set is empty, continue the analysis downward.

[0046] The process of performing routing analysis in reverse from the cluster and saving the analysis results in the reverse routing set is similar to the process of performing routing analysis in the forward direction from the cluster and saving the analysis results in the forward routing set, which will not be elaborated here.

[0047] For routing analysis, it is performed from the cluster center control node. Starting from the end nodes of each spliced route in the routing set of the center control node, if the routing set of the center control node is empty, then the center control node C is used as the starting node, and the set of route nodes that have been traversed by the center control node is denoted as list(C). Find the relevant data item(C, list(n, list(port(r, s)))) of the currently analyzed node (initially the node C) from list(C, list(n, list(port(r, s)))). If it does not exist, it is constructed and generated in the manner of step S201. From the relevant data item(C, list(n, list(port(r, s)))) of the currently analyzed node, analyze the connection conditions of all nodes adjacent to C. For each node n adjacent to C, the external idle fiber core port connection sequence between node C and node n, item(C, n, if the routing requirement is a dual-core service, list (port(r, s))) needs to satisfy Length(list (port(r, s)))≥2, that is, the dual-core service requires at least two or more sets of idle fiber core resource connections between node C and the adjacent node n. Update the current routing splicing result and put it into multiple linked lists (item(C, n, list(port(r, s)))). And update the result of the current center control node analysis to the routing set of the center control node list(linkedlist(item(C, n, list(port(r, s))))).

[0048] Analyze the intersection of the nodes in the forward routing set and the nodes in the center control routing set. Each intersection node represents that one of the forward routes to the center control route has been completed, and update the forward routing set and the center control routing set corresponding to all intersection nodes. Specifically, splice the set of fiber core port binary tuples formed from the center control node routing with the corresponding set of fiber core port binary tuples formed from the forward routing, update the center control node routing set linkedlist(item(C, n, list(port(r, s))), and at the same time update the above result to the forward routing set linkedlist(item(S, n, list(port(r, s))).

[0049] If the nodes in the forward routing set contain the node u in the reverse routing set, it means that one of the target fiber core routes has been completed. Splice the set of fiber core port binary tuples formed from the reverse routing with the corresponding set of fiber core port binary tuples formed from the forward routing to form the final result linkedlist(item(S, E, list(port(r, s)))) and return, and the routing analysis ends.

[0050] Analyze the node intersection in the reverse routing set and the central control routing set. Each intersection node represents that one reverse routing to the central control routing is completed, and update the reverse routing set and the central control routing set corresponding to all included nodes. Specifically, splice the set of core-port binary tuples formed from the central control node routing and the corresponding set of core-port binary tuples formed from the forward routing, update the central control node routing set linkedlist(item(C, n, list(port(r, s)))), and at the same time update the above result to the reverse routing set linkedlist(item(E, n, list(port(r, s)))).

[0051] Thus, according to the device sequence of the finally generated nodes and the corresponding external port-core connection sequence, obtain the complete optical fiber routing path, and clarify the specific transmission route of the optical signal starting from the starting node in the optical fiber network, passing through a series of intermediate nodes, and finally reaching the termination node. By adopting the algorithm that combines bidirectional BFS bidirectional convergence and central control node divergence, the internal convergence time of the routing algorithm is better improved.

[0052] In step S4, generate a core movement instruction according to the optical fiber routing path, and control the robotic arm of the intelligent optical fiber distribution machine to complete the movement operation of the optical fiber.

[0053] A routing scheduling method for an intelligent optical fiber distribution machine cluster provided by the present application can efficiently analyze and obtain a routing by constructing an intelligent optical fiber distribution machine cluster, accurately judging its network type and central control node, and adopting a routing algorithm that combines bidirectional BFS traversal and central control node divergence traversal, and can solve the problems of transmission channel expansion and efficient routing scheduling when the number of intelligent optical fiber distribution ports is insufficient.

[0054] Based on the same inventive concept, an embodiment of the present application also provides a routing scheduling device for an intelligent optical fiber distribution machine cluster. Since the principle of solving problems by the device in the embodiment of the present application is similar to that of the above routing scheduling method for an intelligent optical fiber distribution machine cluster in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be described again.

[0055] As shown in the specification appendix Figure 5 An embodiment of the present application also provides a routing scheduling device for an intelligent optical fiber distribution machine cluster. The device includes: A construction module 501, configured to construct an intelligent optical fiber distribution machine cluster based on multiple intelligent optical fiber distribution machines; A judgment module 502, configured to judge whether the network type of the intelligent optical fiber distribution machine cluster is a centralized control type cluster network or a non-centralized control type cluster network; wherein, if it is a centralized control type cluster network, determine its central control node; An analysis module 503, configured to, for a centralized control type cluster network, analyze the internal routing of the intelligent optical fiber distribution machine cluster by combining a bidirectional BFS traversal algorithm with outward divergence traversal from the central control node to obtain an optical fiber routing path; An execution module 504, configured to generate a core movement instruction according to the optical fiber routing path, and control the intelligent optical fiber distribution machine to perform plugging and unplugging operations on corresponding optical fibers.

[0056] In one embodiment, the judgment module 502 judges whether the network type of the intelligent optical fiber distribution machine cluster is a centralized control type cluster network or a non-centralized control type cluster network, including: obtaining the physical connection relationship of the external ports of each node in the intelligent optical fiber distribution machine cluster, and constructing a connectivity matrix; initializing its central control degree evaluation value according to the connection situation of each node in the intelligent optical fiber distribution machine cluster with other nodes, and forming a central control degree initialization evaluation value vector of all nodes in the intelligent optical fiber distribution machine cluster; using the connectivity matrix to iterate the central control degree initialization evaluation value vector to obtain the central control degree evaluation value of each node in the intelligent optical fiber distribution machine cluster; if there is a node in the intelligent optical fiber distribution machine cluster whose central control degree evaluation value is greater than a preset threshold, determine that the network type of the intelligent optical fiber distribution machine cluster is a centralized control type cluster network, if not, determine that the network type of the intelligent optical fiber distribution machine cluster is a non-centralized control type cluster network. Wherein, the sum of the central control degree evaluation values of all nodes in the intelligent optical fiber distribution machine cluster is 1; and an iteration end condition is set based on the difference in the central control degree evaluation values of each node in the adjacent two rounds of iteration results.

[0057] In one embodiment, the judgment module 502 determines the central control node of the intelligent optical fiber distribution machine cluster, including: taking the node whose central control degree evaluation value is greater than the preset threshold as an alternative central control node of the intelligent optical fiber distribution machine cluster, and determining the number of the alternative central control nodes; if the number of the alternative central control nodes is greater than 1, selecting the alternative central control node with the largest central control degree evaluation value as the final central control node of the intelligent optical fiber distribution machine cluster; or calculating the service load rate of each alternative central control node, and taking the alternative central control node with the smallest service load rate as the final central control node of the intelligent optical fiber distribution machine cluster.

[0058] In one embodiment, the analysis module 503 obtains the optical fiber routing path, including: respectively starting from the start node, the end node and the central control node, searching for the direct connection nodes and the free core port connection sequences, and storing the corresponding data in the forward routing set, the reverse routing set and the central control routing set; wherein, for the dual-core service, the number of free core port connection sequences between nodes is at least 2; uniformly defining the data storage structures of the forward routing set, the reverse routing set and the central control routing set; according to the node intersection situations in the forward routing set, the reverse routing set and the central control routing set, splicing the corresponding core port binary tuple sets to obtain the optical fiber routing path. Among them, for a non-centralized control cluster network, the bidirectional BFS traversal algorithm is used to analyze the internal routing of the intelligent optical fiber distribution machine cluster simultaneously from the start node to the end node to obtain the optical fiber routing path.

[0059] The real-time structured light reconstruction device based on normalized extended epipolar geometry described in this application constructs an intelligent optical fiber distribution machine cluster through a construction module based on multiple intelligent optical fiber distribution machines; judges whether the network type of the intelligent optical fiber distribution machine cluster is a centralized control cluster network or a non-centralized control cluster network through a judgment module; wherein, if it is a centralized control cluster network, determines its central control node; through an analysis module, for a centralized control cluster network, adopts a combination of the bidirectional BFS traversal algorithm and the outward divergence traversal from the central control node to analyze the internal routing of the intelligent optical fiber distribution machine cluster to obtain the optical fiber routing path; through an execution module, generates a core movement instruction according to the optical fiber routing path to control the intelligent optical fiber distribution machine to perform plugging and unplugging operations on the corresponding optical fibers. Thus, when the number of intelligent optical fiber distribution ports is insufficient, an effective expansion of the transmission channel is realized by constructing an intelligent optical fiber distribution machine cluster, and through an optimized routing algorithm, the efficient implementation of the optical fiber routing in the intelligent optical fiber distribution machine cluster is ensured, and the load balance is taken into account to improve the performance of the entire intelligent optical fiber distribution machine cluster.

[0060] Based on the same concept of the present invention, as shown in the attached Figure 6 As shown in the figure, the structure of an electronic device 600 provided in an embodiment of this application, the electronic device 600 includes: at least one processor 601, at least one network interface 604 or other user interfaces 603, a memory 605, and at least one communication bus 602. The communication bus 602 is used to realize the connection and communication between these components. The electronic device 600 optionally includes a user interface 603, including a display (for example, a touch screen, an LCD, a CRT, a holographic imaging or a projector, etc.), a keyboard or a pointing device (for example, a mouse, a trackball, a touchpad or a touch screen, etc.).

[0061] The memory 605 may include a read-only memory and a random access memory, and provide instructions and data to the processor 601. A part of the memory 605 may also include a non-volatile random access memory (NVRAM).

[0062] In some embodiments, the memory 605 stores the following elements, executable modules or data structures, or subsets thereof, or extended sets thereof: The operating system 6051, which contains various system programs for implementing various basic services and processing hardware-based tasks; The application program module 6052, which contains various application programs, such as a launcher, a MediaPlayer, a Browser, etc., for implementing various application services.

[0063] In the embodiments of the present application, by calling the programs or instructions stored in the memory 605, the processor 601 is configured to execute the steps of a routing and scheduling method for an intelligent optical fiber distribution machine cluster.

[0064] The present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is run by a processor, it executes the steps in a routing and scheduling method for an intelligent optical fiber distribution machine cluster.

[0065] Specifically, the storage medium can be a general storage medium, such as a removable disk, a hard disk, etc. When the computer program on the storage medium is run, it can solve the problems of expanding the transmission channel and efficient routing and scheduling when the number of intelligent optical fiber distribution ports is insufficient.

[0066] In the embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of units is only a logical function division, and there may be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed couplings or direct couplings or communication connections to each other can be through some communication interfaces. The indirect couplings or communication connections of devices or units can be electrical, mechanical or other forms.

[0067] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0068] In addition, each functional unit in the embodiments provided in this application may be integrated into a processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.

[0069] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in various embodiments of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0070] Finally, it should be noted that the above embodiments are only specific implementation manners of this application, used to illustrate the technical solution of this application, and are not intended to limit it. The protection scope of this application is not limited thereto. Although this application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that any person skilled in the art within the technical scope disclosed in this application can still modify the technical solutions recorded in the foregoing embodiments, or can easily think of changes, or make equivalent replacements for some of the technical features; and these modifications, changes, or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of this application. All should be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A routing scheduling method for an intelligent optical fiber wiring machine cluster, characterized in that: The method comprises the following steps: Build an intelligent fiber optic wiring machine cluster based on multiple intelligent fiber optic wiring machines; Determine whether the network type of the intelligent optical fiber distribution machine cluster is a centralized control cluster network or a non-centrally controlled cluster network; if it is a centralized control cluster network, determine its central control node; For the centralized control cluster network, the bidirectional BFS traversal algorithm is combined with the outward divergent traversal from the central control node to analyze the internal routing of the intelligent fiber optic wiring machine cluster and obtain the fiber optic routing path. A fiber core movement instruction is generated according to the optical fiber routing path, and an intelligent optical fiber wiring machine is controlled to perform plugging and unplugging operations on corresponding optical fibers.

2. According to claim 1, a routing scheduling method for an intelligent optical fiber distribution machine cluster is characterized in that: The step of determining whether the network type of the intelligent optical fiber distribution machine cluster is a centralized control cluster network or a non-centrally controlled cluster network comprises the following steps: Obtain the physical connection relationship of the external port of each node in the intelligent fiber optic wiring machine cluster and build a connectivity matrix; Initialize the central control evaluation value of each node in the intelligent optical fiber distribution machine cluster according to the connection status of each node with other nodes, and form a central control initialization evaluation value vector of all nodes in the intelligent optical fiber distribution machine cluster; Iterating the central control degree initialization evaluation value vector using the connectivity matrix to obtain the central control degree evaluation value of each node in the intelligent optical fiber distribution machine cluster; If there is a node in the intelligent fiber optic wiring machine cluster whose central control evaluation value is greater than the preset threshold, the network type of the intelligent fiber optic wiring machine cluster is determined to be a centrally controlled cluster network. If not, the network type of the intelligent fiber optic wiring machine cluster is determined to be a non-centrally controlled cluster network.

3. According to claim 2, a routing scheduling method for an intelligent optical fiber distribution machine cluster is characterized in that: in, The sum of the central control evaluation values ​​of all nodes in the intelligent fiber optic wiring machine cluster is 1.

4. According to claim 2, a routing scheduling method for an intelligent optical fiber distribution machine cluster is characterized in that: The method of iterating the center control degree initialization evaluation value vector by using the connectivity matrix comprises the following steps: The iteration end condition is set based on the difference in the evaluation value of the central control degree of each node in the results of two adjacent iterations.

5. The routing scheduling method of the intelligent optical fiber distribution machine cluster according to claim 2, characterized in that: The central control node of the intelligent optical fiber distribution machine cluster is determined in the following manner, including the following steps: The nodes whose central control degree evaluation values ​​are greater than a preset threshold are used as candidate central control nodes of the intelligent optical fiber distribution machine cluster, and the number of the candidate central control nodes is determined; If the number of the candidate central control nodes is greater than 1, the candidate central control node with the largest central control degree evaluation value is selected as the final central control node of the intelligent fiber optic wiring machine cluster; or the business load rate of each of the candidate central control nodes is calculated, and the candidate central control node with the smallest business load rate is selected as the final central control node of the intelligent fiber optic wiring machine cluster.

6. The routing scheduling method of the intelligent optical fiber distribution machine cluster according to claim 1, characterized in that: For the centralized control cluster network, the internal routing of the intelligent optical fiber distribution machine cluster is analyzed by combining the bidirectional BFS traversal algorithm with the outward divergent traversal of the central control node to obtain the optical fiber routing path, including the following steps: Starting from the start node, the end node and the central control node respectively, search for directly connected nodes and idle core port connection sequences, and store the corresponding data in the forward route set, the reverse route set and the central control route set; wherein, for the dual-core service, the number of idle core port connection sequences between nodes is at least 2; Uniformly define the data storage structure of the forward route set, the reverse route set and the central control route set, and initialize them; According to the intersection of nodes in the forward route set, the reverse route set and the central control route set, the corresponding fiber core port binary set is spliced ​​to obtain a fiber routing path.

7. A routing scheduling method for an intelligent optical fiber distribution machine cluster according to claim 6, characterized in that: The method further comprises the following steps: For non-centrally controlled cluster networks, a bidirectional BFS traversal algorithm is used to analyze the internal routing of the intelligent fiber optic wiring machine cluster from the start node to the end node to obtain the fiber optic routing path.

8. A routing scheduling device for an intelligent optical fiber wiring machine cluster, characterized in that: The device comprises: A building module for building an intelligent optical fiber wiring machine cluster based on multiple intelligent optical fiber wiring machines; A judgment module is used to judge whether the network type of the intelligent optical fiber distribution machine cluster is a centralized control cluster network or a non-centrally controlled cluster network; wherein, if it is a centralized control cluster network, determine its central control node; The analysis module is used to analyze the internal routing of the intelligent optical fiber distribution machine cluster by combining the bidirectional BFS traversal algorithm with the outward divergent traversal of the central control node for the centralized control cluster network, and obtain the optical fiber routing path; The execution module is used to generate a fiber core movement instruction according to the optical fiber routing path, and control the intelligent optical fiber wiring machine to perform plugging and unplugging operations on the corresponding optical fiber.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the steps of the routing scheduling method for an intelligent optical fiber distribution machine cluster as described in any one of claims 1 to 7 are performed.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, executes the steps of a routing scheduling method for an intelligent optical fiber distribution machine cluster as described in any one of claims 1 to 7.

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