Collaborative mapping method and device based on node evaluation result

Abstract

The invention relates to the technical field of communication, in particular to a collaborative mapping method and device based on a node evaluation result, and the method comprises the steps: obtaining a virtual network topology structure corresponding to a current network slice demand; generating a node mapping sequence between the virtual nodes and the physical nodes in the virtual network topological structure based on all the virtual nodes and all the physical nodes in the current network slice requirement; generating a candidate physical node set and a candidate physical link set meeting certain conditions by combining network configuration information and a node mapping sequence required by the current network slice; and based on the candidate physical node set and the candidate physical link set, utilizing a certain optimization objective function to cooperatively map virtual nodes and virtual links in the virtual network topology structure. Therefore, the problems that in the related technology, the physical network resources cannot be utilized to the maximum extent while the network slicing requirement cannot be met, and load balancing and optimal path allocation cannot be achieved are solved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a collaborative mapping method and device based on node evaluation results. Background Art

[0002] Virtualization collaborative mapping technology is an effective way to eliminate network rigidity and is also one of the important contents of network virtualization research. How to design a reasonable mapping solution to meet resource requirements and improve the success rate of mapping is very important.

[0003] In the related technology, the mapping order of virtual nodes and virtual links can be divided and classified according to the characteristic attributes of virtual nodes and virtual links, and then the mapping sequence of virtual nodes and virtual links can be determined, and the transmission rate and corresponding modulation format of the selected path can be determined according to the bandwidth requirements of the virtual link to complete the collaborative mapping; the first delay resource sensitivity can also be calculated according to the virtual link, and the second delay resource sensitivity can be calculated according to the physical link, and mapping can be performed according to the first delay resource sensitivity and the second delay resource sensitivity to achieve the purpose of improving resource efficiency and network resource utilization.

[0004] However, related technologies cannot maximize the use of physical network resources while meeting network slicing requirements, and cannot achieve load balancing and optimal path allocation, which urgently needs improvement. Summary of the invention

[0005] The present application provides a collaborative mapping method and device based on node evaluation results to solve the problems in related technologies such as failure to maximize the use of physical network resources while meeting network slicing requirements, and failure to achieve load balancing and optimal path allocation.

[0006] The first aspect of the present application provides a collaborative mapping method based on node evaluation results, and the method includes the following steps: obtaining a virtual network topology structure corresponding to the current network slicing requirement; generating a node mapping sequence between virtual nodes and physical nodes in the virtual network topology structure based on all virtual nodes and all physical nodes in the current network slicing requirement; generating a candidate physical node set and a candidate physical link set that meet preset conditions in combination with the network configuration information of the current network slicing requirement and the node mapping sequence; based on the candidate physical node set and the candidate physical link set, collaboratively mapping the virtual nodes and virtual links in the virtual network topology structure using a preset optimization objective function.

[0007] Optionally, in one embodiment of the present application, obtaining the virtual network topology structure corresponding to the current network slicing demand includes: obtaining the service quality requirements configured in the service configuration file corresponding to the current network slicing demand based on the current network slicing demand; generating target parameters of the virtual network topology structure based on the service quality requirements; and generating the virtual network topology structure by combining the target parameters and the adjacency matrix.

[0008] Optionally, in one embodiment of the present application, the node mapping sequence between virtual nodes and physical nodes in the virtual network topology structure is generated based on all virtual nodes and all physical nodes in the current network slicing requirements, including: using a pre-built AEC-VIKOR (Adversarial Extract Champion Vlse Kriterijumska Optimizacija I Kompromisno Resenje, adversarial extraction and optimization method of multi-criteria compromise solution sorting method) mechanism to evaluate the importance of the virtual nodes and the physical nodes, so as to calculate the virtual importance value corresponding to the virtual node and the physical importance value corresponding to the physical node according to the importance evaluation result; combining the virtual importance value and the physical importance value to determine the initial root node of the virtual network topology structure; alternating BFS (Breadth-First Search)-DFS (Depth-First Search) on the virtual network topology structure. Search, depth-first search) to obtain the local path of each layer of virtual network topology in the virtual network topology structure; after optimizing the initial root node through the local path, the virtual importance value and the physical importance value, determine the final root node, and use the root node to generate a node mapping sequence.

[0009] Optionally, in one embodiment of the present application, the importance of the virtual node and the physical node is evaluated using a pre-built AEC-VIKOR mechanism to calculate the virtual importance value corresponding to the virtual node and the physical importance value corresponding to the physical node according to the importance evaluation result, including: calculating the virtual decision matrix corresponding to the virtual node and the physical decision matrix corresponding to the physical node based on the importance attribute values ​​of the virtual node and the physical node; calculating the virtual expected value and virtual defect value corresponding to the virtual node and the physical expected value and physical defect value corresponding to the physical node based on the virtual decision matrix and the physical decision matrix; combining the virtual expected value, the virtual defect value, the physical expected value and the physical defect value, and calculating the virtual importance value and the physical importance value through preset virtual compromise coefficient and physical compromise coefficient weights.

[0010] Optionally, in one embodiment of the present application, the network configuration information combined with the current network slicing requirements and the node mapping sequence are used to generate a candidate physical node set and a candidate physical link set that meet preset conditions, including: combining the network configuration information combined with the current network slicing requirements and the node mapping sequence to screen out the initial candidate physical node set corresponding to the virtual node that meets the geographic network domain constraints and resource constraints; calculating the load value of each initial candidate physical node in the initial candidate physical node set, and obtaining the candidate physical node set and the initial candidate physical link set that meet the preset conditions based on the load value; according to the physical network and the initial candidate physical link set, obtaining a target physical link set that meets the target bandwidth constraints and target resource constraints; based on the target physical link set, establishing a comprehensive evaluation function with bandwidth, delay, and load balancing as indicators, and using the comprehensive evaluation function to evaluate the target physical links in the target physical link set, so as to select a candidate physical link set based on the comprehensive evaluation value.

[0011] A second aspect of the present application provides a collaborative mapping device based on node evaluation results, the device comprising: an acquisition module, used to acquire a virtual network topology structure corresponding to a current network slicing requirement; a first generation module, used to generate a node mapping sequence between virtual nodes and physical nodes in the virtual network topology structure based on all virtual nodes and all physical nodes in the current network slicing requirement; a second generation module, used to combine the network configuration information of the current network slicing requirement and the node mapping sequence to generate a candidate physical node set and a candidate physical link set that meet preset conditions; a collaborative mapping module, used to collaboratively map the virtual nodes and virtual links in the virtual network topology structure based on the candidate physical node set and the candidate physical link set using a preset optimization objective function.

[0012] Optionally, in one embodiment of the present application, the acquisition module includes: a first generation unit, used to obtain the service quality requirements configured in the service profile corresponding to the current network slice requirement based on the current network slice requirement; a second generation unit, used to generate target parameters of the virtual network topology structure based on the service quality requirements; and a third generation unit, used to generate the virtual network topology structure in combination with the target parameters and the adjacency matrix.

[0013] Optionally, in one embodiment of the present application, the first generation module includes: a first calculation unit, used to use a pre-built AEC-VIKOR mechanism to perform importance evaluation on the virtual node and the physical node, so as to calculate the virtual importance value corresponding to the virtual node and the physical importance value corresponding to the physical node according to the importance evaluation result; a determination unit, used to determine the initial root node of the virtual network topology structure in combination with the virtual importance value and the physical importance value; an acquisition unit, used to alternately perform BFS-DFS on the virtual network topology structure to obtain the local path of each layer of virtual network topology in the virtual network topology structure; a fourth generation unit, used to optimize the initial root node through the local path, the virtual importance value and the physical importance value, determine the final root node, and use the root node to generate a node mapping sequence.

[0014] Optionally, in one embodiment of the present application, the calculation unit includes: a first calculation subunit, used to calculate the virtual decision matrix corresponding to the virtual node and the physical decision matrix corresponding to the physical node based on the importance attribute values ​​of the virtual node and the physical node; a second calculation subunit, used to calculate the virtual expected value and the virtual defect value corresponding to the virtual node and the physical expected value and the physical defect value corresponding to the physical node based on the virtual decision matrix and the physical decision matrix; a third calculation subunit, used to combine the virtual expected value, the virtual defect value, the physical expected value and the physical defect value, and calculate the virtual importance value and the physical importance value through preset virtual compromise coefficient and physical compromise coefficient weights.

[0015] Optionally, in one embodiment of the present application, the second generation module includes: a screening unit, used to combine the network configuration information of the current network slicing requirement and the node mapping sequence to screen out the initial candidate physical node set corresponding to the virtual node that meets the geographic network domain constraints and resource constraints; a second calculation unit, used to calculate the load value of each initial candidate physical node in the initial candidate physical node set, and obtain a candidate physical node set and an initial candidate physical link set that meet preset conditions based on the load value; a fifth generation unit, used to obtain a target physical link set that meets the target bandwidth constraints and target resource constraints based on the physical network and the initial candidate physical link set; a third calculation unit, used to establish a comprehensive evaluation function with bandwidth, delay, and load balancing as indicators based on the target physical link set, and use the comprehensive evaluation function to evaluate the target physical links in the target physical link set, so as to select a candidate physical link set based on the comprehensive evaluation value.

[0016] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the collaborative mapping method based on node evaluation results as described in the above embodiment.

[0017] The fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program. When the program is executed by a processor, it implements the above-mentioned collaborative mapping method based on node evaluation results.

[0018] The fifth aspect of the present application provides a computer program product, including a computer program, which, when executed, implements the above-mentioned collaborative mapping method based on node evaluation results.

[0019] The embodiment of the present application can generate a node mapping sequence between virtual nodes and physical nodes based on the virtual network topology structure required by the current network slice, and combine the network configuration information and node mapping sequence required by the current network slice to obtain a candidate physical node set and a candidate physical link set that meet certain conditions, and then use a certain optimization objective function to perform collaborative mapping of virtual nodes and virtual links, actively integrate network resources, further provide the probability of network slice deployment, optimize load balancing, and achieve optimal path allocation. Therefore, the problem of not being able to maximize the use of physical network resources while meeting network slicing requirements and not being able to achieve load balancing and optimal path allocation in the related technology is solved.

[0020] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0022] Figure 1 A flowchart of a collaborative mapping method based on node evaluation results provided according to an embodiment of the present application;

[0023] Figure 2 A flowchart of obtaining a virtual network topology structure according to an embodiment of the present application;

[0024] Figure 3 A flowchart of generating a node mapping sequence according to an embodiment of the present application;

[0025] Figure 4 A flowchart of BFS-DFS provided according to an embodiment of the present application;

[0026] Figure 5 A flowchart of an AEC-VIKOR mechanism provided according to an embodiment of the present application;

[0027] Figure 6 A flowchart of generating a candidate physical node set and a candidate physical link set according to an embodiment of the present application;

[0028] Figure 7 A block diagram of a collaborative mapping device based on node evaluation results provided according to an embodiment of the present application;

[0029] Figure 8 It is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0030] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0031] The following describes the collaborative mapping method and device based on the node evaluation results of the embodiment of the present application with reference to the accompanying drawings. In view of the problem mentioned in the above background technology that it is not possible to maximize the use of physical network resources while meeting the network slicing requirements, and it is not possible to achieve load balancing and optimal path allocation, the present application provides a collaborative mapping method based on node evaluation results. In this method, a node mapping sequence between virtual nodes and physical nodes can be generated based on the virtual network topology structure required by the current network slicing, and the network configuration information and node mapping sequence required by the current network slicing can be combined to obtain a set of candidate physical nodes and a set of candidate physical links that meet certain conditions, and then a certain optimization objective function is used to perform collaborative mapping of virtual nodes and virtual links, actively integrate network resources, further provide the probability of network slicing deployment, optimize load balancing, and achieve optimal path allocation. As a result, the problem that the physical network resources cannot be maximized while meeting the network slicing requirements, and load balancing and optimal path allocation cannot be achieved in the related technology is solved.

[0032] Specifically, Figure 1 The present invention provides a flowchart of a collaborative mapping method based on node evaluation results according to an embodiment of the present application.

[0033] like Figure 1 As shown, the collaborative mapping method based on node evaluation results includes the following steps:

[0034] In step S101, the virtual network topology structure corresponding to the current network slicing requirement is obtained.

[0035] As a possible implementation method, the embodiment of the present application can generate a virtual network topology structure corresponding to the current network slicing requirements based on the business and service quality requirements. Specifically, the embodiment of the present application can design and implement the virtual network topology required by the current network slicing by aggregating business and service quality requirements.

[0036] Optionally, in one embodiment of the present application, a virtual network topology structure corresponding to a current network slicing requirement is obtained, including: obtaining a service quality requirement configured in a service configuration file corresponding to the current network slicing requirement based on the current network slicing requirement; generating target parameters of the virtual network topology structure based on the service quality requirement; and generating a virtual network topology structure by combining the target parameters and an adjacency matrix.

[0037] In some embodiments, the process of obtaining the virtual network topology structure in the embodiment of the present application is as follows: Figure 2 As shown, its main contents are:

[0038] Step S201: Obtaining service quality requirements.

[0039] Among them, in the process of generating the current network slicing demand instance, the embodiment of the present application analyzes and aggregates the service quality requirements configured in the service configuration file provided by the slice service user. It should be noted that the service quality requirements in the embodiment of the present application may include but are not limited to key service quality requirements such as bandwidth requirements, latency requirements, and computing power requirements. They can be specifically set by technical personnel in this field according to actual conditions, and this application does not impose specific restrictions.

[0040] Step S202: converting the service quality requirements into target parameters of the virtual network topology structure.

[0041] Among them, in the design stage of the virtual network topology structure, the embodiment of the present application can convert the service quality requirements into the target parameters of the virtual network topology structure. It should be noted that the target parameters of the embodiment of the present application can include but are not limited to the computing resource requirements of the virtual node, the bandwidth requirements of the virtual link, etc., which can be specifically set by technical personnel in the field according to actual conditions, and this application does not impose specific restrictions.

[0042] Further, in the embodiment of the present application, N v A set of virtual nodes representing the virtual network topology. In each set of virtual nodes, a single virtual node i is represented by express, Each virtual node Represents a virtual network function or virtual network device in the current network slice requirement. The computing resource requirement of the virtual node can be expressed as a vector R v , which means the amount of computing resources required by the virtual node. Represents a virtual node The amount of computing resources required.

[0043] Step S203: introducing the adjacency matrix.

[0044] It can be understood that the embodiment of the present application uses the connection relationship between virtual nodes to form a global topological structure required by a single network slice, and introduces the adjacency matrix E v Represents a virtual node in a virtual network topology Connection relationship, virtual node and virtual nodes The virtual link is represented as in, It represents the bandwidth resources required by the virtual link between virtual node i and virtual node j, that is, the bandwidth demand, which can be calculated based on the expected data traffic and service quality requirement bandwidth demand between the two nodes.

[0045] Step S204: Generate a virtual network topology structure.

[0046] It can be understood that the embodiment of the present application can design and implement the virtual network topology structure required by the current network slicing based on the business and service quality requirements, which can be represented by but not limited to an undirected weighted graph, which can be represented as: G v =(N v ,E v ,R v ,B v ,D v ),v≤K.

[0047] In step S102, based on all virtual nodes and all physical nodes in the current network slicing requirements, a node mapping sequence between virtual nodes and physical nodes in the virtual network topology structure is generated.

[0048] It can be understood that the embodiments of the present application can use the pre-built AEC-VIKOR mechanism to separately evaluate the importance of all virtual nodes and all physical nodes in the current network slicing requirement subnet.

[0049] In addition, the embodiment of the present application can adopt BFS-DFS combined with an intelligent optimization strategy to dynamically adjust all virtual nodes in the virtual network topology structure.

[0050] As a possible implementation method, the AEC-VIKOR mechanism of the embodiment of the present application can respectively evaluate the importance of all virtual nodes and all physical nodes in the current network slicing requirement subnet, and use BFS-DFS traversal sorting for the virtual nodes in the current network slicing requirement, thereby obtaining a node mapping sequence between virtual nodes and physical nodes.

[0051] Optionally, in one embodiment of the present application, based on all virtual nodes and all physical nodes in the current network slicing requirements, a node mapping sequence between virtual nodes and physical nodes in the virtual network topology structure is generated, including: using a pre-built AEC-VIKOR mechanism to perform importance evaluation on virtual nodes and physical nodes, so as to calculate the virtual importance value corresponding to the virtual node and the physical importance value corresponding to the physical node according to the importance evaluation result; combining the virtual importance value and the physical importance value to determine the initial root node of the virtual network topology structure; performing BFS-DFS alternately on the virtual network topology structure to obtain the local path of each layer of virtual network topology in the virtual network topology structure; after optimizing the initial root node through the local path, virtual importance value and physical importance value, determine the final root node, and use the root node to generate a node mapping sequence.

[0052] In some embodiments, the process of generating a node mapping sequence in the embodiment of the present application is as follows: Figure 3 As shown, its main contents are:

[0053] Step S301: Greedily sort all network slice demand subnets based on service quality requirements.

[0054] It can be understood that the network controller of the embodiment of the present application can greedily sort all network slice demand subnets based on the quality of service requirements, specifically:

[0055] The distribution of queues in the network controller of the embodiment of the present application is determined by the service mode and the service quality requirement. Assuming that the set of network slice requirements arriving is K={1,2,...,K}, v∈K, the service quality requirement of its resource requirements is calculated, and the calculation formula can be but is not limited to:

[0056]

[0057] Among them, R t is the total computing resources required by the nodes in the network slicing requirements, B t is the total bandwidth required by the network slice demand link, β is the weighted parameter of the relative weight of link bandwidth and node resources, It connects two virtual nodes. and If and If there is a link requirement between on the contrary,

[0058] Furthermore, the embodiment of the present application can use the NQ value to greedily sort all network slicing requirements, arranging them from large to small, to enhance their priority and service quality, so as to improve the slicing success rate.

[0059] Step S302: Use the pre-built AEC-VIKOR mechanism to evaluate the importance of virtual nodes and physical nodes.

[0060] Among them, in the embodiment of the present application, an AEC-VIKOR mechanism is proposed, which comprehensively considers the topological attributes and resource attributes of the node and comprehensively evaluates the virtual and physical nodes in the node mapping stage. This evaluation ensures that important nodes are selected first to maximize the reasonable allocation and utilization of resources. The content of the AEC-VIKOR mechanism is described in detail below and will not be repeated here.

[0061] Step S303: alternately perform BFS-DFS on the virtual network topology structure to generate a node mapping sequence.

[0062] In the embodiment of the present application, the virtual nodes and physical nodes in the network topology are deeply evaluated, and the importance value T of the virtual nodes in the network topology is evaluated by combining multi-dimensional parameter analysis such as importance value and resource weight. i and the physical node importance value T s Finally, BFS-DFS is used to dynamically adjust the virtual network topology nodes in the current network slicing requirements, thereby optimizing the multi-level node mapping sequence in the node mapping stage.

[0063] For example, Figure 4 The flow shown describes the BFS-DFS process, the main contents of which are:

[0064] Step S401: multi-objective evaluation.

[0065] Step S402: Dynamically adjust the search strategy.

[0066] Step S403: root node strategy selection.

[0067] Step S404: BFS queue initialization.

[0068] Step S405: traverse directly connected nodes layer by layer.

[0069] Step S406: Calculate load balancing and topology consistency.

[0070] Step S407: Put the nodes that meet the conditions into the BFS queue.

[0071] Step S408: DFS stack initialization.

[0072] Step S409: Search for DFS stack direct path traversal branches.

[0073] Step S410: Evaluate resource utilization and compare with the global optimal solution.

[0074] Step S411: branch backtracking.

[0075] Step S412: Determine whether the node is a target.

[0076] Step S413: Output the queue result.

[0077] It can be understood that in the initial stage, the embodiment of the present application can use a heuristic selection mechanism to determine the initial root node of BFS-DFS according to the importance value and connection weight of the node in the network topology, and put it into the BFS queue and DFS stack respectively. At the same time, the algorithm dynamically maintains a node importance priority queue to ensure that each step of selection can maximize the local optimal solution.

[0078] Furthermore, in the specific search process, the embodiment of the present application alternately extracts nodes from the BFS queue and the DFS stack. BFS is responsible for hierarchical traversal to achieve more network coverage globally, while DFS focuses on local depth first, mining potential resource-maximizing node mapping paths, and solving bottlenecks in local path resource utilization. Each time a node is taken out from BFS or DFS, it is first determined whether the node meets the target mapping condition, that is, whether it is a direct child node or an indirectly connected node of the current root node. Node judgment is based on a variety of strategies, including its importance in the virtual topology map, its matching degree with the physical node, resource availability, etc.

[0079] It should be noted that the BFS-DFS in the embodiment of the present application can also be described as:

[0080] Initial root node selection: According to the virtual node importance ranking, find the virtual node with the smallest comprehensive ranking value from the virtual network topology map and use it as the initial root node of BFS-DFS.

[0081] Multi-strategy search alternation: Use BFS for breadth traversal to ensure wide coverage of each layer, and then switch to DFS for depth search to explore possible local optimal paths. At the same time, for each layer of nodes in BFS and DFS, the AEC-VIKOR mechanism is called to sort the nodes of this layer by combining multiple parameters such as node importance value, network load, connection quality, resource allocation, etc. The sorting results are arranged in ascending order to ensure that the most valuable nodes are mapped first.

[0082] Dynamic optimization adjustment: During the search process, the algorithm dynamically monitors the network topology and resource utilization, and adaptively adjusts the BFS-DFS alternation frequency. When the local path presents a resource bottleneck or important nodes are densely populated, DFS is used first to find the local optimal solution; when the node correlation is strong within the global scope, BFS is turned to for global breadth expansion to ensure full network coverage.

[0083] Multi-level iterative optimization: Find the minimum Virtual node for value As the root node of BFS-DFS; traverse G using the joint algorithm v Topology, each layer of BFS-DFS calls the AEC-VIKOR mechanism according to The values ​​are sorted in ascending order and the sorted results are returned to N v ', until all layers have been executed.

[0084] In the BFS-DFS of the embodiment of the present application, BFS can find the shortest path in the network quickly, while DFS can go deep into the deepest part of each branch, which is helpful to explore complex node configurations. By cross-linking the use of BFS and DFS, combining the advantages of the two, the breadth of the search can be effectively increased without sacrificing the depth of the search. In the early stage of generating candidate nodes, BFS is used to perform a quick shallow search to locate potential areas, and then DFS is used to explore the specific node mapping scheme in depth. This strategy can effectively reduce the computing time, especially when facing large-scale complex network structures across multiple domains. At the same time, the use of cross-linking algorithms can more accurately evaluate and utilize network resources. BFS can quickly identify resource-rich areas and quickly utilize loads when small batches of network slices are required. When the demand for network slices and the number of slices continue to increase, DFS further explores how to effectively configure virtual network functions in these areas, thereby searching for more node combinations that meet the mapping conditions with a higher probability, improving mapping efficiency and increasing the possibility of approaching the global optimal solution.

[0085] Optionally, in one embodiment of the present application, a pre-built AEC-VIKOR mechanism is used to perform an importance evaluation on virtual nodes and physical nodes, so as to calculate the virtual importance value corresponding to the virtual node and the physical importance value corresponding to the physical node according to the importance evaluation results, including: calculating the virtual decision matrix corresponding to the virtual node and the physical decision matrix corresponding to the physical node based on the importance attribute values ​​of the virtual node and the physical node; calculating the virtual expected value and the virtual defect value corresponding to the virtual node and the physical expected value and the physical defect value corresponding to the physical node based on the virtual decision matrix and the physical decision matrix; combining the virtual expected value, the virtual defect value, the physical expected value and the physical defect value, and calculating the virtual importance value and the physical importance value through the preset virtual compromise coefficient and the physical compromise coefficient weights.

[0086] In some embodiments, the embodiment of the present application uses the AEC-VIKOR mechanism to evaluate the importance of virtual nodes and physical nodes to obtain corresponding importance values. The process is as follows: Figure 5 As shown, the main contents are:

[0087] Step S501: Based on the importance attribute values ​​of the virtual nodes, a normalized virtual decision matrix is ​​obtained.

[0088] It should be noted that the embodiment of the present application can execute the network slicing requirement slicing process one by one according to the greedy sorting result of the service quality requirement, setting G v Resource view of the slice requirement for the vth network slice requirement.

[0089] Furthermore, the embodiment of the present application uses the importance attribute value of the virtual node to obtain a normalized virtual decision matrix D, which can be expressed as but not limited to:

[0090]

[0091] b ij =w j ·a ij ,i=1,2,L,N;j=1,2,L,L,

[0092] Among them, N represents the number of nodes in the network topology, L represents the number of evaluation indicators of the node, and a ij Represents the i-th virtual node The value of the relative evaluation index standard j, w j Represents the standard weight coefficient. The value range of the weight coefficient is [0,1], and the sum of all weight coefficients is 1.

[0093] In the embodiment of the present application, the criterion j may include but is not limited to the resource importance and topological importance of the node, and L node attribute features are set, which may include but is not limited to the resource importance value R of the node. I , the degree centrality value D of the node C , the closeness centrality value C of the node C , betweenness centrality B C , eigenvector centrality E C et al., Graph Element Analysis G A wait.

[0094] Step S502: Calculate the virtual expected value and virtual defect value of the virtual node.

[0095] Among them, the embodiment of the present application can respectively use the calculation formulas of virtual expected value and virtual defect value to calculate the virtual node The virtual expected value S i and virtual defect value R i , which can be expressed as but not limited to:

[0096]

[0097] in, and are the positive and negative ideal solutions of D respectively.

[0098] Step S503: Calculate the virtual importance value of the virtual node according to the virtual expected value and the virtual defect value.

[0099] Among them, the virtual importance value T in the embodiment of the present application is i The calculation formula can be but is not limited to:

[0100]

[0101] in, is the compromise coefficient.

[0102] Step S504: fitting the virtual compromise coefficient using the intercept method.

[0103] It can be understood that the embodiment of the present application can use the intercept method to fit the virtual compromise coefficient The value of , the calculation process can be but is not limited to:

[0104] make but Conclusion

[0105]

[0106] Then find out each virtual node in the virtual network topology The corresponding virtual importance value T i .

[0107] Step S505: Obtain the node sequence of the virtual node according to the virtual importance value.

[0108] Among them, the embodiment of the present application can be based on the obtained value, split the decision interval, and list the virtual importance value T of each decision interval i , and sort them from small to large, perform clustering feature analysis, select the node with the highest probability in each decision interval as the feature node of each interval, list the final node sorting, and then get the node sequence of the virtual node.

[0109] Step S506: Calculate the physical importance value of the physical node.

[0110] It is understandable that the embodiment of the present application can obtain the physical network topology G P Topology information, for each physical node in the physical network topology Repeat steps S501 to S503 to calculate each physical node in the physical network topology. The physical importance value T s , its calculation formula can be expressed as but not limited to:

[0111]

[0112] The beneficial effects of the AEC-VIKOR mechanism in the embodiment of the present application are: comprehensively evaluating the support capabilities of physical network nodes for network slice virtual nodes, achieving node optimization orchestration required by network slicing, and improving the utilization rate of slice network virtual resources.

[0113] In step S103, the network configuration information and node mapping sequence required by the current network slicing are combined to generate a set of candidate physical nodes and a set of candidate physical links that meet preset conditions.

[0114] In the actual implementation process, the embodiment of the present application can screen virtual nodes that meet the network configuration information and node mapping sequence required by the current network slice. Required physical node G P , and generate a candidate physical link set.

[0115] Among them, certain conditions can be understood as virtual node mapping conditions required by the current network slice, etc., which can be set by technicians in this field according to actual conditions, and this application does not make specific restrictions.

[0116] Optionally, in one embodiment of the present application, in combination with the network configuration information and node mapping sequence required by the current network slicing, a candidate physical node set and a candidate physical link set that meet preset conditions are generated, including: in combination with the network configuration information and node mapping sequence required by the current network slicing, an initial candidate physical node set corresponding to virtual nodes that meet geographic network domain constraints and resource constraints is screened out; the load value of each initial candidate physical node in the initial candidate physical node set is calculated, and based on the load value, a candidate physical node set and an initial candidate physical link set that meet preset conditions are obtained; based on the physical network and the initial candidate physical link set, a target physical link set that meets the target bandwidth constraint and the target resource constraint is obtained; based on the target physical link set, a comprehensive evaluation function with bandwidth, delay, and load balancing as indicators is established, and the target physical links in the target physical link set are evaluated using the comprehensive evaluation function to select a candidate physical link set based on the comprehensive evaluation value.

[0117] It can be understood that, in the embodiment of the present application, for each virtual node v i , in the physical node set P = {p1,p2,…,p m}, filter out the initial candidate physical node set that meets the geographic network domain constraints and resource constraints And calculate the load value of each initial candidate physical node to obtain a set of candidate physical nodes that meet certain conditions.

[0118] Furthermore, the embodiment of the present application performs joint optimization mapping of virtual nodes and physical nodes based on a candidate physical node set and relying on a load balancing strategy.

[0119] Among them, certain conditions can be set by technicians in this field according to actual conditions, and this application does not impose specific restrictions.

[0120] It should be noted that the embodiment of the present application proposes a more complex cross-domain mapping algorithm based on network slicing requirements, network configuration and resource constraints, aiming to collaboratively complete the efficient mapping of virtual nodes and virtual links by combining the KSP (K-Shortest Path) algorithm, load balancing strategy and multi-constraint optimization model. The optimization model comprehensively considers multiple constraints such as bandwidth, latency and resource load to ensure the efficiency and stability of the mapping process.

[0121] In some embodiments, the process of generating a candidate physical node set and a candidate physical link set in the embodiment of the present application is as follows: Figure 6 As shown, the main contents are:

[0122] Step S601: Screen out an initial set of candidate physical nodes.

[0123] It can be understood that, first, the embodiment of the present application defines a binary variable Used to describe the physical node p j Whether the virtual node v is satisfied i The geographic network domain constraints can be expressed as, but not limited to:

[0124]

[0125] Further, in the embodiment of the present application, if v i is the root node in the BFS search tree, then the load of the physical node is calculated to filter and select the physical node with the smallest load At this time, the node mapping needs to meet the following computing resource constraints: in, Represents the physical node p j The remaining computing resources, Represents a virtual node v i computing resource requirements.

[0126] If v i It is a non-root node, and its mapping needs to be with its parent node v in the BFS search tree p(i) and all mapped directly connected virtual nodes v i,j Keep it consistent. Define each node v i,j The corresponding physical node is p i,j , by constructing a neighbor physical node set N(pi,j ), get the initial candidate physical node set: C i ∈N(p i,j ), where N(p i,j ) represents the physical node p i,j The set of neighbor nodes. The initial candidate physical node set C i The resource constraints of the node map must be satisfied, namely:

[0127]

[0128] Step S602: Generate a candidate physical node set.

[0129] It can be understood that, in the embodiment of the present application, after obtaining the initial candidate physical node set C i Afterwards, these nodes can be sorted according to certain conditions based on the load balancing strategy. In the embodiment of the present application, the load value of each initial candidate physical node can be calculated by the following formula, which can be expressed as but not limited to:

[0130]

[0131] in, Indicates the current physical node p j The remaining computing resources. Therefore, the node load L(p j ) is smaller, which means the node resources are more sufficient and the load is lower. According to the load value, the initial candidate physical node set C is sorted from small to large. i Sort the physical nodes in to form a candidate physical node set C i ', which can be expressed as but not limited to:

[0132]

[0133] Step S603: Generate a target physical link set.

[0134] After the virtual node mapping is completed, for each pair of mapped virtual nodes (v i ,v j ), the embodiment of the present application can find the shortest path that meets the target bandwidth constraint in the physical network. Here, the embodiment of the present application can use the KSP algorithm to search from the physical node arrive The K shortest paths between them are the target physical link set. The target physical link set defines the path set as:

[0135]

[0136] Among them, each path π k The following link resource constraints must be met: in, For the path π k The minimum remaining bandwidth on is a virtual link (v i ,v j ) bandwidth requirements.

[0137] The embodiments of the present application can maximize the use of physical network resources while meeting the needs of network slicing, and achieve efficient load balancing and optimal path allocation.

[0138] Step S604: Generate a candidate physical link set.

[0139] It should be noted that, in the embodiment of the present application, after step S601 and step S602 are successfully executed, the KSP algorithm is used to select k shortest paths from the initial candidate physical link set to obtain the target physical link set.

[0140] Furthermore, the embodiment of the present application selects a strategy that takes into account the link load. For each path p, the path length L(p), the bandwidth availability of the path B(p), the congestion of the path C(p), and the reliability of the path R(p) are combined to comprehensively evaluate the pros and cons of each path. Among them, the embodiment of the present application defines a comprehensive scoring function S(p), which is the weighted sum of these indicators, and then uses the comprehensive scoring function to calculate the comprehensive evaluation value, which can be expressed as but not limited to:

[0141]

[0142] Among them, α, β, γ, and δ are weight parameters, which need to be adjusted according to the actual network environment and application requirements.

[0143] Furthermore, the embodiment of the present application uses a comprehensive scoring function to calculate the scores of all KSP algorithms, and sorts the paths according to the comprehensive evaluation values. Paths with lower scores have higher priorities, and the top path after sorting is selected as the final network mapping path, thereby obtaining a candidate physical link set.

[0144] In addition, to ensure the fairness of the algorithm, a path selection factor P can be introduced. This indicator considers the score difference between paths to reduce the preference for a specific path when selecting the optimal path. The expression of the path selection factor P can be but is not limited to:

[0145]

[0146] in, For physical link The link load reflects the resource usage of the current physical link.

[0147] In step S104, based on the candidate physical node set and the candidate physical link set, a preset optimization objective function is used to collaboratively map virtual nodes and virtual links in the virtual network topology structure.

[0148] As a possible implementation method, after obtaining the candidate physical node set and the candidate physical link set, the embodiment of the present application can abstract the entire node and link mapping problem into a joint optimization problem, the goal of which is to minimize the overall physical resource overhead and network load. The specific optimization objective function can be, but is not limited to, expressed as:

[0149]

[0150] Among them, the first item is to minimize the load of physical nodes, and the second item is to minimize the consumption of physical link resources. The final mapping strategy dynamically adjusts the mapping path by weighing node resources, link resources, and cross-domain constraints to ensure the efficient operation of the entire network slice.

[0151] Furthermore, the embodiment of the present application traverses all virtual nodes in the virtual network, completes the collaborative mapping and resource allocation of virtual nodes and virtual links, and completes the deployment of network slices.

[0152] It should be noted that in the embodiment of the present application, if any virtual node or virtual link cannot be mapped during the collaborative mapping stage of virtual nodes and virtual links, the current network slicing requirements cannot be successfully deployed.

[0153] According to the collaborative mapping method based on node evaluation results proposed in the embodiment of the present application, a node mapping sequence between virtual nodes and physical nodes can be generated based on the virtual network topology structure required by the current network slice, and the network configuration information and node mapping sequence required by the current network slice can be combined to obtain a candidate physical node set and a candidate physical link set that meet certain conditions, and then a certain optimization objective function is used to perform collaborative mapping of virtual nodes and virtual links, actively integrate network resources, further provide the probability of network slice deployment, optimize load balancing, and achieve optimal path allocation. Therefore, the problems in the related technology that physical network resources cannot be maximized while meeting network slicing requirements, and load balancing and optimal path allocation cannot be achieved are solved.

[0154] Next, a collaborative mapping device based on node evaluation results proposed according to an embodiment of the present application is described with reference to the accompanying drawings.

[0155] Figure 7 It is a block diagram of a collaborative mapping device based on node evaluation results provided according to an embodiment of the present application.

[0156] like Figure 7As shown, the node evaluation result-based collaborative mapping device 10 includes: an acquisition module 100 , a first generation module 200 , a second generation module 300 and a collaborative mapping module 400 .

[0157] Among them, the acquisition module 100 is used to obtain the virtual network topology structure corresponding to the current network slicing requirements.

[0158] The first generation module 200 is used to generate a node mapping sequence between virtual nodes and physical nodes in a virtual network topology structure based on all virtual nodes and all physical nodes in the current network slicing requirements.

[0159] The second generation module 300 is used to generate a set of candidate physical nodes and a set of candidate physical links that meet preset conditions in combination with the network configuration information and node mapping sequence required by the current network slicing.

[0160] The collaborative mapping module 400 is used to collaboratively map virtual nodes and virtual links in a virtual network topology structure based on a candidate physical node set and a candidate physical link set using a preset optimization objective function.

[0161] Optionally, in one embodiment of the present application, the acquisition module 100 includes: a first generation unit, a second generation unit and a third generation unit.

[0162] Among them, the first generation unit is used to obtain the service quality requirements configured in the service configuration file corresponding to the current network slice requirements based on the current network slice requirements.

[0163] The second generating unit is used to generate target parameters of the virtual network topology structure based on the quality of service requirement.

[0164] The third generating unit is used to generate a virtual network topology structure by combining the target parameters and the adjacency matrix.

[0165] Optionally, in one embodiment of the present application, the first generating module 200 includes: a first calculating unit, a determining unit, an acquiring unit and a fourth generating unit.

[0166] The first calculation unit is used to evaluate the importance of virtual nodes and physical nodes by using the pre-built AEC-VIKOR mechanism, so as to calculate the virtual importance value corresponding to the virtual node and the physical importance value corresponding to the physical node according to the importance evaluation result.

[0167] The determination unit is used to determine the initial root node of the virtual network topology structure by combining the virtual importance value and the physical importance value.

[0168] The acquisition unit is used to perform BFS-DFS alternately on the virtual network topology structure to obtain a local path of each layer of the virtual network topology in the virtual network topology structure.

[0169] The fourth generation unit is used to determine the final root node after optimizing the initial root node through the local path, the virtual importance value and the physical importance value, and generate a node mapping sequence using the root node.

[0170] Optionally, in one embodiment of the present application, the computing unit includes: a first computing subunit, a second computing subunit and a third computing subunit.

[0171] The first calculation subunit is used to calculate the virtual decision matrix corresponding to the virtual node and the physical decision matrix corresponding to the physical node based on the importance attribute values ​​of the virtual node and the physical node.

[0172] The second calculation subunit is used to calculate the virtual expected value and the virtual defect value corresponding to the virtual node and the physical expected value and the physical defect value corresponding to the physical node based on the virtual decision matrix and the physical decision matrix.

[0173] The third calculation subunit is used to combine the virtual expectation value, the virtual defect value, the physical expectation value and the physical defect value, and calculate the virtual importance value and the physical importance value through the preset virtual compromise coefficient and the physical compromise coefficient weight.

[0174] Optionally, in one embodiment of the present application, the second generating module 300 includes: a screening unit, a second calculating unit, a fifth generating unit and a third calculating unit.

[0175] Among them, the screening unit is used to combine the network configuration information and node mapping sequence required by the current network slicing to screen out the initial candidate physical node set corresponding to the virtual nodes that meet the geographic network domain constraints and resource constraints.

[0176] The second calculation unit is used to calculate the load value of each initial candidate physical node in the initial candidate physical node set, and obtain a candidate physical node set and an initial candidate physical link set that meet preset conditions based on the load value.

[0177] The fifth generating unit is used to obtain a target physical link set that meets the target bandwidth constraint and the target resource constraint according to the physical network and the initial candidate physical link set.

[0178] The third calculation unit is used to establish a comprehensive evaluation function with bandwidth, delay, and load balancing as indicators based on the target physical link set, and use the comprehensive evaluation function to evaluate the target physical links in the target physical link set to select a candidate physical link set based on the comprehensive evaluation value.

[0179] It should be noted that the above explanations of the embodiment of the collaborative mapping method based on node evaluation results are also applicable to the collaborative mapping device based on node evaluation results of this embodiment, and will not be repeated here.

[0180] According to the collaborative mapping device based on node evaluation results proposed in the embodiment of the present application, a node mapping sequence between virtual nodes and physical nodes can be generated based on the virtual network topology structure required by the current network slice, and the candidate physical node set and candidate physical link set that meet certain conditions can be obtained by combining the network configuration information and node mapping sequence required by the current network slice, and then a certain optimization objective function is used to perform collaborative mapping of virtual nodes and virtual links, actively integrate network resources, further provide the probability of network slice deployment, optimize load balancing, and achieve optimal path allocation. Therefore, the problems in the related technology that physical network resources cannot be utilized to the maximum extent while meeting network slicing requirements, and load balancing and optimal path allocation cannot be achieved are solved.

[0181] Figure 8 This is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. The electronic device may include:

[0182] A memory 801 , a processor 802 , and a computer program stored in the memory 801 and executable on the processor 802 .

[0183] When the processor 802 executes the program, the collaborative mapping method based on the node evaluation result provided in the above embodiment is implemented.

[0184] Furthermore, the electronic device further comprises:

[0185] The communication interface 803 is used for communication between the memory 801 and the processor 802 .

[0186] The memory 801 is used to store computer programs that can be executed on the processor 802 .

[0187] The memory 801 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0188] If the memory 801, the processor 802 and the communication interface 803 are implemented independently, the communication interface 803, the memory 801 and the processor 802 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0189] Optionally, in a specific implementation, if the memory 801, the processor 802 and the communication interface 803 are integrated on a chip, the memory 801, the processor 802 and the communication interface 803 can communicate with each other through an internal interface.

[0190] The processor 802 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0191] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned collaborative mapping method based on node evaluation results.

[0192] An embodiment of the present application also provides a computer program product, including a computer program, which, when executed, implements the above-mentioned collaborative mapping method based on node evaluation results.

[0193] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0194] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0195] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0196] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0197] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented by hardware, as in another embodiment, it can be implemented by any one or a combination of multiple of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0198] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0199] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0200] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A collaborative mapping method based on node evaluation results, characterized in that: The following steps are involved: Obtain the virtual network topology corresponding to the current network slicing requirements; Based on all virtual nodes and all physical nodes in the current network slicing requirement, generate a node mapping sequence between virtual nodes and physical nodes in the virtual network topology structure; Combining the network configuration information of the current network slicing requirement and the node mapping sequence, generating a candidate physical node set and a candidate physical link set that meet preset conditions; Based on the candidate physical node set and the candidate physical link set, virtual nodes and virtual links in the virtual network topology are collaboratively mapped using a preset optimization objective function.

2. The method according to claim 1, characterized in that: The obtaining of the virtual network topology structure corresponding to the current network slicing requirement includes: Based on the current network slicing requirement, obtain the service quality requirement configured in the service configuration file corresponding to the current network slicing requirement; generating target parameters of the virtual network topology structure based on the quality of service requirements; The virtual network topology structure is generated by combining the target parameters and the adjacency matrix.

3. The method according to claim 1, characterized in that: The generating a node mapping sequence between virtual nodes and physical nodes in the virtual network topology structure based on all virtual nodes and all physical nodes in the current network slicing requirement includes: The virtual node and the physical node are evaluated for importance by using a pre-built multi-attribute decision-making method AEC-VIKOR mechanism, so as to calculate a virtual importance value corresponding to the virtual node and a physical importance value corresponding to the physical node according to the importance evaluation result; Determining an initial root node of the virtual network topology structure by combining the virtual importance value and the physical importance value; Alternately performing a breadth-first search (BFS) and a depth-first search (DFS) on the virtual network topology structure to obtain a local path of each layer of the virtual network topology in the virtual network topology structure; After optimizing the initial root node through the local path, the virtual importance value and the physical importance value, a final root node is determined, and a node mapping sequence is generated using the root node.

4. The method according to claim 3, characterized in that The using of the pre-built AEC-VIKOR mechanism to perform importance evaluation on the virtual node and the physical node, so as to calculate the virtual importance value corresponding to the virtual node and the physical importance value corresponding to the physical node according to the importance evaluation result, includes: Based on the importance attribute values ​​of the virtual node and the physical node, a virtual decision matrix corresponding to the virtual node and a physical decision matrix corresponding to the physical node are calculated; Based on the virtual decision matrix and the physical decision matrix, calculating the virtual expected value and the virtual defect value corresponding to the virtual node and the physical expected value and the physical defect value corresponding to the physical node; The virtual expected value, the virtual defect value, the physical expected value and the physical defect value are combined to calculate the virtual importance value and the physical importance value through the preset virtual compromise coefficient and the physical compromise coefficient weight.

5. The method according to claim 1, characterized in that The generating a candidate physical node set and a candidate physical link set that meet preset conditions by combining the network configuration information of the current network slicing requirement and the node mapping sequence includes: In combination with the network configuration information of the current network slicing requirement and the node mapping sequence, an initial candidate physical node set corresponding to the virtual node that meets the geographic network domain constraint and the resource constraint is screened out; Calculating the load value of each initial candidate physical node in the initial candidate physical node set, and obtaining a candidate physical node set and an initial candidate physical link set that meet preset conditions based on the load value; According to the physical network and the initial candidate physical link set, a target physical link set that satisfies a target bandwidth constraint and a target resource constraint is obtained; Based on the target physical link set, a comprehensive evaluation function with bandwidth, delay and load balancing as indicators is established, and the target physical links in the target physical link set are evaluated using the comprehensive evaluation function to select a candidate physical link set according to the comprehensive evaluation value.

6. A collaborative mapping device based on node evaluation results, characterized in that: include: An acquisition module is used to obtain the virtual network topology structure corresponding to the current network slicing requirements; A first generating module, configured to generate a node mapping sequence between virtual nodes and physical nodes in the virtual network topology structure based on all virtual nodes and all physical nodes in the current network slicing requirement; A second generation module is used to generate a candidate physical node set and a candidate physical link set that meet preset conditions by combining the network configuration information required by the current network slicing and the node mapping sequence; The collaborative mapping module is used to collaboratively map the virtual nodes and virtual links in the virtual network topology structure based on the candidate physical node set and the candidate physical link set using a preset optimization objective function.

7. The device according to claim 6, characterized in that The acquisition module comprises: A first generating unit is used to obtain, based on the current network slice requirement, a service quality requirement configured in a service configuration file corresponding to the current network slice requirement; A second generating unit, configured to generate target parameters of the virtual network topology structure based on the quality of service requirement; The third generating unit is used to generate the virtual network topology structure by combining the target parameters and the adjacency matrix.

8. The device according to claim 6, characterized in that The first generating module comprises: A first calculation unit, configured to perform importance evaluation on the virtual node and the physical node by using a pre-built AEC-VIKOR mechanism, so as to calculate a virtual importance value corresponding to the virtual node and a physical importance value corresponding to the physical node according to the importance evaluation result; A determination unit, configured to determine an initial root node of the virtual network topology structure by combining the virtual importance value and the physical importance value; An acquisition unit, configured to perform BFS-DFS alternately on the virtual network topology structure to obtain a local path of each layer of the virtual network topology in the virtual network topology structure; The fourth generating unit is used to determine the final root node after optimizing the initial root node through the local path, the virtual importance value and the physical importance value, and generate a node mapping sequence using the root node.

9. The device according to claim 8, characterized in that The computing unit comprises: A first calculation subunit, configured to calculate a virtual decision matrix corresponding to the virtual node and a physical decision matrix corresponding to the physical node based on importance attribute values ​​of the virtual node and the physical node; A second calculation subunit is used to calculate the virtual expected value and the virtual defect value corresponding to the virtual node and the physical expected value and the physical defect value corresponding to the physical node based on the virtual decision matrix and the physical decision matrix; The third calculation subunit is used to combine the virtual expected value, the virtual defect value, the physical expected value and the physical defect value, and calculate the virtual importance value and the physical importance value through the preset virtual compromise coefficient and the physical compromise coefficient weight.

10. The device according to claim 6, characterized in that The second generating module comprises: A screening unit, configured to combine the network configuration information of the current network slice requirement and the node mapping sequence to screen out an initial candidate physical node set corresponding to the virtual node that meets the geographic network domain constraint and the resource constraint; A second calculation unit, configured to calculate a load value of each initial candidate physical node in the initial candidate physical node set, and obtain a candidate physical node set and an initial candidate physical link set that meet a preset condition based on the load value; A fifth generating unit, configured to obtain a target physical link set satisfying a target bandwidth constraint and a target resource constraint according to the physical network and the initial candidate physical link set; The third computing unit is used to establish a comprehensive evaluation function with bandwidth, delay, and load balancing as indicators based on the target physical link set, and use the comprehensive evaluation function to evaluate the target physical links in the target physical link set to select a candidate physical link set based on the comprehensive evaluation value.

11. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the collaborative mapping method based on node evaluation results as described in any one of claims 1 to 5.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the collaborative mapping method based on node evaluation results as described in any one of claims 1 to 5.

13. A computer program product, characterized in that It comprises a computer program, which, when executed, is used to implement the collaborative mapping method based on node evaluation results as described in any one of claims 1 to 5.

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