CN-122027484-A - Multi-stage network reconstruction recovery method based on structure perception

CN122027484ACN 122027484 ACN122027484 ACN 122027484ACN-122027484-A

Abstract

The invention discloses a multi-stage network reconstruction recovery method based on structure perception, which comprises the steps of identifying a path set influenced by broken links in a network topological graph, generating a candidate path set for each affected path in the network topological graph after the broken links are removed, calculating the comprehensive structural similarity with a corresponding original path for each candidate path, calculating the end-to-end task success rate of each candidate path based on the real-time failure rate of nodes and edges and the path transmission delay by considering communication degradation factors, selecting the candidate path with the largest optimization objective function value from the corresponding candidate path set for each affected path, and outputting a reconstruction result, wherein the optimization objective function comprises the comprehensive structural similarity. The invention has the advantages of no need of training, complete interpretation and audit, and has obvious engineering landing advantage in the field of combat or key infrastructure with extremely high requirements on safety and reliability.

Inventors

CHEN ZHUMEI
NIE GUANGYONG
LI HAOLONG
LIU SHANGLIN
LIN JINGKUN

Assignees

电子科技大学

Dates

Publication Date: 20260512
Application Date: 20260225

Claims (9)

1. A multi-stage network reconstruction restoration method based on structure awareness, comprising: identifying a path set affected by the broken link in the network topology map; Generating a candidate path set for each affected path in the network topological graph after the link failure is removed, wherein each candidate path is required to meet length constraint I, type quota constraint and phase constraint based on the current scene; for each candidate path, calculating the comprehensive structural similarity with the corresponding original path; Considering communication degradation factors, and calculating the end-to-end task success rate of each candidate path based on the real-time failure rate of the nodes and the edges and the path transmission delay; And selecting a candidate path with the largest optimization objective function value from the corresponding candidate path set as a reconstruction path for each affected path, and outputting a reconstruction result, wherein the optimization objective function comprises the comprehensive structural similarity.
2. The structure-aware-based multi-stage network reconstruction restoration method according to claim 1, wherein generating the set of candidate paths comprises: and generating the candidate path set by adopting depth-first search or iterative deepening search and setting an upper limit of path enumeration depth and an upper limit of number, wherein a prefix pruning strategy based on path length, node type and scene constraint is applied in the search process.
3. The structure-aware-based multi-stage network reconstruction restoration method according to claim 1, wherein the computing of the comprehensive structural similarity to the corresponding original path is: ; In the formula, Is a candidate path And the original path Is a comprehensive structural similarity of (1); Is the original path; is a candidate path; Representing the overlapping degree of nodes among paths for the Jaccard similarity coefficient based on the nodes; representing the overlapping degree of links between paths for a side-based Jaccard similarity coefficient; Is the path length similarity; distributing similarity for node types; And the weight coefficients of the four similarity indexes are respectively.
4. A multi-stage network reconstruction restoration method based on structure awareness according to claim 3 wherein a penalty term is introduced to maintain a specific critical link when calculating the optimization objective, the revised similarity score being: ; In the formula, Is the original integrated structural similarity of the two-dimensional structure, For the critical link penalty factor(s), As a set of links of the original path, As a set of critical hit links, Is a link set of candidate paths.
5. The structure-aware-based multi-stage network reconstruction restoration method according to claim 1, wherein an end-to-end task success rate of each candidate path is calculated: ; In the formula, For an end-to-end task success rate for each candidate path, In order for the node to fail at a rate, In order to be a rate of edge failure, For the delay efficiency factor, v is the node on the path, Is a link on the path.
6. The multi-stage network reconstruction restoration method based on structure awareness according to claim 1, wherein the optimization objective function is a multi-objective weighting function, specifically: ; In the formula, To choose a regular term based on weaknesses or congestion, Is the original integrated structural similarity of the two-dimensional structure, In order to be a structural similarity term, As a task success rate term, The weight coefficients for the regular penalty term, The end-to-end task success rate for the candidate path.
7. The structure-aware-based multi-stage network reconstruction restoration method according to claim 1, wherein the reconstruction result comprises: the selected alternate path, the integrated structural similarity of the alternate path to the original path, the path success rate, and the differential set of links between the old and new paths, which identifies the links that are newly added, removed, and maintained.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the structure-aware-based multi-stage network reconstruction restoration method according to any one of claims 1 to 7 when the computer program is executed by the processor.
9. A computer readable storage medium having stored thereon a computer program, which when executed by a processor implements the structure-aware multi-stage network reconstruction restoration method according to any one of claims 1 to 7.

Description

Multi-stage network reconstruction recovery method based on structure perception Technical Field The invention relates to the technical field of complex network analysis and intelligent decision making, in particular to a multi-stage network reconstruction recovery method based on structure awareness. Background With the expansion of the size of informatization and networking systems, the stability and vulnerability of complex networks is receiving extensive attention from academia and industry. How to identify the key nodes and weak links in the complex network not only relates to the robustness and reliability of the whole system, but also directly influences the continuity and the completion efficiency of the task chain. The current state of research and application is mainly represented in the following directions: (1) Single index centrality method: Complex network analysis often uses indexes such as centrality, betweenness centrality, proximity centrality and the like as important basis for judging key nodes. Brandes proposed a fast median centrality algorithm in 2001, reducing the computational complexity to O (|v||e|), making large-scale network analysis possible. The method is widely applied to the scenes of communication networks, traffic networks, social networks and the like. (2) Network robustness and seepage theory view angle: Complex network theory reveals that a non-scale network is robust to random failures, but extremely vulnerable to targeted attacks (e.g., removing high centrality nodes). This conclusion becomes an important theoretical basis for key node identification, and related research results have been widely spread on platforms such as Nature and arXiv. (3) Critical Node Detection Problem (CNDP): CNDP models "find out a group of nodes that make the network connectivity drop most seriously" as the combined optimization problem, have multiple algorithm solving methods such as integer planning, heuristic, etc., and get application in key infrastructure protection such as electric power, traffic, communication, etc.. (4) Network efficiency index: Latora and Marchiori propose network efficiency indicators, and the overall information transfer efficiency is characterized by averaging the inverse of the shortest path, which provides a reference for evaluating network performance at the macro level, and has been adopted in a number of network performance analysis scenarios. Although the above method provides an important idea for the vulnerability study of complex networks, the following disadvantages still exist: 1. Structure-oriented, lacking task-oriented: both the single index centrality and the seepage theory focus on the importance of network topology positions or global connectivity, but the task achievement probability of failing to combine a specific information chain is difficult to reflect the role of the nodes in actual task execution. 2. Lack of node function and health modeling: most of the existing methods assume that the nodes are in an ideal working state, and the real-time performance attenuation or failure probability of the nodes are not considered, so that the evaluation result is different from the actual performance. 3. Neglecting the influence of environmental factors: Environmental conditions such as distance, delay, interference, etc. have a significant impact on link reliability, but most methods do not model these factors directly. 4. The real-time performance is not enough: The CNDP and the global efficiency index are generally complex in calculation, suitable for static analysis, and difficult to meet the real-time vulnerability identification requirement in a dynamic environment. Disclosure of Invention In order to solve the technical problems in the prior art, the invention provides a multi-stage network reconstruction recovery method based on structure perception, which reconstructs a communication chain from an information source to a task terminal in real time and maintains the semantics and the structural characteristics of the original chain. In order to achieve the above object, the present invention provides a multi-stage network reconstruction recovery method based on structure awareness, including: identifying a path set affected by the broken link in the network topology map; Generating a candidate path set for each affected path in the network topological graph after the link failure is removed, wherein each candidate path is required to meet length constraint I, type quota constraint and phase constraint based on the current scene; for each candidate path, calculating the comprehensive structural similarity with the corresponding original path; Considering communication degradation factors, and calculating the end-to-end task success rate of each candidate path based on the real-time failure rate of the nodes and the edges and the path transmission delay; And selecting a candidate path with the largest optimization objective function value from