沈阳工业大学学报2025，Vol.47Issue(1)：92-97,6.DOI:10.7688/j.issn.1000-1646.2025.01.12
基于时间局部性的网络拓扑结构发现算法
Network topology discovery algorithm based on temporal locality
摘要
Abstract
[Objective]With the rapid development of social network technology,obtaining the topology of large-scale complex networks has become an urgent problem in various disciplines such as electronics,networks,biology,and medicine.Typically,large-scale complex networks consist of participating nodes and virtual connections,where nodes represent roles such as individuals,families,and society,and connections depict the complex relationships between these roles.Generally,there is a phenomenon of extremely high homology in complex networks,namely that there are a large number of repetitive or similar architectures,which greatly increases the difficulty of discovering the dynamic structure of networks.[Methods]Based on the principle of temporal locality,a heuristic network community discovery algorithm was proposed to further optimize the accuracy and running time of topology discovery.By modifying the calculation rules of nodes within adjacent time ranges and using the cosine similarity criterion,the topology discovery algorithm deeply described the predictability of complex relationships among multiple participating nodes in the network.Specifically,the algorithm was based on the classical Louvain algorithm,optimizing the accuracy and running time of community detection by calculating incremental modularity and cosine similarity.In addition,the algorithm used the concept of modularity to accurately measure network topology,and the calculation formula of incremental modularity indicators was introduced to grasp the changes in topology discovery algorithm indicators in real time.[Results]To verify the effectiveness of the proposed algorithm,simulation was conducted using an actual communication dataset of a smart grid,which included 616 pieces of communication connection data of 115 power-using units.The simulation results show that compared with the classical Louvain algorithm,the proposed algorithm has significant advantages in detection efficiency and running time.The comparative analysis of normalized mutual information indicators shows that the proposed algorithm has higher normalized mutual information and lower average running time when the number of participating nodes is large.This indicates that the new algorithm has superiority in large-scale networks,although its performance is slightly inferior in small-scale networks.Simulation with the actual dataset reveals that the topology discovery algorithm based on temporal locality has obvious advantages in the precise discovery of large-scale smart distribution networks,able to provide strategies for optimizing network topology discovery in fields such as smart grids.[Conclusion]In summary,the innovation of the topology discovery algorithm based on temporal locality lies in applying the principle of temporal locality to network community discovery.This paper provides a new perspective and method for the study of complex network community discovery algorithms,having reference significance for researchers in related fields.Future research will address the application issues of the algorithm in small-scale networks and further analyze the robustness of the algorithm.关键词
复杂网络/拓扑结构/Louvain算法/社区发现算法/判定准则/时间局部性/运行耗时/模块度Key words
complex network/topology/Louvain algorithm/community discovery algorithm/criterion/temporal locality/running time/modularity分类
信息技术与安全科学引用本文复制引用
黎燕,刘成江,张千千,殷攀程..基于时间局部性的网络拓扑结构发现算法[J].沈阳工业大学学报,2025,47(1):92-97,6.基金项目
国家自然科学基金项目(52077146) （52077146）
国网西南分部应用建设项目(71999821N005). （71999821N005）
