模糊的社团结构能有效提升网络传输性能。基于社团结构,利用节点之间的同异配程度和 k core 结构来定义链路重要性,提出了一种新的在社团内部删除链路,社团之间添加链路来减弱社团结构,提高网络容量的链路重连策略,即社团组合信息链路...模糊的社团结构能有效提升网络传输性能。基于社团结构,利用节点之间的同异配程度和 k core 结构来定义链路重要性,提出了一种新的在社团内部删除链路,社团之间添加链路来减弱社团结构,提高网络容量的链路重连策略,即社团组合信息链路重连策略(CCLS策略)。为了验证方法的有效性,我们分别在伪随机网络、具有社团结构的CWS小世界网络、无标度社团网络以及真实网络进行了仿真实验,仿真结果表明,CCLS策略能有效减弱网络社团特性,提高网络传输容量。展开更多
The disintegration of networks is a widely researched topic with significant applications in fields such as counterterrorism and infectious disease control. While the traditional approaches for achieving network disin...The disintegration of networks is a widely researched topic with significant applications in fields such as counterterrorism and infectious disease control. While the traditional approaches for achieving network disintegration involve identifying critical sets of nodes or edges, limited research has been carried out on edge-based disintegration strategies. We propose a novel algorithm, i.e., a rank aggregation elite enumeration algorithm based on edge-coupled networks(RAEEC),which aims to implement tiling for edge-coupled networks by finding important sets of edges in the network while balancing effectiveness and efficiency. Our algorithm is based on a two-layer edge-coupled network model with one-to-one links, and utilizes three advanced edge importance metrics to rank the edges separately. A comprehensive ranking of edges is obtained using a rank aggregation approach proposed in this study. The top few edges from the ranking set obtained by RAEEC are then used to generate an enumeration set, which is continuously iteratively updated to identify the set of elite attack edges.We conduct extensive experiments on synthetic networks to evaluate the performance of our proposed method, and the results indicate that RAEEC achieves a satisfactory balance between efficiency and effectiveness. Our approach represents a significant contribution to the field of network disintegration, particularly for edge-based strategies.展开更多
文摘模糊的社团结构能有效提升网络传输性能。基于社团结构,利用节点之间的同异配程度和 k core 结构来定义链路重要性,提出了一种新的在社团内部删除链路,社团之间添加链路来减弱社团结构,提高网络容量的链路重连策略,即社团组合信息链路重连策略(CCLS策略)。为了验证方法的有效性,我们分别在伪随机网络、具有社团结构的CWS小世界网络、无标度社团网络以及真实网络进行了仿真实验,仿真结果表明,CCLS策略能有效减弱网络社团特性,提高网络传输容量。
基金supported by the National Natural Science Foundation of China (Grant Nos. 61877046, 12271419, and 62106186)the Natural Science Basic Research Program of Shaanxi (Program No. 2022JQ-620)the Fundamental Research Funds for the Central Universities (Grant Nos. XJS220709, JB210701, and QTZX23002)。
文摘The disintegration of networks is a widely researched topic with significant applications in fields such as counterterrorism and infectious disease control. While the traditional approaches for achieving network disintegration involve identifying critical sets of nodes or edges, limited research has been carried out on edge-based disintegration strategies. We propose a novel algorithm, i.e., a rank aggregation elite enumeration algorithm based on edge-coupled networks(RAEEC),which aims to implement tiling for edge-coupled networks by finding important sets of edges in the network while balancing effectiveness and efficiency. Our algorithm is based on a two-layer edge-coupled network model with one-to-one links, and utilizes three advanced edge importance metrics to rank the edges separately. A comprehensive ranking of edges is obtained using a rank aggregation approach proposed in this study. The top few edges from the ranking set obtained by RAEEC are then used to generate an enumeration set, which is continuously iteratively updated to identify the set of elite attack edges.We conduct extensive experiments on synthetic networks to evaluate the performance of our proposed method, and the results indicate that RAEEC achieves a satisfactory balance between efficiency and effectiveness. Our approach represents a significant contribution to the field of network disintegration, particularly for edge-based strategies.
