In this paper, we propose a new centrality algorithm that can simultaneously rank the nodes and layers of multilayer networks, referred to as the MRFNL centrality. The centrality of nodes and layers are obtained by de...In this paper, we propose a new centrality algorithm that can simultaneously rank the nodes and layers of multilayer networks, referred to as the MRFNL centrality. The centrality of nodes and layers are obtained by developing a novel iterative algorithm for computing a set of tensor equations. Under some conditions, the existence and uniqueness of this centrality were proven by applying the Brouwer fixed point theorem. Furthermore, the convergence of the proposed iterative algorithm was established. Finally, numerical experiments on a simple multilayer network and two real-world multilayer networks(i.e., Pierre Auger Collaboration and European Air Transportation Networks) are proposed to illustrate the effectiveness of the proposed algorithm and to compare it to other existing centrality measures.展开更多
为了减少多层网络中的资源分配冗余,降低网络资源配置代价,提供必要的生存性保证,提出了基于多重可备用的跨层资源优化方法。该方法考虑不同业务的生存性需求,将多跳业务分为三类,对不同业务应用不同的资源分配方法;在最小化网络资源配...为了减少多层网络中的资源分配冗余,降低网络资源配置代价,提供必要的生存性保证,提出了基于多重可备用的跨层资源优化方法。该方法考虑不同业务的生存性需求,将多跳业务分为三类,对不同业务应用不同的资源分配方法;在最小化网络资源配置代价的约束下,提出多重可备用的思想,即同时使用层间备用和层内备用;最后应用ILP(Integer Linear programming,整数线性规划)技术对该方法进行分析和验证。展开更多
基金Project supported by the Postgraduate Research and Practice Innovation Program of Jiangsu Province,China(Grant No.AE91313/001/016)the National Natural Science Foundation of China(Grant No.11701097)the Natural Science Foundation of Jiangxi Province,China(Grant No.20161BAB212055)
文摘In this paper, we propose a new centrality algorithm that can simultaneously rank the nodes and layers of multilayer networks, referred to as the MRFNL centrality. The centrality of nodes and layers are obtained by developing a novel iterative algorithm for computing a set of tensor equations. Under some conditions, the existence and uniqueness of this centrality were proven by applying the Brouwer fixed point theorem. Furthermore, the convergence of the proposed iterative algorithm was established. Finally, numerical experiments on a simple multilayer network and two real-world multilayer networks(i.e., Pierre Auger Collaboration and European Air Transportation Networks) are proposed to illustrate the effectiveness of the proposed algorithm and to compare it to other existing centrality measures.
文摘为了减少多层网络中的资源分配冗余,降低网络资源配置代价,提供必要的生存性保证,提出了基于多重可备用的跨层资源优化方法。该方法考虑不同业务的生存性需求,将多跳业务分为三类,对不同业务应用不同的资源分配方法;在最小化网络资源配置代价的约束下,提出多重可备用的思想,即同时使用层间备用和层内备用;最后应用ILP(Integer Linear programming,整数线性规划)技术对该方法进行分析和验证。
