The network diameter is an important characteristic parameter of a complex network. Calculation for a large-scale complex network’s diameter has been an important subject in the study of complex networks. If the netw...The network diameter is an important characteristic parameter of a complex network. Calculation for a large-scale complex network’s diameter has been an important subject in the study of complex networks. If the network diameter is calculated directly, the problem mainly exists in efficiency for searching and counting the shortest paths. If the network diameter is calculated indirectly by studying the statistical function about the relationship between the network diameter and parameters affecting the diameter, the problems not only exist in the efficiency of statistic, but also exist in the function which may be not applicable to all kinds of networks. An algorithm for the complex network diameter based on the k order distance matrix is proposed with a matrix multiplication approach, and a mathematical proof for the algorithm correctness is given as well. Furthermore, some relevant propositions and deductions for reducing the complexity of this algorithm are put forward. With a good theoretical basis and a simple calculation process, this algorithm can be used to calculate the diameter of a large-scale complex network with small-world effect more accurately and efficiently. Two cases about the advanced research projects agency(ARPA) network model and the Chinese airline network model are adopted to verify the effect of this algorithm.展开更多
“一星多用、多星组网、多网协同”思想的发展与应用为卫星互联网的关键节点识别带来了更多的挑战,也提出了更高的要求。针对卫星时序网络节点评估结果不准确的问题,考虑了不同时间片拓扑之间的耦合强度,提出了一种基于改进超邻接矩阵(s...“一星多用、多星组网、多网协同”思想的发展与应用为卫星互联网的关键节点识别带来了更多的挑战,也提出了更高的要求。针对卫星时序网络节点评估结果不准确的问题,考虑了不同时间片拓扑之间的耦合强度,提出了一种基于改进超邻接矩阵(supra-adjacency matrix,SAM)的卫星互联网时序网络模型。随后,综合卫星节点在网络中固有的拓扑特性和通信特性,选取特征向量中心性、介数中心性、节点紧密度、传输时延、传输速率和传输容量指标建立了节点重要度综合评估指标体系,在此基础上,基于熵权-逼近理想解排序法(technique for order preference by similarity to an ideal solution,TOPSIS)和时间权重矩阵设计了卫星互联网节点重要度评估方法。通过ARPANET和铱星星座进行仿真验证,实验结果证明了所提出的模型和方法能够准确地从局部和全局角度获得卫星节点重要度排序,并识别出潜在重要节点,对卫星互联网关键节点识别及抗毁性研究有一定的参考意义。展开更多
基金supported by the National Natural Science Foundation of China(61273210)
文摘The network diameter is an important characteristic parameter of a complex network. Calculation for a large-scale complex network’s diameter has been an important subject in the study of complex networks. If the network diameter is calculated directly, the problem mainly exists in efficiency for searching and counting the shortest paths. If the network diameter is calculated indirectly by studying the statistical function about the relationship between the network diameter and parameters affecting the diameter, the problems not only exist in the efficiency of statistic, but also exist in the function which may be not applicable to all kinds of networks. An algorithm for the complex network diameter based on the k order distance matrix is proposed with a matrix multiplication approach, and a mathematical proof for the algorithm correctness is given as well. Furthermore, some relevant propositions and deductions for reducing the complexity of this algorithm are put forward. With a good theoretical basis and a simple calculation process, this algorithm can be used to calculate the diameter of a large-scale complex network with small-world effect more accurately and efficiently. Two cases about the advanced research projects agency(ARPA) network model and the Chinese airline network model are adopted to verify the effect of this algorithm.
文摘“一星多用、多星组网、多网协同”思想的发展与应用为卫星互联网的关键节点识别带来了更多的挑战,也提出了更高的要求。针对卫星时序网络节点评估结果不准确的问题,考虑了不同时间片拓扑之间的耦合强度,提出了一种基于改进超邻接矩阵(supra-adjacency matrix,SAM)的卫星互联网时序网络模型。随后,综合卫星节点在网络中固有的拓扑特性和通信特性,选取特征向量中心性、介数中心性、节点紧密度、传输时延、传输速率和传输容量指标建立了节点重要度综合评估指标体系,在此基础上,基于熵权-逼近理想解排序法(technique for order preference by similarity to an ideal solution,TOPSIS)和时间权重矩阵设计了卫星互联网节点重要度评估方法。通过ARPANET和铱星星座进行仿真验证,实验结果证明了所提出的模型和方法能够准确地从局部和全局角度获得卫星节点重要度排序,并识别出潜在重要节点,对卫星互联网关键节点识别及抗毁性研究有一定的参考意义。
