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基于回溯机制的互联网AS拓扑的betweenness算法

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计算机研究与发展 2006年第10期43卷 1790-1796页

作者：张国强张国清中国科学院计算技术研究所中国科学院研究生院北京100049

betweenness能够刻画节点或边在网络中的重要程度.在Internet中,betweenness直接反应了特定网络拓扑结构下节点或链路可能承载的网络流量,能够对网络的动态行为进行预测.但传统的Be-tweenness计算复杂度较高,为O(n3),但这些算法是为加... 详细信息

betweenness能够刻画节点或边在网络中的重要程度.在Internet中,betweenness直接反应了特定网络拓扑结构下节点或链路可能承载的网络流量,能够对网络的动态行为进行预测.但传统的Be-tweenness计算复杂度较高,为O(n3),但这些算法是为加权网络设计的,而很多实际的网络模型并没有考虑权重.另一方面,目前的算法都没有考虑边的语义,而互联网AS(autonomoussystem)拓扑中的边具有语义.针对简单无权网络提出一种基于回溯的时间复杂度为O(nm)的betweenness计算方法.在进一步考虑InternetAS拓扑的特殊性,即任意两个相连的AS都具有某种商业关系的基础上提出了互联网AS层拓扑的betweenness计算方法.

关键词： betweenness 自治系统网络拓扑路由策略

Control of cascading failures in coupled map lattices based on adaptive predictive pinning control

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Journal of Zhejiang University-Science C(Computers and Electronics) 2011年第10期12卷 828-835页

作者： Zhe-jing BAO Gang WU Wen-jun YAN School of Electrical Engineering Zhejiang University Hangzhou 310027 China

An adaptive predictive pinning control is proposed to suppress the cascade in coupled map lattices (CMLs).Two monitoring strategies are applied:(1) A specific fraction of nodes with the highest degree or betweenness are chosen to constitute the set of monitored nodes;(2) During the cascade,an adaptive pinning control is implemented,in which only the nodes in the monitored set whose current state is normal but whose predictive state is abnormal,are pinned with the predictive *** show that for the scale-free (SF) CML the degree-based monitoring strategy is advantageous over the betweenness-based strategy,while for the small-world (SW) CML the situation is the *** the adaptive predictive pinning control,the fewer local controllers can effectively suppress the cascade throughout the whole network.

关键词： Coupled map lattices Cascade Pinning Predictive control Degree betweenness

Sewage flow optimization algorithm for large-scale urban sewer networks based on network community division

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控制理论与应用（英文版） 2008年第4期6卷 372-378页

作者： Lihui CEN Yugeng XI Department of Automation Shanghai Jiao Tong University Shanghai 200240 China

By considering the flow control of urban sewer networks to minimize the electricity consumption of pumping stations, a decomposition-coordination strategy for energy savings based on network community division is developed in this paper. A mathematical model characterizing the steady-state flow of urban sewer networks is first constructed, consisting of a set of algebraic equations with the structure transportation capacities captured as constraints. Since the sewer networks have no apparent natural hierarchical structure in general, it is very difficult to identify the clustered groups. A fast network division approach through calculating the betweenness of each edge is successfully applied to identify the groups and a sewer network with arbitrary configuration could be then decomposed into subnetworks. By integrating the coupling constraints of the subnetworks, the original problem is separated into N optimization subproblems in accordance with the network decomposition. Each subproblem is solved locally and the solutions to the subproblems are coordinated to form an appropriate global solution. Finally, an application to a specified large-scale sewer network is also investigated to demonstrate the validity of the proposed algorithm.

关键词： Large-scale sewer network betweenness Network community division Decomposition and coordination

Interest Point Detection in Images Based on Topology Structure Features of Directed Complex Network

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Interest Point Detection in Images Based on Topology Structu...

Confidence Intervals for Assessing Sizes of Social Network Centralities

第36届中国控制会议

作者： Qingyu Zou Weiliang Sun Liyun Xing Yan Chen Haitao Yuan College of Electrical and Information Engineering Beihua University College of Communication Engineering Jilin University

ISBN: (纸本)9781538629185

Interest point detection is one of the key technologies in image processing and target recognition. This paper presents a new method for detecting interest points in digital images and computer vision problems based on complex network theory. We associate a directed and weighted complex network model to each image and then we propose three different algorithms to locate these key points based on three topological features of image complex network model, which are degree, closeness and betweenness.

关键词： Image Interest point Complex network Degree Closeness betweenness

来源： cnki会议评论

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Social Networking 2018年第4期7卷 220-242页

作者： Dawn Iacobucci Rebecca McBride Deidre L. Popovich Maria Rouziou Vanderbilt University Nashville TN USA Finance and Administration Development Deloitte New York NY USA Texas Tech University Lubbock TX USA

This research uses random networks as benchmarks for inferential tests of network structures. Specifically, we develop formulas for expected values and confidence intervals for four frequently employed social network centrality indices. The first study begins with analyses of stylized networks, which are then perturbed with increasing levels of random noise. When the indices achieve their values for fully random networks, the indices reveal systematic relationships that generalize across network forms. The second study then delves into the relationships between numbers of actors in a network and the density of a network for each of the centrality indices. In doing so, expected values are easily calculated, which in turn enable chi-square tests of network structure. Furthermore, confidence intervals are developed to facilitate a network analyst’s understanding as to which patterns in the data are merely random, versus which are structurally significantly distinct.

关键词： Centrality Degree Closeness betweenness Eigenvector Centrality Social Networks

An Energy-Based Centrality for Electrical Networks

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Energy and Power Engineering 2013年第4期5卷 597-602页

作者： Ruiyuan Kong Congying Han Tiande Guo Wei Pei College of Humanities and Social Sciences University of Chinese Academy of Sciences Beijing China Institute of Electrical Engineering Chinese Academy of Sciences Beijing China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing China

We present an energy-based method to estimate centrality in electrical networks. Here the energy between a pair of vertices denotes by the effective resistance between them. If there is only one generation and one load, then the centrality of an edge in our method is the difference between the energy of network after deleting the edge and that of the original network. Compared with the local current-flow betweenness on the IEEE 14-bus system, we have an interesting discovery that our proposed centrality is closely related to it in the sense of that the significance of edges under the two measures are very similar.

关键词： Centrality Energy Effective Resistance Current-flow betweenness

Complex Networks: Traffic Dynamics, Network Performance, and Network Structure

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维普期刊数据库

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American Journal of Operations Research 2013年第1期3卷 187-195页

作者： Ziping Hu Krishnaiyan Thulasiraman Pramode K. Verma Department of Computer Science The University of Oklahoma Norman USA School of Electrical & Computer Engineering The University of Oklahoma Tulsa USA

This paper explores traffic dynamics and performance of complex networks. Complex networks of various structures are studied. We use node betweenness centrality, network polarization, and average path length to capture the structural characteristics of a network. Network throughput, delay, and packet loss are used as network performance measures. We investigate how internal traffic, through put, delay, and packet loss change as a function of packet generation rate, network structure, queue type, and queuing discipline through simulation. Three network states are classified. Further, our work reveals that the parameters chosen to reflect network structure, including node betweenness centrality, network polarization, and average path length, play important roles in different states of the underlying networks.

关键词： Complex Networks betweenness Centrality Network Polarization Average Path Length Throughput De-lay Packet Loss

Research on LFS Algorithm in Software Network

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Journal of Software Engineering and Applications 2010年第2期3卷 185-189页

作者： Wei Wang Hai Zhao Hui Li Jun Zhang Peng Li Zheng Liu Naiming Guo Jian Zhu Bo Li Shuang Yu Hong Liu Kunzhan Yang 不详

betweenness centrality helps researcher to master the changes of the system from the overall perspective in software network. The existing betweenness centrality algorithm has high time complexity but low accuracy. Therefore, Layer First Searching (LFS) algorithm is proposed that is low in time complexity and high in accuracy. LFS algorithm searches the nodes with the shortest to the designated node, then travels all paths and calculates the nodes on the paths, at last get the times of each node being traveled which is betweenness centrality. The time complexity of LFS algorithm is O(V2).

关键词： LFS Software Network the Shortest Path betweenness Centrality

Topological Connectivity Analysis on Freight Transportation Networks

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Topological Connectivity Analysis on Freight Transportation ...