Unicast Network Topology Inference Algorithm Based on Hierarchical Clustering  

作　　者：肖甫 是晨航 黄凯祥 王汝传 

机构地区：[1]College of Computer,Nanjing University of Posts and Telecommunications [2]Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks,Nanjing University of Posts and Telecommunications

出　　处：《Transactions of Nanjing University of Aeronautics and Astronautics》2015年第6期591-599,共9页南京航空航天大学学报（英文版）

基　　金：supported by the National Natural Science Foundation of China (Nos.61373137,61373017, 61373139);the Major Program of Jiangsu Higher Education Institutions (No.14KJA520002);the Six Industries Talent Peaks Plan of Jiangsu(No.2013-DZXX-014);the Jiangsu Qinglan Project

摘　　要：Network topology inference is one of the important applications of network tomography.Traditional network topology inference may impact network normal operation due to its generation of huge data traffic.A unicast network topology inference is proposed to use time to live(TTL)for layering and classify nodes layer by layer based on the similarity of node pairs.Finally,the method infers logical network topology effectively with self-adaptive combination of previous results.Simulation results show that the proposed method holds a high accuracy of topology inference while decreasing network measuring flow,thus improves measurement efficiency.Network topology inference is one of the important applications of network tomography. Traditional network topology inference may impact network normal operation due to its generation of huge data traffic. A unicast network topology inference is proposed to use time to live （TTL） for layering and classify nodes layer by layer based on the similarity of node pairs. Finally, the method infers logical network topology effectively with self-adaptive combination of previous results, Simulation results show that the proposed method holds a high accuracy of topology inference while decreasing network measuring flow, thus improves measurement efficiency.

关 键 词：network topology inference network tomography hierarchical clustering time to live(TTL) 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]