西安电子科技大学学报（自然科学版）Issue(4)：133-139,7.DOI:10.3969/j.issn.1001-2400.2015.04.022
利用有限混合模型的高效网络拓扑推断算法
Efficient topology inference algorithm using the finite mixture model
摘要
Abstract
The performance of the existing efficient topology inference algorithm is highly sensitive to the threshold . To address the problem , a finite mixture model based topology inference algorithm is proposed . Firstly , a leaf node is selected from the original leaf‐node set , and then the similarities between the node and the other leaf nodes are measured , after which the original leaf‐node set is roughly divided into several subsets using the finite mixture model based on the measured similarities . The internal nodes corresponding to each subset could be inferred afterwards . Subsequently , the above procedures are applied for each subset obtained from rough division , and the process is iterated until all of the internal nodes are found . Analysis and simulation show that the proposed algorithm needs less correlation data than the existing algorithm , and performs almost as well as the existing algorithm with the optimum threshold .关键词
拓扑推断/网络层析成像/有限混合模型Key words
topology inference/network tomography/finite mixture model分类
信息技术与安全科学引用本文复制引用
张润生,刘健,李艳斌..利用有限混合模型的高效网络拓扑推断算法[J].西安电子科技大学学报（自然科学版）,2015,(4):133-139,7.基金项目
国家科技支撑计划资助项目（2011BA H24B04），中国博士后科学基金面上资助项目 （）
