Journal of South China University of Technology (Natural Science Edition) ›› 2010, Vol. 38 ›› Issue (11): 110-116.doi: 10.3969/j.issn.1000-565X.2010.11.020

• Computer Science & Technology • Previous Articles     Next Articles

An Approach to Fast Inferring Link State Probability Based on End-to-End Measurement

Zhao Zuo  Cai Wan-dong   

  1. School of Computer Science and Technology,Northwestern Polytechnical University,Xi＇an 710129,Shaanxi,China
  • Received:2009-09-23 Revised:2010-06-01 Online:2010-11-25 Published:2010-11-25
  • Contact: 赵佐（1974-），男，博士生，主要从事网络测量与性能评价研究． E-mail:zhaozuo@nwpu．edu．cn
  • About author:赵佐（1974-），男，博士生，主要从事网络测量与性能评价研究．
  • Supported by:

    教育部博士点基金资助项目（200806990030）; 西北工业大学科技创新基金资助项目（2008KJ02028）

PDF

938

Abstract:

As a kind of prior knowledge,link state probability distribution plays an important role in inferring the accuracy of link performance state.This paper deals with the inference of internal link state probability based on the end-to-end measurement in tree topology,and defines it as a maximum likelihood estimation problem.By using a product model to describe the relationship between the path and the link state probability and by estimating link state probability via the computation of path state probability,a new approach to the fast inference of link state probability is proposed.The approach is then applied to simulation experiments.The results indicate that the proposed approach is effective and practical in inferring the internal link state probability.

Key words: Boolean network tomography, link state probability inference, end-to-end measurement, product mo-del, path state probability