基于k阶马尔可夫链的单播网络丢包层析成像
doi: 10.3724/SP.J.1146.2010.00814
Unicast Network Loss Tomography Based on k-th Order Markov Chain
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摘要: 该文针对时域相关的网络链路丢包估计问题,提出一种基于k阶马尔可夫链的单播网络丢包层析成像方法。该方法首先引入k阶马尔可夫链描述网络链路丢包过程,然后用最大伪似然方法估计k阶马尔可夫链链路丢包模型的状态转移概率。当k足够大时,该文方法可以根据单播端到端测量数据,准确地估计出网络链路上每个数据包丢失的概率。ns-2仿真验证了该文方法的有效性。Abstract: This paper addresses the issue of temporal dependence network link loss inference, presents a k-th order Markov chain based unicast network loss tomography method. The method introduces firstly k-th order Markov Chain (k-MC) to describe the link packet loss process, and then uses pseudo maximum likelihood method to estimate the state transition probabilities of k-th order Markov chain. If k is large enough, then the method presented in this paper is capable of obtaining an accurate loss probability estimate of each packet based on unicast end-to-end measurements. ns-2 simulation validated the effectiveness of the method.
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