Temporal Dependence Network Link Loss Inference from Unicast End-to-End Measurements

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概要

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• In this letter, we address the issue of estimating the temporal dependence characteristic of link loss by using network tomography. We use a k-th order Markov chain (k>1) to model the packet loss process, and estimate the state transition probabilities of the link loss model using a constrained optimization-based method. Analytical and simulation results indicate that our method yields more accurate packet loss probability estimates than existing loss inference methods.

• 2012-06-01

著者

• Hu Guangmin

  School Of Communication And Information Engineering University Of Electronic Science And Technology Of China

• HU Guangmin

  School of Communication and Information Engineering, University of Electronic Science and Technology of China

• FEI Gaolei

  School of Communication and Information Engineering, University of Electronic Science and Technology of China

関連論文

• Temporal Dependence Network Link Loss Inference from Unicast End-to-End Measurements
• Network-Wide Anomaly Detection Based on Router Connection Relationships
• A Fast Link Delay Distribution Inference Approach under a Variable Bin Size Model

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