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Sheng-Li Pan, Zhi-Yong Zhang, Ying-Jie Zhou, Feng Qian, Guang-Min Hu. Identify Congested Links Based on Enlarged State Space[J]. Journal of Computer Science and Technology, 2016, 31(2): 350-358. DOI: 10.1007/s11390-016-1631-9
Citation: Sheng-Li Pan, Zhi-Yong Zhang, Ying-Jie Zhou, Feng Qian, Guang-Min Hu. Identify Congested Links Based on Enlarged State Space[J]. Journal of Computer Science and Technology, 2016, 31(2): 350-358. DOI: 10.1007/s11390-016-1631-9

Identify Congested Links Based on Enlarged State Space

  • When paths share a common congested link, they will all suffer from a performance degradation. Boolean tomography exploits these performance-level correlations between different paths to identify the congested links. It is clear that the congestion of a path will be distinctly intensive when it traverses multiple congested links. We adopt an enlarged state space model to mirror different congestion levels and employ a system of integer equations, instead of Boolean equations, to describe relationships between the path states and the link states. We recast the problem of identifying congested links into a constraint optimization problem, including Boolean tomography as a special case. For a logical tree, we propose an up-to-bottom algorithm and prove that it always achieves a solution to the problem. Compared with existing algorithms, the simulation results show that our proposed algorithm achieves a higher detection rate while keeping a low false positive rate.
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