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首页> 外文期刊>International journal of communication systems >Efficient probe selection for fault localization using the property of submodularity
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Efficient probe selection for fault localization using the property of submodularity

机译：利用子模量特性有效地选择探针进行故障定位

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摘要

As the computer network increasingly grows larger and more complex, fault diagnosis has become a challenging task. Active probing is an efficient tool for fault localization. By implementing some test programs and analyzing the results, active-probing-based techniques can perform diagnosis efficiently and adaptively. Because probes may generate additional traffic overhead, it is important to appropriately select small number of probes to reach the desired diagnostic capability. However, the computation of probe selection problem in such environment is extremely expensive. Most of the past works purchase the speed at the cost of diagnostic accuracy. In this paper, we first verify that probe selection problem satisfies the property of submodularity. Then we take the use of the property and develop a submodularity-based selection algorithm with following novel features: (i) it is cost effective, failure resistant and more accurate; (ii) it could deal with the uncertainties about the network structures and the observations; and (iii) it can select the required probes in near-linear time. Finally, we implement submodularity-based selection algorithm and other two representative probe selection algorithms (bounded path enumeration approximation algorithm and greedy search algorithm) on different settings of networks. The results have shown how the new algorithm outperforms the former two algorithms. Copyright © 2011 John Wiley & Sons, Ltd.
机译：随着计算机网络变得越来越大和越来越复杂，故障诊断已成为一项具有挑战性的任务。主动探测是故障定位的有效工具。通过实施一些测试程序并分析结果，基于主动探测的技术可以高效，自适应地执行诊断。由于探针可能会产生额外的流量开销，因此重要的是适当选择少量的探针以达到所需的诊断能力。但是，在这样的环境下探针选择问题的计算非常昂贵。过去的大多数作品都以诊断准确性为代价来购买速度。在本文中，我们首先验证探针选择问题满足亚模性质。然后，我们利用该特性，开发出具有以下新颖特征的基于亚模量的选择算法：（i）具有成本效益，抗故障能力和准确性； （ii）可以处理有关网络结构和观测结果的不确定性； （iii）可以在接近线性的时间内选择所需的探头。最后，我们在不同的网络设置上实现了基于亚模的选择算法和其他两个代表性的探针选择算法（有界路径枚举近似算法和贪婪搜索算法）。结果表明，新算法的性能优于前两种算法。版权所有©2011 John Wiley＆Sons，Ltd.

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