Topology-Based Failure Diagnosis Algorithm in Space Information Networks

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Abstract:

The space information networks are easy to be disturbed and destroyed, which is due to their hostile operational environments and results in a decrease in network quality of service. Given their characteristics, a distributed topology failure diagnosis scheme composed of failure detection node election and failure diagnosis is proposed. First, a proper number of nodes are elected to detect faults in a coordinated and distributed way by using minimum dominating set algorithm. Then elected diagnosis nodes detect faults around based on the theory of dependency-graph. The technology of minimum Huffman tree is used to preliminarily locate failures and on that base the further location is fulfilled through sending detection messages on purpose. Simulation results from NS2 demonstrate that high accurate diagnosis rate can be reached at the expense of low cost by this failure diagnosis algorithm.

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956-962

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June 2011

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© 2011 Trans Tech Publications Ltd. All Rights Reserved

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[1] Wenxue Qian, Liyang Xie, Dayan Huang, Xiaowei Yin: System Reliability Analysis and Fault Diagnosis Based on Bayesian Network, ISA 2009 International Workshop on Intelligent Systems and Application, Wuhan(2009).

DOI: 10.1109/icma.2009.5246614

Google Scholar

[2] Ko Y B, Vaidya NH: Location-Aided Routing (LAR) Mobile Ad Hoc Networks, Proceedings of the fourth annual international conference on Mobile computing and networking (Mo-biCom 98). Dallas, Texas(1998).

DOI: 10.1145/288235.288252

Google Scholar

[3] Bulusu N, Heidemann J, Estrin D: GPS-less Low Cost Out-door Localization for Very Small Devices, IEEE Personal Communications Magazine Vol. 7 (2000), 35-37.

DOI: 10.1109/98.878533

Google Scholar

[4] Hu Fangxia, Liu Jie, Chen Xinglong: Fault Diagnosis of Gas Blower on Genetic Fussy Neural Network, WCSE'09. WRI World Congress on Software Engineering, Xiamen(2009).

DOI: 10.1109/wcse.2009.217

Google Scholar

[5] Bin Wu, Kwan L. Yeng: Monitoring Cycle Design for Fast Link Failure Detection in All-Optical Networks, Global Telecommunications Conference, Washington, DC (2007).

DOI: 10.1109/glocom.2007.441

Google Scholar

[6] Bin Wu, Pin-Han Ho, Kwan L. Yeng: Monitoring Trail- a New Paradigm for Fast Link Failure Localization in WDM Mesh Networks, Global Telecommunications Conference, New Orleans, LO. (2008).

DOI: 10.1109/glocom.2008.ecp.519

Google Scholar