A Unified approach for Selecting Probes and Probing Stations for Fault Detection and Localization in Computer Networks

Fault detection and localization is a central element in the management of network failures. It allows inferring the exact failure of a network from all the observed symptoms. Because failures in network systems are inevitable, detection and diagnosis efficiency is important for the stability, coherence and performance of a communication system. In this paper, we propose a unified approach to diagnosing nodes faults in a computer network. In our approach, the problems of choosing probing stations and probes, classically separated, are solved jointly in order to obtain, with lower complexity, minimum sets of probes and probing stations capable of detecting and localizing any failed node. The optimality of our new method has been tested through the simulation of the network configuration.

[1]  Vinay K. Pathak,et al.  Survey of Probe Set and Probe Station Selection Algorithms for Fault Detection and Localization in Computer Networks , 2015 .

[2]  Ehab Al-Shaer,et al.  Overlay Fault Diagnosis Based on Evidential Reasoning , 2009, IEEE INFOCOM 2009.

[3]  Mingyan Liu,et al.  A distributed monitoring mechanism for wireless sensor networks , 2002, WiSE '02.

[4]  Otman A. Basir,et al.  A new probing scheme for fault detection and identification , 2009, 2009 IEEE International Conference on Electro/Information Technology.

[5]  Genady Grabarnik,et al.  Active Probing , 2002 .

[6]  L.W. Chu,et al.  Internet service fault management using active probing in uncertain and noisy environment , 2009, 2009 Fourth International Conference on Communications and Networking in China.

[7]  Sheng Ma,et al.  Adaptive diagnosis in distributed systems , 2005, IEEE Transactions on Neural Networks.

[8]  Otman Basir,et al.  Fusion Based Approach for Distributed Alarm Correlation in Computer Networks , 2010, 2010 Second International Conference on Communication Software and Networks.

[9]  M. Natu,et al.  Efficient Probing Techniques for Fault Diagnosis , 2007, Second International Conference on Internet Monitoring and Protection (ICIMP 2007).

[10]  Bhawani Sankar Biswal,et al.  A Survey on Greedy Based Algorithms for Biclustering of Gene Expression Microarray Data , 2016, 2016 International Conference on Information Technology (ICIT).

[11]  Andreas Terzis,et al.  Practical Passive Lossy Link Inference , 2005, PAM.

[12]  Maitreya Natu,et al.  Active Probing Approach for Fault Localization in Computer Networks , 2006, 2006 4th IEEE/IFIP Workshop on End-to-End Monitoring Techniques and Services.

[13]  Russell R. Barton,et al.  Zone recovery methodology for probe-subset selection in end-to-end network monitoring , 2002, NOMS 2002. IEEE/IFIP Network Operations and Management Symposium. ' Management Solutions for the New Communications World'(Cat. No.02CH37327).

[14]  G. Jakobson,et al.  Alarm correlation , 1993, IEEE Network.

[15]  Malgorzata Steinder,et al.  A survey of fault localization techniques in computer networks , 2004, Sci. Comput. Program..

[16]  Krishna R. Pattipati,et al.  Fault Localization Using Passive End-to-End Measurements and Sequential Testing for Wireless Sensor Networks , 2012, IEEE Trans. Mob. Comput..

[17]  Raouf Boutaba,et al.  Efficient Active Probing for Fault Diagnosis in Large Scale and Noisy Networks , 2010, 2010 Proceedings IEEE INFOCOM.

[18]  Youxian Sun,et al.  A new fault detection method for computer networks , 2013, Reliab. Eng. Syst. Saf..

[19]  Maitreya Natu,et al.  Efficient probe selection algorithms for fault diagnosis , 2008, Telecommun. Syst..

[20]  John Augustine,et al.  Probe station selection algorithms for fault management in computer networks , 2010, 2010 Second International Conference on COMmunication Systems and NETworks (COMSNETS 2010).