A NOVEL HIERARCHICAL CLUSTERING APPROACH FOR DIAGNOSING LARGE– SCALE WIRELESS ADHOC SYSTEMS

We propose a scalable distributed diagnosis approach for large-scale self-diagnosable wireless adhoc networks that form an arbitrary network topology. The diagnosis strategy assumes multiple initiators for the diagnosis process in contrast to a single initiator centralized bottleneck and also avoids...

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Published in:International journal of computers & applications 2009-10, Vol.31 (4), p.1
Main Authors: Khilar, P.M., Mahapatra, S.
Format: Article
Language:English
Subjects:
Algorithms
Fault diagnosis
Network topologies
Scalability
Simulation
Wireless networks
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Mahapatra, S.
description We propose a scalable distributed diagnosis approach for large-scale self-diagnosable wireless adhoc networks that form an arbitrary network topology. The diagnosis strategy assumes multiple initiators for the diagnosis process in contrast to a single initiator centralized bottleneck and also avoids a costly distributed diagnosis algorithm where every node is an initiator of the diagnosis process. Key results of this paper include realistic testing mechanism and fault models, an efficient and scalable distributed diagnosis algorithm using clustering, a global diagnosis strategy of all the nodes. The proposed approach has been evaluated analytically as well as through simulation. The diagnosis latency and message complexity of the algorithm was found to be O(ΔTx + lcTf + max(Tout1, Tout2)) and O(ncCs) respectively. The result shows that the diagnosis performance is better using the proposed clustering approach than non-clustering approaches. [PUBLICATION ABSTRACT]
doi_str_mv 10.2316/Journal.202.2009.4.202-2513
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subjects Algorithms
Fault diagnosis
Network topologies
Scalability
Simulation
Wireless networks
title A NOVEL HIERARCHICAL CLUSTERING APPROACH FOR DIAGNOSING LARGE– SCALE WIRELESS ADHOC SYSTEMS
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