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Improving Displacement Number and Overheads of DRFN using Artificial Bee Colony Technique in WSNs
Author(s) -
Rajneet Kaur,
Shaveta Angurala
Publication year - 2015
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2015907377
Subject(s) - computer science , displacement (psychology) , artificial intelligence , psychology , psychotherapist
Failure in Wireless Sensor Networks is common due to deployment of sensor nodes in harsh or hostile environment with limited power backup. Node failures could degrade the efficiency of sensor networks. Thus, failure detection and recovery techniques are very crucial for effective performance of nodes in Wireless Sensor Networks. In this paper we presented an improved DRFN technique by improving its failover mechanism. The failure handling scheme will be improved by using Artificial Bee Colony (ABC) based optimization technique. We analyze existing DRFN technique and compare it with the proposed technique on the basis of performance metrics such as occurrence of displacements and displacement overheads. Experimental results show that the proposed failure detection and recovery technique outperform over the available technique. The presented scheme is implemented and analyzed in 2013 version of MATLAB simulation tool.

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