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Energy and Trust Aware Clustering based on Genetic Algorithm for Wireless Sensor Networks

Published on December 2015 by Soumitra Das, Sanjeev Wagh
National Conference on Advances in Computing
Foundation of Computer Science USA
NCAC2015 - Number 5
December 2015
Authors: Soumitra Das, Sanjeev Wagh
e4496e44-da87-4063-87e8-05c844232b03

Soumitra Das, Sanjeev Wagh . Energy and Trust Aware Clustering based on Genetic Algorithm for Wireless Sensor Networks. National Conference on Advances in Computing. NCAC2015, 5 (December 2015), 27-31.

@article{
author = { Soumitra Das, Sanjeev Wagh },
title = { Energy and Trust Aware Clustering based on Genetic Algorithm for Wireless Sensor Networks },
journal = { National Conference on Advances in Computing },
issue_date = { December 2015 },
volume = { NCAC2015 },
number = { 5 },
month = { December },
year = { 2015 },
issn = 0975-8887,
pages = { 27-31 },
numpages = 5,
url = { /proceedings/ncac2015/number5/23390-5058/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advances in Computing
%A Soumitra Das
%A Sanjeev Wagh
%T Energy and Trust Aware Clustering based on Genetic Algorithm for Wireless Sensor Networks
%J National Conference on Advances in Computing
%@ 0975-8887
%V NCAC2015
%N 5
%P 27-31
%D 2015
%I International Journal of Computer Applications
Abstract

Wireless Sensor Networks (WSNs) are gaining a lot of recognition, since it has extensive areas of applications. These networks consist of tiny sensor nodes, powered by a battery source having less power and computational capabilities. These nodes are mostly deployed in remote areas where it is very difficult to replace their batteries. As battery power is a crucial parameter in the algorithm design, a system based on clustering using a genetic algorithm has been proposed to maximize the lifespan of sensor nodes. In this clustering algorithm, energy is distributed and network performance is enriched by choosing cluster heads on the basis of (i) the remaining energy of sensor nodes (ii) nearest hop distance between the sensor nodes and (iii) trust of the sensor nodes. To further enhance the network lifetime, the proposed algorithm additionally implements a multihop routing mechanism from source sensor nodes to destination sink using intermediate cluster heads. To prove the effectiveness, this proposed algorithm has been simulated using Matlab and compared with "Design and Implementation of a New Energy Efficient Clustering Algorithm using Genetic Algorithm for Wireless Sensor Networks"(DINEECAGA)[11]. From the result analysis, it has been shown that the proposed algorithm is far better in terms of energy efficient than the (DINEECAGA) [11].

References
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  11. Mehr, Moslem Afrashteh. "Design and implementation a new energy efficient clustering algorithm using genetic algorithm for wireless sensor networks. "World Academy of Science, Engineering and Technology 52 (2011): 430-433.
  12. Norouzi, Ali, and A. Halim Zaim. "Genetic algorithm application in optimization of wireless sensor networks. " The Scientific World Journal 2014 (2014).
Index Terms

Computer Science
Information Sciences

Keywords

Genetic Algorithm Cluster Head Clustering Wireless Sensor Network Trust Multihop.