Optimal coverage of Wireless Sensor Network using Termite Colony Optimization Algorithm

Due to great advancement in the field of science and technology, Wireless Sensor Network (WSN) has been become one of the most attractive and intriguing research area in last few years. Large-scale sensor networks has been deployed by interconnecting several hundred to a few thousand sensors nodes o...

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Bibliographic Details
Published in2015 International Conference on Electrical Engineering and Information Communication Technology (ICEEICT) pp. 1 - 6
Main Authors Das, Pronaya Prosun, Chakraborty, Nirjhar, Allayear, Shaikh Muhammad
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2015
Subjects
Linear programming
Logic gates
metaheuristics
Monitoring
NP-hard
Robustness
Sensors
Sociology
Statistics
termite colony optimization
Wireless sensor network
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Summary:Due to great advancement in the field of science and technology, Wireless Sensor Network (WSN) has been become one of the most attractive and intriguing research area in last few years. Large-scale sensor networks has been deployed by interconnecting several hundred to a few thousand sensors nodes opens up diverse technical challenges and tremendous application possibilities. This paper presents a Termite Colony Optimization (TCO) algorithm, an adaptable and balanced way, which optimizes a minimal number of sensors while covering a maximum area. TCO is a population based metaheuristic approach developed from the intelligent behavior of termite that is known to us as Swarm Intelligence. It has the ability to solve the presented problem in efficient way that has shown more effectiveness and robustness compared to other population based algorithms. In this paper, we have justified our simulation results with the results of other papers. After that we have experimented with varying different parameters like grid size, number of sensors and termites. It has also proved the capability of our TCO over the constraints and difficulties as well.
DOI:10.1109/ICEEICT.2015.7307523