The coverage problem in a wireless sensor network
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
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MDAI '07 Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence
Q-Coverage Problem in Wireless Sensor Networks
ICDCN '09 Proceedings of the 10th International Conference on Distributed Computing and Networking
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INSS'09 Proceedings of the 6th international conference on Networked sensing systems
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SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
Artificial bee colony algorithm: a survey
International Journal of Advanced Intelligence Paradigms
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In this paper we address sensor deployment problem to achieve different types of target coverage, viz; simple coverage, k-coverage and Q-coverage. Energy which is an important and scarce resource is not being optimally used if sensor nodes are randomly deployed in a region. This energy wastage can significantly be reduced if the deployment positions can be optimally computed. It is important to provide required coverage by keeping the required sensing range at minimum which will require less energy for sensing. We find out the optimal deployment positions in a 3-D terrain using Artificial Bee Colony (ABC) algorithm, which is based on swarm intelligence, and also compare the sensing range requirement for simple, k and Q-coverage problems. Experimental results reveal that for dense networks, the required sensing range does not increase in same proportion for increased value of k and increased value of average number of sensor nodes in Q for k-Coverage and Q-Coverage problems respectively. Sensitivity analysis is done to study the change in the required sensing range if the sensor nodes cannot be deployed exactly in the optimal positions. The analysis reveals that there is no significant change in the sensing range if the sensor nodes are deployed in near optimal positions.