Coverage Maximization and Energy Conservation for Mobile Wireless Sensor Networks: A Two Phase Particle Swarm Optimization Algorithm

Nor Azlina Ab. Aziz, Ammar W. Mohemmed, Mohamad Yusoff Alias, Kamarulzaman Ab. Aziz and Syabeela Syahali
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Nor Azlina Ab. Aziz: Multimedia University, Malaysia
Ammar W. Mohemmed: Knowledge Engineering & Discovery Research Institute, Auckland University of Technology, New Zealand
Mohamad Yusoff Alias: Multimedia University, Malaysia
Kamarulzaman Ab. Aziz: Multimedia University, Malaysia
Syabeela Syahali: Multimedia University, Malaysia

International Journal of Natural Computing Research (IJNCR), 2012, vol. 3, issue 2, 43-63

Abstract: WSN is a group of low-cost, low-power, multifunctional and small size wireless sensor nodes that work together to sense the environment, perform simple data processing and communicate wirelessly over a short distance. Mobile wireless sensor networks (WSN) coverage can be enhanced by moving the sensors so that a better arrangement is achieved. However, movement is a high energy consumption task. To maximize coverage the sensors need to be placed not too close to each other so that the sensing capability of the network is fully utilised; however they must not be located too far from each other to avoid coverage holes. It is desired to achieve optimal coverage and at the same time not to relax the mobility energy consumption issue due to the fact that sensors have a limited energy supply. This research is interested in solving the coverage and energy conservation issues of mobile wireless sensors using PSO. In this paper the WSN coverage maximization problem is considered by taking into account the energy spent for sensor repositioning. Thus there are two objectives to be optimized, namely maximizing the coverage and conserving the energy. The two objectives are tackled one by one, starting with the coverage maximization followed by energy conservation. Hence a two-phase PSO approach is proposed. The results show that the proposed algorithm successfully achieves its objectives to reduce the energy usage while at the same time improve the coverage. The energy usage is reduced by cutting down the maximum distance moved.

Date: 2012
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