Year of Publication: 2012
Page Numbers: 65-73
Authors: Suat Ozdemir, Bara'a Attea, Onder Khalil
Conference Name: The International Conference on Computing, Networking and Digital Technologies (ICCNDT2012)
- Bahrain


A wireless sensor network (WSN) generally consists of a large number of inexpensive power constrained sensors that are small in size and communicate over short distances to perform a predefined task. Besides military applications, WSNs have been realized their ability in other applications including wildlife habitats monitoring, target detection, and health care applications. However, realizing the full potential of WSN poses many design problems, especially those which involve tradeoffs between multiple conflicting optimization objectives such as coverage preservation and energy conservation. While many efforts were made in the area of WSN design problems employing solutions inspired from nature, the focus, however, were typically on a single optimization objective. For example, while both energy conservation in a cluster-based WSNs and coverage- maintenance protocols have been extensively studied in the past, these have not been integrated in a multi-objective optimization manner. This paper employs a recently developed multi-objective optimization algorithm, the so-called multi- objective evolutionary algorithm based on decomposition (MOEA/D) to solve simultaneously the coverage preservation and energy conservation design problems in cluster-based WSNs. The performance of the proposed approach, in terms of coverage and network lifetime is compared with other evolutionary approaches including the weighted genetic algorithm and NSGA II. Simulation results reveal that MOEA/D provides a more efficient and reliable behavior over other approaches.