Multi-objective clustered-based routing with coverage control in wireless sensor networks

Ozdemir S., Attea B. A., Khalil O. A.

SOFT COMPUTING, vol.17, no.9, pp.1573-1584, 2013 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 17 Issue: 9
  • Publication Date: 2013
  • Doi Number: 10.1007/s00500-012-0970-x
  • Journal Name: SOFT COMPUTING
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.1573-1584
  • Keywords: Coverage preservation, Clustering, Energy conservation, Evolutionary algorithms, Multi-objective optimization, Wireless sensor networks
  • Hacettepe University Affiliated: No


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. 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 both energy conservation routing protocols in a cluster-based WSNs and coverage-maintenance problems have been extensively studied in the literature, these two problems have not been integrated in a multi-objective optimization (MOO) manner. This paper employs a recently developed MOO algorithm, the so-called multi-objective evolutionary algorithm based on decomposition (MOEA/D) to solve simultaneously the energy conservation and coverage preservation design problems in cluster-based WSNs. The performance of the proposed approach, in terms of network lifetime and coverage is compared with the heuristic LEACH and SEP clustering protocols and with another prominent MOEA, the so-called non-dominated sorting genetic algorithm II (NSGA II). Simulation results reveal that MOEA/D provides a more efficient and reliable behavior over other approaches.