4.7 Article

A decomposition-based multi-objective optimization approach for balancing the energy consumption of wireless sensor networks

Journal

APPLIED SOFT COMPUTING
Volume 107, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.asoc.2021.107365

Keywords

Wireless sensor networks; Network lifetime; Multi-objective evolutionary algorithm

Funding

  1. Vingroup Joint Stock Company, Vietnam
  2. Domestic Master/PhD Scholarship Programme of Vingroup Innovation Foundation (VINIF), Vingroup Big Data Institute (VINBIGDATA) [VINIF.2020.TS.105]

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This paper examines the optimization of network lifetime and the number of relay nodes in three-dimensional terrains, proposing a novel algorithm called MOEA/D-LS to achieve a better balance between two objectives. Simulation results show that the proposed algorithm outperforms existing algorithms on all measured metrics.
Wireless sensor networks consist of many sensor nodes with limited resources and computing capability. Thus, managing energy consumption to prolong network lifetime is a critical issue. Several approaches have been proposed to extend the network lifetime, one of which involves deploying relay nodes to transfer data from sensors to the base station. However, the limited number of relay nodes is a challenge that often goes overlooked. This paper examines the problem of optimizing the network lifetime and the number of relay nodes in three-dimensional terrains. A novel algorithm called MOEA/D-LS is proposed with the aim of obtaining a better tradeoff between two objectives. The algorithm is a hybridization between multiobjective evolutionary algorithm based on decomposition, and a special local search to optimize the former's subproblems. Simulation results on 3D datasets show that the proposed algorithm has a significantly better performance compared with existing algorithms on all measured metrics. (C) 2021 Elsevier B.V. All rights reserved.

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