A survey of multi-objective optimization in wireless sensor networks: Metrics, algorithms and open problems

Abstract

Wireless sensor networks (WSNs) have attracted substantial research interest, especially in the context of performing monitoring and surveillance tasks. However, it is challenging to strike compelling trade-offs amongst the various conflicting optimization criteria, such as the network's energy dissipation, packet-loss rate, coverage and lifetime. This paper provides a tutorial and survey of recent research and development efforts addressing this issue by using the technique of multi-objective optimization (MOO) in WSNs. First, we provide an overview of the main optimization objectives used in WSNs. Then, we elaborate on various prevalent approaches conceived for MOO, such as the family of evolutionary algorithms (EAs) and the family of swarm intelligence optimization algorithms (SIOAs). Furthermore, we summarize a range of recent studies of MOO in the context of WSNs, which are intended to provide useful guidelines for researchers in the referenced literature. Finally, we discuss a range of open problems to be tackled by future research.

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ORCID for Lajos Hanzo: orcid.org/0000-0002-2636-5214

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