Exploring the Performance of Meta-Heuristic Searching for Wireless Sensor Networks Deployment

Abstract

Wireless Sensor Deployment WSD is an optimization research problem that aims to obtain the best configuration and locations of the sensor in the environment in order to optimize various performance metrics. Most importantly, the coverage of sensing and communication as well as the energy of sensors which affects the lifetime of the network. Thus, researchers formulate WSD as multi-objective optimization MOO problem, which requires evaluating the optimization algorithm based on the non-dominated solutions NDS and the evaluation metrics of MOO.  The literature contains a wide range of MOO approaches that were used for WSND. NSGA-II and NSGA-III are regarded as state of the art for MOO. In this article, we adapted three MOO algorithms NSGA-II, NSGA-III, and MOJPSO for WSD based on three objectives: coverage, lifetime, and cost represented by the number of sensors. The MOO is regarded as constrained optimization as we required achieving the connectivity for any acceptable solution. The comparison was based on the standard MOO evaluation metrics.