Multi-Objective Set Cover Problem for Reliable and Efficient Wireless Sensor Networks - Ali Attea, Bara’a (Iraqi Journal of Science, 2023)
Achieving energy-efficient Wireless Sensor Network (WSN) that monitors all targets atall times is an essential challenge facing many large-scale surveillance applications.Singleobjectiveset cover problem (SCP) is a well-known NP-hard optimization problem used toset a minimum set of active sensors that efficiently cover all the targeted area. Realizingthat designing energy-efficient WSN and providing reliable coverage are in conflict witheach other, a multi-objective optimization tool is a strong choice for providing a set ofapproximate Pareto optimal solutions (i.e., Pareto Front) that come up with tradeoffbetween these two objectives. Thus, in the context of WSNs design problem, our maincontribution is to turn the definition of single-objective (SCP) into a multi-objectiveproblem by adopting an additional conflicting objective to be optimized. To the best of ourknowledge, improving coverage reliability of WSNs has not been explored whilesimultaneously solving SCP problem. This paper addresses the problem of improvingcoverage reliability of WSNsusing a realistic sensing model to handle coverage uncertainty.To this end, this paper formulates the so-called multi-objective SCP with the goal ofselecting the minimum number of sensors so that the selected set reliably covers all thetargets.To cope with two optimization objectives rather than one objective, thispaperinvestigates the use of a multi-objective evolutionary algorithm, the so-called nondominatedsorting genetic algorithm for tackling the formulated problem. Moreover, itadopts a heuristic crossover operator designed specifically to improve the performance ofthe algorithm.The effectiveness of the algorithm is verified in terms of sensors cost andcoverage reliability under extensive simulations