On the performance of quick artificial bee colony algorithm for dynamic deployment of wireless sensor networks

In recent years, the use of wireless sensor networks (WSNs) has increased and there have been significantimprovements in this field. Especially with smarter, cheaper, and smaller sensor nodes, various kinds of informationcan be detected and collected in different environments and under different conditions. WSNs have thus been used inmany applications such as military, surveillance, target tracking, home, medical, and environmental applications. As thepopularity of WSNs increases, problems related to these networks are being realized. The dynamic deployment problemis one of the main challenges that have a direct effect on the performance of WSNs. In this study, a novel optimizationtechnique named the quick artificial bee colony (qABC) algorithm was applied to the dynamic deployment problem ofWSNs. qABC is a new version of the artificial bee colony algorithm (ABC) and it redefines the onlooker bee phaseof ABC in a more detailed way. In order to see the performance of qABC on this problem, WSNs that include onlymobile sensors or both stationary and mobile sensors were considered with binary and probabilistic detection models.Some experimental studies were conducted for tuning the colony size (CS ) and neighborhood radius (r ) parameters ofthe qABC algorithm, and the performance of the proposed method was compared with the standard ABC algorithmand some other recently introduced approaches including a parallel ABC, a cooperative parallel ABC, a version of ABCpowered by a transition control mechanism (tlABC), and a parallel version of tlABC. Additionally, some CPU timeanalyses were provided for qABC and ABC considering different dimensions of the problem. Simulation results showthat the qABC algorithm is an effective method that can be used for the dynamic deployment problem of WSNs, and itgenerally improves the convergence performance of the standard ABC on this problem when r ≥ 1.

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