Abstract
In recent years, the use of wireless sensor networks (WSNs) has increased and there have been significant improvements in this field. Especially with smarter, cheaper, and smaller sensor nodes, various kinds of information can be detected and collected in different environments and under different conditions. WSNs have thus been used in many applications such as military, surveillance, target tracking, home, medical, and environmental applications. As the popularity of WSNs increases, problems related to these networks are being realized. The dynamic deployment problem is one of the main challenges that have a direct effect on the performance of WSNs. In this study, a novel optimization technique named the quick artificial bee colony (qABC) algorithm was applied to the dynamic deployment problem of WSNs. qABC is a new version of the artificial bee colony algorithm (ABC) and it redefines the onlooker bee phase of ABC in a more detailed way. In order to see the performance of qABC on this problem, WSNs that include only mobile 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 of the qABC algorithm, and the performance of the proposed method was compared with the standard ABC algorithm and some other recently introduced approaches including a parallel ABC, a cooperative parallel ABC, a version of ABC powered by a transition control mechanism (tlABC), and a parallel version of tlABC. Additionally, some CPU time analyses were provided for qABC and ABC considering different dimensions of the problem. Simulation results show that the qABC algorithm is an effective method that can be used for the dynamic deployment problem of WSNs, and it generally improves the convergence performance of the standard ABC on this problem when $r \geq 1$.
Highlights
Wireless sensor networks (WSNs) are important topics in network science and one of the main focuses of researchers is to improve their performance in order to make them more comfortable for different applications
In order to see the performance of the quick artificial bee colony (qABC) on the dynamic deployment problem of WSNs, first a series of experiments were carried out considering different scenarios
Performance of the qABC was compared with some other optimization methods including the artificial bee colony (ABC), a parallel ABC [24], a cooperative parallel ABC [24], a version of the ABC powered by a transition control mechanism [25], and a parallel version of the tlABC (p-tlABC) [25] on the dynamic deployment problem of WSNs
Summary
Wireless sensor networks (WSNs) are important topics in network science and one of the main focuses of researchers is to improve their performance in order to make them more comfortable for different applications. Ozturk et al applied the ABC algorithm to the problem of dynamic deployment of WSNs consist of only mobile sensors considering a binary detection model [4]. Aslan et al examined the performance of a parallelized implementation of ABC on solving the dynamic deployment problem considering a probabilistic detection model and a network that includes only mobile sensors [22]. Yadav et al proposed a modified version of ABC by addressing two drawbacks of the standard ABC algorithm using a crossover operator and a hybrid local search, and they tested its performance on a dynamic deployment problem with mobile sensors and considered a probabilistic detection model [23].
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