A new metaheuristic approach based on orbit in the multi-objective optimization of wireless sensor networks
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A new metaheuristic approach based on orbit in the multi-objective optimization of wireless sensor networks Recep O¨zdag˘1
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Murat Canayaz1
Ó Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Wireless sensor networks (WSNs) is a research area which has been used in various applications and has continuously developed up to now. WSNs are used in many applications, especially in military and civilian applications, with the aim of monitoring the environment and tracking objects. For this purpose, increasing the coverage rate of WSNs is one of the important criteria that determine the effective monitoring of the network. Since the sensors that make up the WSNs have a limited capacity in terms of energy, process and memory, various algorithmic solutions have been developed to optimize this criterion. The effective dynamic deployment of sensor nodes, which is the primary goal of these solutions, has a critical role in determining the performance of the network. A new orbit-based dynamic deployment approach based on metaheuristic Whale Optimization Algorithm has been proposed in this study. The goal is to optimize the convergence speed of the nodes, the coverage rate of the network, the total displacement (movement) distances of sensors and the degree of kcoverage of each target (Grid) point in the area by effectively performing the dynamic deployments of sensors after their random distribution. This approach is compared with MADA-WOA and MADA-EM in the literature. Simulation results indicated that the approach developed in rapidly converging sensors to each other, increasing the network’s coverage rate, and in minimizing the total movement distances of the sensors in the area and the degrees of k-coverage of Grid points covered by the sensors could be proposed. Keywords Wireless sensor networks Sensor deployment Area coverage problem Whale optimization algorithm Binary detection model Degree of k-coverage
1 Introduction Recently, WSNs have attracted a lot of attention to themselves both in the field of application and in the field of academic research. With respect to the field of application, they are used in military and civilian applications requiring security such as environmental surveillance and monitoring of environments, in health practices and the detection of disasters. Along with the development of the WSNs, sensors have had the features such as the ability to make simpler calculations with lower cost and less energy ¨ zdag˘ & Recep O [email protected] Murat Canayaz [email protected] 1
Department of Computer Engineering, Van Yuzuncu Yil University, 65080 Van, Turkey
consumption, and performing better detection in the area where they are distributed [1]. WSNs consist of sensor nodes that have the features of detecting, communicating, and moving. Mobile nodes can change their location in the network due to their moving features and can be placed in the optimum position by constantly updating their location with dynamic depl
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