Energy-efficient clustering method for wireless sensor networks using modified gravitational search algorithm
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ORIGINAL PAPER
Energy‑efficient clustering method for wireless sensor networks using modified gravitational search algorithm Sepehr Ebrahimi Mood1 · Mohammad Masoud Javidi1 Received: 14 May 2018 / Accepted: 4 January 2019 © Springer-Verlag GmbH Germany, part of Springer Nature 2019
Abstract Past decades have witnessed the advancement of wireless sensor networks (WSNs) in both academic and industrial communities. Clustering is one of the most popular methods to increase the lifespan of WSNs. The optimal number of cluster heads and how to organize the clusters are the most important issues to be addressed in the clustering methods. In this paper, we proposed a novel user-independent and dynamical method to calculate the optimal number of clusters, organize the clusters, and determine the best cluster heads in each round. In this method, efficient energy consumption and link quality were considered to compute the optimal number of clusters. Then, the algorithm began to organize the compact clusters with high energy level cluster heads. We investigated a new fitness function in order to achieve these objectives. A new version of gravitational search algorithm (GSA) was used to solve this optimization problem. In this algorithm, the power distance sums scaling method was applied to calculate the mass values. Then, a fuzzy logic controller is employed to identify the parameter of this algorithm to control the exploitation and exploration abilities of the method during the computational process of the algorithm. Then, the novel version of GSA was applied to reach an appropriate solution for the fitness function, find the optimal number of clusters, and properly organize these clusters. To evaluate the effectiveness of the proposed method, several experiments were performed and the obtained results were compared with the results of other popular clustering methods. The simulation results revealed that the performance of the modified GSA was better than other state-of-the-art meta-heuristic optimization algorithms. Moreover, the proposed method for the clustering problem in WSNs outperformed other popular clustering methods and increased the lifetime of WSNs. Keywords Wireless sensor network · Clustering methods · Energy consumption · Gravitational search algorithm · Fuzzy logic controller
1 Introduction Nowadays, Wireless Sensor Networks (WSNs) are an interesting field of research. These networks are used in many industrial problems and real-world applications, namely military applications (Akyildiz et al. 2002; Furtak et al. 2016), health monitoring (Edwards-Murphy et al. 2016; Rotariu et al. 2013), target tracking (Bin and Xinyun 2014), agriculture (Bapat et al. 2017; Abbasi et al. 2014), smart home (Li and Lin 2015; Mohammed and Duman 2017), etc. * Mohammad Masoud Javidi [email protected] Sepehr Ebrahimi Mood [email protected] 1
Department of Computer Science, Shahid Bahonar University of Kerman, Kerman, Iran
A WSN contains a large number of cheap and small sensor nodes located in the target area r
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