JCSE, vol. 13, no. 4, pp.163-174, 2019

DOI: http://dx.doi.org/10.5626/JCSE.2019.13.4.163

A Hybrid Approach for Prolonging Lifetime of Wireless Sensor Networks Using Genetic Algorithm and Online Clustering

Amin Rezaeipanah, Hamed Nazari, and Gholamreza Ahmadi
Department of Computer, Faculty of Computer, University of Rahjuyan Danesh Borazjan, Bushehr, Iran Department of Computer Engineering, Urmia University, Urmia, Iran Department of Computer Engineering, Persian Gulf University, Bushehr, Iran

Abstract: Currently, the technology advancements have led to significant growth in the application of wireless sensor networks (WSNs) and its remarkable developments. WSNs are the most applicable and least-cost sub-category of existing computer networks. However, WSNs still suffer from energy limitation challenges. Since the energy limitation challenges are not appropriately resolved, prolonging the lifetime of nodes by reducing energy consumption has obtained more attention in this literature. In this paper, while routing is being performed an online clustering approach has been developed for updating the sensors??clustering, if it is required. The proposed clustering is carried out based on three objectives including reducing the distance between nodes within a cluster, reducing the distance between the cluster head (CH) candidate nodes and the sink node, and online appropriate energy distribution of the nodes in each cluster for each routing round. The improved fuzzy C-means (FCM) algorithm is applied to perform clustering. Additionally, the genetic algorithm (GA) is used as the routing algorithm. In order to evaluate the performance of the proposed FCM-GA algorithm, the DirectTransmission, SH-MEER, and MH-FEER algorithms are compared with FCM-GA. The results show that the proposed FCM-GA algorithm outperforms other algorithms in terms of network lifetime and the number of sent packets.

Keyword: Wireless sensor networks; Online clustering; Improved FCM algorithm; Genetic algorithm.

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