A robust harmony search algorithm based clustering protocol for wireless sensor networks

Optimizing energy consumption is the main concern for designing and planning the operation of the Wireless Sensor Networks (WSNs). Clustering technique is one of the methods utilized to extend lifetime of the network by applying data aggregation and balancing energy consumption among sensor nodes of the network. In this paper, we propose the recently developed, Harmony Search Algorithm (HSA) for minimizing the intra-cluster distance and optimizing the energy consumption of the network. HSA is music based metaheuristic optimization method which is analogous with the music improvisation process where musician continue to polish the pitches in order to obtain better harmony. A comparison is made with the well known cluster-based protocol approach developed for WSNs known as Low-Energy Adaptive Clustering Hierarchy (LEACH), heuristic optimization algorithms like Particle Swarm Optimization (PSO) and Genetic Algorithm(GA) as well as the traditional K-means and Fuzzy C-Means (FCM) clustering algorithms. Simulation results demonstrate that the proposed protocol using HSA can reduce energy consumption and improve the network lifetime.