Heuristic Clustering for Wireless Sensor Networks using Genetic Approach

To save energy in wireless sensor network, clustering is an effective method due to its support for data compression, data centric and randomization. The clustering structure functions to the exchange of schedules; the transfer of data packets and use randomization for rotating clusters to balance the energy. There are several design issues in clustering like limited energy, network lifetime, limited abilities, application dependencies, etc. In this paper, we propose a Genetic Algorithm (GA) to optimize sensor nodes' energy consumption with clustering technique as it is convenient to reduce energy consumption and traffics in the network. We use a multi-objective algorithm that generates an optimal number of sensor-clusters with cluster-heads and minimizes the cost of transmission. The components are thereafter used and the average fitness of the system is evaluated. The effectiveness of our algorithm is shown by simulation.