Genetic algorithm based approach for cluster formation in wireless sensor networks

In wireless sensors networks (WSNs) the efficient use of the sensors´ energy is a key point to extend the network lifetime. In the literature there are several different techniques to reduce the energy consumption of the sensors. Sensor node clustering is one of these techniques commonly used. However, finding an optimal clustering in WSNs is a NP-Hard problem, thus heuristics and metaheuristics are the appropriate methods to find good clustering in reasonable computational time. In this work we propose the application of a simple and efficient metaheuristic based on genetic algorithms to obtain near-optimal clustering. We develop a clustering protocol to simulate the clusters formation and data transmission. The good performance of our protocol is compared with the well-known and commonly used clustering protocols for WSNs: LEACH and LEACH-C. The obtained results reveal that the genetic algorithm determines better clusters extending the network lifetime.