Multi-objective Evolutionary Algorithms for Energy-Efficiency in Heterogeneous Wireless Sensor Networks

Nowadays the use of wireless sensor networks is a common activity. For this reason there are many works trying to solve one of the main inconveniences of the wireless sensor networks: the energy consumption. Traditionally, these networks were composed only by sensors, but now routers have been included in order to facilitate communication among sensors and reduce energy consumption at the same time. In this work, we have studied the deployment of a heterogeneous wireless sensor network optimizing some factors: area covered average number of hops and network reliability. For this purpose, we have used two multi-objective evolutionary algorithms: NSGA-II and SPEA-II. We have done experiments over various scenarios, checking by means of statistical techniques that SPEA-II offers better results than its competitor.