Energy optimization in wireless sensor networks based on genetic algorithms

Wireless sensor is a consolidated technology with high potential in the Internet of Things. However, some open issues must be tackled in order to leverage the whole potential of this technology. One of the challenges is the energy consumption. Many algorithms have been proposed for saving energy. However these approaches use a mono-objective evaluation and the contradiction between optimization parameters values is not considered. Besides these approaches don't offer a unique solution. This paper describes MOR4WSN an algorithm based in NSGA-II for selecting the best sensor distribution as well as a mechanism for optimization of results. Experimental evaluation shows promising results in terms of lifetime maximization.