Minimizing energy consumption in mission-specific mobile sensor networks by placing sensors and base station in the best locations: Genetic algorithms approach

Abstract

Motivated by recent developments in Wireless Sensor Neworks (WSNs), we present in this paper two new algorithms, namely Sensors Genetic Algorithm (SGA) and Base station Genetic Algorithm (BGA). We developed SGA and BGA in order to contribute to solve the energy constraint in a critical sensor network, where each sensor satisfies its own missions depending on its locations. The first algorithm (SGA) aims at equilibrating the mission and communication cost by placing each sensor in the best position relatively to the degree of mission satisfaction and the quality of communication between all nodes. The second algorithm (BGA) locates the Base Station (BS) with respect of available resources in the network. The comparison of our algorithms to other techniques displays that SGA and BGA are efficients in terms of convergence to the appropriate solutions of the complicated optimization problem posed in this case.