A new evolutionary based application specific routing protocol for clustered wireless sensor networks

Energy consumption is a major issue in designing wireless sensor networks. To achieve the energy efficiency, many routing protocols have been proposed and LEACH is the representative one. LEACH utilizes randomize rotation of the cluster heads to evenly distribute energy load among all nodes. However, it depends only on a probability model and energy efficiency could not be maximized. In this paper, a new application specific low power routing protocol named ASLPR is introduced that takes into account some concepts from sensor nodes (e.g., distance from base station, residual energy, distance between cluster heads) to elect the optimal cluster heads. As the proposed routing protocol is complex and has some controllable parameters, tuning of its parameters is an important problem to achieve the best performance based on the application. In this work, a hybrid algorithm based on genetic algorithm and simulated annealing is applied to optimize ASLPR in order to prolong the network lifetime, based on the application specifications. Simulation results demonstrate the efficiency of the proposed methodology to balance the energy consumption of nodes and maximize network lifetime. The gain (on average) in stable region of ASLPR until first node dies is 78%, as compared with three LEACH-based protocols.