Optimizing Energy in WSN using Evolutionary Algorithm

Wireless sensor network (WSN) open up new application area such as intelligent environmental and structural monitoring. One of the major challenges in WSN lies in the constraint energy and computation resource available in the sensor nodes. This paper deals with minimizing the energy resource of the wireless sensor nodes and maximizing its life time. When an event is detected in a particular area, all the nodes around the sensing range will collect the data and forward it to the upstream nodes. This makes wastage of energy because all the nodes are involved in sensing, processing and transmitting the same data.. WSN should be energy efficient in term of energy consumption and quality of path that are used to route the packets, towards the data collecting point called sink. Next node selection is based on minimum cost value. The cost depends on link quality residual energy and number of successive transmission. Genetic algorithm is used to optimize the minimum cost function. By using evolutionary optimization method minimum number of nodes is selected to obtain the optimal route.