Derived Genetic Algorithm Optimizer for Energy Efficient Routing in Wireless Sensor Network

Abstract

Wireless sensor network is a type of network with spatially distributed nodes for the application of particular data. It consists of large number of sensor nodes with one or more base stations. The data is sent from sensor nodes to base station straightly or in multihop manner. Increasing the lifetime of network and less energy utilization are two key concerns for WSNs. Some energy-saving routing algorithms decrease total energy utilization of WSN, but they are difficult one in sending the data packets on many key nodes in order that these nodes drain out battery energy quickly through reducing network lifetime. In order to increase the energy efficiency and network lifetime, Derived Genetic Algorithm Optimizer for Energy Efficient Routing (DGAO-EER) scheme is introduced. GA is an effective one for energy efficient path finding in sensor network. GA collects the useful information about individuals from current nodes (i.e., gene). Initially, fitness function is presented to allocate the fitness value for every individual node. This function is used to find the nearby nodes to send the packets from source to sink node. Then, the data transfer of genetic information is carried out between two neighboring node to find another two neighboring nodes is called as crossover operation. Mutation restores the lost genetic values quickly when the node chooses the neighboring node. This process helps in increasing the lifetime of the network and energy efficiency. Performance results shows that the proposed DGAO-EER obtains the better performance in terms of energy consumption rate, energy drain rate, routing over head and routing delay as compared to the state-of-the-art works.