A Novel Fruit Fly Optimization Algorithm in Wireless Sensor Networks for Energy Efficient Routing

A Novel Energy-Efficient Min-Max Optimization (NEMO) is proposed to improve the data delivery performance in WSN. The NEMO scheme is used in the virtual grid (after partitioning the sensor field into uniform sized cells based on the number of nodes present in the sensor field) environment to periodically collect the data from the mobile sink through the cell headers. Here the movement of sink is based on controlled fashion (sink moves around the boundary of the sensor field environment) and collects the data from the border line cell headers. For efficient data delivery Fruit Fly Optimization (FFO) algorithm is applied here to find the best path by using the fitness value (smell concentration) calculated between the nodes based on the distance. Optimal path is chosen by first calculating the minimum hop count paths and then find the maximum of total fitness value along those paths. In that way best path is selected by considering the shortest path (since the fitness value is based on the distance) which improves the data delivery performance and also it minimizes the energy consumption. The proposed scheme enables the sensor nodes to maintain the optimal path towards the latest location of mobile sink by using the FFO algorithm which leads to maximize the network lifetime in wireless sensor networks.