Shortest path routing in solar powered WSNs using soft computing techniques
The main objective of this paper is to develop a three phase genetic algorithm to find the shortest path routing in solar poweredWireless Sensor Networks (WSNs), and thereby reducing the energy loss and the time consumed in the communication between various nodes (sensors) of the same. A three phase hybrid genetic algorithm is proposed for solving the shortest Path (SP) routing problem. The performance of the proposed algorithm is compared with Dijkstra, Munemoto, and Ahn algorithms. Here we have classified the wireless sensors as clusters which uses k-means clustering algorithm and within each cluster the shortest path routing for communication is found out using proposed three phase genetic algorithms.