WITHDRAWN: Optimal path selection with clustering in wireless sensor networks

Abstract

Wireless networks are accomplished with heterogeneous autonomous tiny nodes for the communication. The main functionality of the node is sensing. This sensed data is gathered and carried to the nearest sink node or a cluster head then transmitted to the base station. There are many issues to consider but routing is the vital, fundamental and challenging issue which has to be addressed for efficient data transmission and also to increase the lifespan of the network. In todays network models the route is overhead for the transmission of the data, towards the dynamic nature of the network framework, every time the model has to redesign for the shortest path to reach the base station. The nature of introducing machine learning will enhance the life time of the networks and also to predict the shortest path, with the parameters as energy, delay, error, packet size, Qos etc. The aim of the work is that the model itself should learn to predict the optimal path by its experiences to decrease the latency with efficiency.