Optimization of Energy Consumption Based Cluster-Head Selection in WSN for IOT Application

Wireless sensor networks (WSN) groups specialized transducers that provide sensing services to Internet of Things (IOT) devices with limited energy and storage resources. Since replacement or recharging of batteries in sensor nodes is almost impossible, power consumption becomes one of the crucial design issues in WSN. Clustering algorithm plays an important role in power conservation for the energy constrained network. Choosing a cluster head can appropriately balance the load in the network thereby reducing energy consumption and enhancing lifetime. The paper focuses on an efficient cluster head election scheme that rotates the cluster head position among the nodes with higher energy level as compared to other. Presence of selfish nodes is a very big problem in Wireless Networks. A selfish node doesn't forward packets and utilize to its own profit but it is hesitating using personal resources for others. If such activities occurs within most of the nodes in the network, the network is interrupted. Selfish behaviour detection is an essential condition in wireless networks. In our project we have described an efficient method for detection and punishment of a selfish node. Here we proposed a new framework is degree of intrinsic selfishness and the degree of extrinsic selfishness. Under the distributed node-selfishness management, a path selection criterion is designed to select the most reliable and shortest path in terms of RNs'. Degree of intrinsic selfishness nodes affected by their available resources, and the optimal reasons are determined by the source to stimulate forwarding multiservice of the RNs in the selected path. The algorithm considers initial energy, residual energy and an optimum value of cluster heads to elect the next group of cluster heads for the network that suits for IOT applications such as environmental monitoring, smart cities, and systems. Simulation analysis shows the modified version performs better than the LEACH protocol by enhancing the throughput by 60%, lifetime by 66%, and residual energy by 64%.