An Analytical Study Of Hierarchy Protocol For Energy Conservation In Wireless Sensor Networks

  • N.Sivakumar et. al

Abstract

Abstract Wireless Sensor networks plays a vital role in the recent technologies.WSN consists of group of sensor nodes and monitors the environment for application without having any central controller. The sensor networks consist of sensed data, which may be depending upon the applications in real time. The networks transfer the large amount of data, broadcast messages from one node to another. These Application required high performance on the network without affecting the resource constraints.  Wireless devices are having limited energy because nodes are operated by batteries. The main challenge in the WSN is the durability of the energy in the nodes. By using the protocol the energy of the nodes can be stable and reduce the error prone transmission of sensored data. In this paper, The use of low power sensor nodes to collect useful sensing information effectively is critical for any wireless sensor network (WSN) application to last longer. To increase network lifetime, energy consumption is considered as one of an essential performance metric. Most of the current proposed routing protocols proposed to reduce the amount of energy consumed and to increase the network lifetime. The common pioneer hierarchical routing protocol for wsn such as Low Energy Adaptive Cluster Hierarchical Routing (LEACH) is also proposed to improve the energy efficiency of WSN. LEACH is a cluster based routing protocol in which sensor nodes are combined together to form separate clusters and every cluster has a leader node named cluster head (CH). In this paper, we have done the analytical study of LEACH protocol to identify to what extent LEACH protocol can perform in terms of average energy consumption and packet loss for different data rate. The Analysis of LEACH (Low Energy Adaptive Clustering Hierarchy) Protocol and TEEN (Threshold Sensitive Energy Efficient Sensor Network) protocol to conserve the energy of the nodes in the Wireless sensor networks.

Published
2019-12-06