Nangai Abinaya S, Sudha R
For many applications in wireless sensor networks (WSNs), users want to continuously extract data from the networks for analysis. In wireless sensor networks, sensor nodes in the area of interest must report the cognitive process to the sink by sensing, and this report will satisfies the report frequency required by the sink. This approach proposes a link-aware clustering mechanism, called LCM, which determines energy efficient and establishes the routing path. Node status and causal connection of the nodes, considers a fiction clustering metric called the predicted transmission count (PTX). Itevaluates the attribute of nodes for clusterheads and gateways to construct clusters. Each clusterhead or gateway nodes depends on this primary clustering metric, helps to derive the priority of nodes which is having the greatest priority becomes the clusterhead or gateway. Simulation results show that this technique is significantly forms the higher degree of the clustering and considers the residual energy and link condition in the packet delivery ratio and energy consumption.