An Energy Efficient Spatial Correlation Based Data Gathering Algorithm for Wireless Sensor Networks
Wireless sensor networks have a wide range of applications including environmental monitoring. These networks consist of wireless sensor nodes which are densely deployed to provide a wider coverage area. The dense deployment of the sensor node provides spatial correlation in the network. In this paper, an efficient data gathering approach is implemented by combining the dual prediction and clustering algorithm. Clustering algorithm based on spatial correlation is used to cluster the sensor nodes. Then within the cluster, the nodes send their data to the sink using the normalized least mean square dual prediction algorithm. Simulation results show that the proposed algorithm reduces the average energy consumption of the network.