Spatial Correlation Based Clustering Algorithm for Random and Uniform Topology in WSNS

Abstract

In Wireless Sensor Networks (WSN) sensor nodes with similar readings can be grouped such that, it is enough to report a single reading from the entire group. A representative node is selected from each cluster to do the reporting job. This helps to increase the battery life of sensor nodes. However, efficiently identifying sensor groups and their representative nodes is a challenging task. In this paper, a distributed algorithm is proposed to determine a set of representative nodes which exploits the tradeoff between data quality and energy consumption. In this paper, we group the sensor nodes based on their inherent spatial and data correlation in WSN. The proposed clustering algorithm is applied for uniform and random topology of sensor network. The results based on different metrics such as average number of clusters formed, energy consumption and average variation in cluster size are compared for both topologies.

Spatial Correlation Based Clustering with Node Energy Based Multi-Hop Routing Scheme for Wireless Sensor Networks

“…But as the area of the sensor network grows in size, this particular mechanism can only support shorter network life time with reduced throughput. Standard algorithms like LEACH and its recent variants [4][5][6][7][8][9][10][11][12][13][14][15] are the examples of this particular approach. Here in this paper, we have proposed a cluster based multihop data transfer mechanism from the cluster head to the sink based on spatial correlation [16][17][18][19][20][21][22][23] between the scattered nodes.…”