Data Aware Clustering for Data Gathering in Wireless Sensor Networks

Abstract

The data fusing ability of cluster head is affected by the correlation of sensed data from different nodes in Wireless sensor networks, which are data centered. This paper analyses the influence of regional data correlation on energy efficiency of clustering protocol, and then proposes a data aware clustering for data gathering (DACDG). DACDG uses residual energy and the correction of sensed data from neighbors to construct clusters, and adopts the way of iterative computing to elect cluster head. Compared with existing protocols, simulation results show that DACDG achieves its goals of consuming less energy, equalizing the energy consumption of all the nodes, as well as extending the network lifetime outstandingly.