Exploiting Energy-aware Spatial Correlation in Wireless Sensor Networks

Abstract

Wireless sensor networks (WSNs) promise fine-grain monitoring in a wide variety of applications, which require dense sensor nodes deployment. Due to high density of nodes, spatially redundant or correlated data is generated. Redundancy increases the reliability level of information delivery but increases the energy consumption of the nodes too. Since energy conservation is a key issue for WSNs, therefore, spatial correlation can be exploited to deactivate some of the nodes generating redundant information. In this paper, we present an energy-aware spatial correlation based on a clustering protocol. In this approach, only the cluster-heads are responsible of exploiting spatial correlation of their member nodes and selecting the appropriate member nodes to remain active. The correlation is based on the distortion tolerance and the residual energy of member nodes. Each cluster-head divides its clustered region into correlation regions and selects a representative node in each correlation region which is closer to the center of correlation region and has the higher residual energy. Hence, the whole field is represented by a subset of active nodes which perform the task well. Simulation results prove that the required reporting rate can be achieved with lesser number of nodes by exploiting spatial correlation and eventually conserving the nodes energy.