Energy-Efficient Clustering in Wireless Sensor Networks With Spatially Correlated Data

In this paper, the authors show how spatial correlation in data can be exploited to reduce energy consumption in a wireless sensor network. They analytically characterize the optimal cluster size, and then use a greedy clustering algorithm to study approximate solutions to the optimal data gathering problem. A Wireless Sensor Network (WSN) consists of a large set of sensor nodes that cooperate to monitor environmental conditions (e.g., temperature, precipitation, radioactivity) in a given geographic area. WSNs are often designed for long-term operation in remote unattended environments, despite the limited battery capacity of the wireless sensor nodes.