Tracking and exploiting correlations in dense sensor networks
In this paper, we propose a novel method for reducing energy consumption in a sensor network. It is important in a sensor network to minimize the energy usage of each sensor, because the nodes typically have finite battery life and if a node dies, this can lead to a loss of data or a network partition. As a result, several researchers have proposed various methods of routing and communication between nodes to reduce energy consumption. We propose an orthogonal approach to previous methods. In particular, we propose to exploit the inherent correlations that exist between sensor nodes by devising a novel algorithm that enables sensor nodes to compress their readings without knowing the exact measurements of the other nodes. Our simulations show that our algorithm used is promising as it leads to significant energy saving for various types of sensor nodes.