Energy-conserving data cache placement in sensor networks

Abstract

Wireless sensor networks hold a very promising future. The nodes of wireless sensor networks (WSN) have a small energy supply and limited bandwidth available. Since radio communication is expensive in terms of energy consumption, the nodes typically spend most of their energy reserve on wireless communication (rather than on CPU processing) for data dissemination and retrieval. Therefore, the role of energy conserving data communication protocols and services in WSN can not be overemphasized. Caching data at locations that minimize packet transmissions in the network reduces the power consumption in the network, and hence extends its lifetime. Finding locations of the nodes for caching data to minimize communication cost corresponds to finding the nodes of a weighted Minimum Steiner tree whose edge weights depend on the edge’s Euclidean length and its data traffic rate. We call this tree a Steiner Data Caching Tree (SDCT). We prove that an optimal SDCT is binary, and that at-least two of the three internal angles formed at the Steiner points are equal. We derive expressions that determine the exact location of a Steiner point for a set of three nodes based on their location and their data refresh rate requirements. Based on these (optimality) results, we present a dynamic distributed energy-conserving application-layer service for data caching and asynchronous multicast. We present the results of simulation of our service that verifies its power saving properties