Data-Driven Processing in Sensor Networks

Wireless sensor networks are poised to enable continuous data collection on unprecedented scales, in terms of area location and size, and frequency. This is a great boon to fields such as ecological modeling. We are collaborating with researchers to build sophisticated temporal and spatial models of forest growth, utilizing a variety of measurements. There exists a crucial challenge in supporting this activity: network nodes have limited battery life, and radio communication is the dominant energy consumer. The straightforward solution of instructing all nodes to report their measurements as they are taken to a base station will quickly consume the network’s energy. On the other hand, the solution of building models for node behavior and substituting these in place of the actual measurements is in conflict with the end goal of constructing models. To address this dilemma, we propose data-driven processing, the goal of which is to provide continuous data without continuous reportin...

• Type: Conference
• Year: 2007
• Where: CIDR
• Authors: Adam Silberstein, Gregory Filpus, Kamesh Munagala, Jun Yang 0001
• Keywords: Algorithms, CIDR 2007, Continuous Data, Continuous Data Collection, Data Collection