COMPASS - COllaborative Multiscale Processing and Architecture for SensorNetworkS

COMPASS is a new sensor network architecture that supports collaborative, multiscale data processing.

In a battery-powered sensor network, energy and communication bandwidth are both limited. Moreover, processing a sensor measurement locally often requires orders of magnitude less energy than communicating it to a distant node, yielding an interesting communication/computation tradeoff: whenever possible, the network should reduce the need for global communication at the expense of increased local processing and communication. A promising approach for reducing global communication is to perform signal processing to extract key information inside the sensor network in a distributed fashion, thus dramatically reducing global communication requirements without losing fidelity.

The COMPASS project is developing a new sensor network architecture whose communications hierarchy is aligned with the information flow of its computations. In particular, our research involves developing (1) a multioverlay sensor network architecture that supports both multiscale and proximity communication and computation; (2) new multiscale sensor data representations based on wavelet transforms; and (3) network services for sychronization and localization of network nodes. The research includes analysis, simulation, and a small-scale testbed of sensor nodes on the Rice University campus.

Authors: Richard G. Baraniuk, Peter Druschel, David B. Johnson, Matthias Heinkenschloss, T. S. Eugene Ng, Santashil PalChaudhuri, Shriram Sarvotham, Yanjun Sun, Raymond S. Wagner, Veronique Delouille, William Mantzel, Ramesh Neelamani

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