COMPASS
COllaborative Multiscale Processing and Architecture for SensorNetworkS
Rice University
Overview
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.
People
The COMPASS project is
based at Rice University and features an interdisciplinary team from
the Departments of Computer Science, Electrical and Computer
Engineering, and Applied Mathematics.
Faculty: Richard G.
Baraniuk, Peter
Druschel, David B. Johnson,
Matthias
Heinkenschloss, T.
S. Eugene Ng
Students:
Santashil PalChaudhuri,
Shriram Sarvotham,
Yanjun Sun,
Ray Wagner
Alumni:
Veronique Delouille,
William Mantzel,
Ramesh Neelamani
Talks
Available internally in Meeting.
Papers
Adaptive Clock Synchronization in Sensor Networks.
(pdf)
Published at IPSN Apr, 2004
A Multiscale Data Representation for Distributed Sensor Networks.
(pdf)
Published at ICASSP Mar, 2005
Non-Asymptotic Performance of Symmetric Slepian-Wolf Coding.
(pdf)
Published at CISS Mar, 2005
A Spatial Domain Decomposition Method for Parabolic Optimal Control Problems.
(pdf)
Published as CAAM TR05-03 May, 2005
Design of Adaptive Overlays for Multi-scale Communication in Sensor Networks.
(pdf)
Published at DCOSS Jun, 2005
Distributed Wavelet Transform for Irregular Sensor Network Grids.
(pdf)
Published at SSP Jul, 2005
Robust Distributed Estimation using the Embedded Subgraphs Algorithm.
(pdf)
Submitted to IEEE Transactions on Signal Processing, Jul, 2005
An Adaptive Scheduling Protocol for Multi-scale Sensor Network Architecture.
(pdf)
Published at DCOSS Jun, 2007
Funding
COMPASS is supported by two grants (NSF CNS-0520280 and NSF CNS-0435425) from the NeTS program of the National Science Foundation and the Rice University ERIT program.
