COllaborative Multiscale Processing and Architecture for SensorNetworkS

Rice University

Overview - What is COMPASS?
People - Who are we?
Talks - Presentation slides
Papers - COMPASS documents
Funding - Who sponsors COMPASS?
Meeting - Presentation Schedule


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.


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.


  • 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.