The wireless sensor networks research group at UMass conducts research on a variety of systems, networking and data management issues in data-centric sensor networks. Our focus is on building scalable, energy-efficient sensor networks through the use of heterogeneous sensor modalities, sensor platforms and processors. Our projects are diverse and span core systems building blocks, data and network management tools and services, mathematical principles, and application of sensor networks to scientific, industrial and health-care disciplines.

Deepak Ganesan
Prashant Shenoy
Mark Corner


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STONES: STOrage for Networked Embedded Sensors This project is aimed at developing an ultra-low power storage sub-system for sensor devices. As part of the first phase, the ESSense sub-project performed a measurement study of storage devices relevant to the sensor domain in order to find the most energy-efficient device. In the second part of the STONES project, we developed an object storage system for sensor nodes, Capsule. > ESSense (Energy-efficient Storage for Sensors) website > Capsule Object Store website

PRESTO: A Predictive Storage Architecture for Sensor Networks PRESTO is a hierarchical storage architecture for emerging large-scale, hierarchical sensor networks. In contrast to existing techniques, PRESTO is a proxy-centric architecture, where tethered proxies balance the need for interactive querying from users with the energy optimization needs of the remote sensors. > Presto website

SensEye: A Multi-tier Multi-modal Camera Sensor Network Recent technology trends have resulted in a broad spectrum of camera sensors, wireless radio technologies, and embedded sensor platforms. SensEye is designed on the principle that multi-tier networks are not only scalable, they offer a number of advantages over simpler, single-tier unimodal networks: lower cost, better coverage, higher functionality, and better reliability. > SensEye website

HPM: Hierarchical Power Management for Sensor Clusterheads
In this project, we are applying hierarchical power management techniques developed for mobile computing platforms to the design of a sensor clusterhead. The key innovation is the intelligent use of multiple processors on sensor clusterheads to deal with widely varying sensor application workloads.
>HPM website

Fall 2006: CS691AA: Wireless Sensor Networks
Also taught in 2005, 2004.

Spring 2005: CS791T - Mathematical Techniques in Sensor Data Processing

Fall 2003: CS791L - Sensor Networks