Candidate Talk: Power-Aware Platform Design for Wireless Sensor Networks

Date

March 20, 2008

Overview

Designing wireless sensor networks that can provide meaningful services in every-day life applications requires the ability to continuously monitor humans and understand what they do over
space and time. However, monitoring humans is a very complex task that might involve a set of heterogeneous sensors ranging from simple motion or RFID sensors to more complex camera sensors.
Typical low-power microprocessors cannot be used to concurrently acquire, process and communicate the information produced from all of these sensing modalities. As a result, a shift from low-power to power-aware sensor node platform design is needed, where the required application processing and communication capabilities must become available at the minimum possible power overhead. In this design paradigm more capable processors or even multiple heterogeneous processors and/or radios might be used. Networked embedded systems with heterogeneous processors and/or radios extend the energy/timing trade-off flexibility and provide the opportunity to fine tune resource utilization. In this talk,
I will present specific power-aware design techniques that can be employed to achieve energy-efficient task scheduling strategies and show how several design bottlenecks and tradeoffs can be exploited to improve the performance and accuracy of these strategies. These design techniques, bottlenecks and tradeoffs will be presented in the context of two different prototype power-aware platforms I have designed and implemented, the XYZ sensor node and the mPlatform architecture.

Speakers

Dimitrios Lymberopoulos

Dimitrios Lymberopoulos is a Ph.D. candidate at the Department of Electrical Engineering at Yale University where he has been working under the supervision of Andreas Savvides since 2003. Before joining Yale, he received his 5-year Diploma from the Computer Engineering and Informatics Department at the University of Patras, Greece in 2003. His core dissertation work focuses on the design and implementation of a low power sensor network architecture for understanding human behaviors over space and time. Other aspects of his work include the design and implementation of power-aware sensor node architectures and the exploration of different sensor physical layers for node localization. In 2006 he was the recipient of a Microsoft Research Fellowship that has been supporting his graduate studies over the last two years.

People

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