In addition to the project presentations, there will be a guest lecture by Mark Corner, UMass, on Nov. 27.
Bio: Mark Corner has been an Assistant Professor in the Department of Computer Science at the University of Massachusetts Amherst since 2003. He graduated with his PhD in Electrical Engineering from the University of Michigan. His primary interests lie in the areas of mobile and pervasive computing and networking, file systems, and security. He was the recipient of an NSF CAREER award in 2005, Best Paper awards at FAST 2007 and ACM Multimedia 2005, as well as the Best Student Paper Award at Mobicom 2002. He was also elected to serve on DARPA's Computer Science Study Group panel for 2008. Prof. Corner is the Program Chair of the HotMobile 2008 Workshop and serves on the editorial board of IEEE Pervasive.
Abstract of talk:
Embedded systems can operate perpetually without being connected to a power source by harvesting environmental energy from motion, the sun, wind, or heat differentials. However, programming these perpetual systems is challenging. In response to changing energy levels, programmers can adjust the execution frequency of energy-intensive tasks, or provide higher service levels when energy is plentiful and lower service levels when energy is scarce. However, it is often difficult for programmers to predict the energy consumption resulting from these adjustments. Worse, explicit energy management can tie a program to a particular hardware platform, limiting portability.
In this talk, I will discuss Eon, a programming language and runtime system designed to support the development of perpetual systems. To our knowledge, Eon is the first energy-aware programming language. Eon is a declarative coordination language that lets programmers compose programs from components written in C or nesC. Paths through the program ("flows") may be annotated with different energy states. Eon's automatic energy management then dynamically adapts these states to current and predicted energy levels. It chooses flows to execute and adjusts their rates of execution, maximizing the quality of service under available energy constraints. We demonstrate the utility and portability of Eon by deploying two perpetual applications on widely different hardware platforms: a GPS-based location tracking sensor deployed on a threatened species of turtle and on automobiles.
Title: Sensor networks for environmental monitoring
Course numbers: Duke CPS 296.4 or STA 294 (cross-listed),
UNC Math 891 section 2 and NSCU MA 810C.003 or ST810V.
Time: Tuesday 4:30-7pm
Place: 19 T.W. Alexander Dr. RTP; Room 104, NISS Building.
Coordinating instructor: Carla Ellis
Class List: cps[coursenum]@csDOTdukeDOTedu
This course will cover the entire range of technical issues that must be addressed to effectively use sensor networks to study the environment – from the design of the sensor nodes that will capture the data of interest to the modeling that yields information to the environmental scientists. A running theme will be provided by the sensor network deployment in Duke Forest (including a site visit) and working with the data gathered there. The course will be team-taught by Duke faculty from computer science, engineering, statistics, and ecology as well as various guest lecturers.
There will be a term project requirement.
This is part of a SAMSI Program described at www.samsi.info/programs/2007sensornetprogram.shtml.
Topics will include: