Tracking Energy in Networked Embedded Systems
Speaker: Prabal Dutta , UC-Berkeley
Date: December 5 2008
Time: 11:00AM to 12:00PM
Location: Star Seminar Room (32-D463)
Host: Sam Madden, CSAIL
Contact: Sheila Marian, 617-253-1996, sheila@csail.mit.edu
Relevant URL: http://www.cs.berkeley.edu/~prabalABSTRACT
Energy is a critical resource in many wireless embedded systems but
profiling energy usage in resource-constrained systems, like sensor
networks, has proven challenging. Answering even basic questions
about energy usage is difficult. For example, how much energy do
individual operations, such as sampling sensors, receiving packets, or
using the CPU cost? What is the energy breakdown of a node, in terms
of logical activity, hardware subsystem, or time? Network-wide, how
much energy do distributed services such as routing, time
synchronization, and localization consume?
In this talk, I will outline three technical challenges to energy
profiling -- measuring energy consumption (metering), breaking down
aggregate usage by power domain (slicing), and grouping causally
connected actions within nodes and across the network (tracking) --
and present iCount and Quanto, our solutions to these problems.
iCount is new energy meter design that measures energy usage by
counting the cycles of a switching regulator and offers high-speed,
high-resolution, and low-overhead snapshots of system-wide energy
usage. Quanto builds on iCount, and combines well-defined interfaces
for hardware power state visibility, regression for per-hardware
subsystem energy breakdown, and programmer-defined causal activity
tracking using labels, to map how energy and time are spent on nodes
and across a network.
Using iCount and Quanto, we have been able to precisely quantify the
effects of low-level system implementation decisions, such as using
DMA versus direct bus operations, or the effect of external radio
interference on the power draw of a low duty cycle radio. While these
initial results are promising, some challenges remain: compressing the
large volume of profile data, visualizing the profile data more
effectively, applying the lessons to larger scale systems, and making
the hardware and software more accessible.
BIO
Prabal Dutta is a Ph.D. candidate in the Computer Science Division at
the University of California, Berkeley, where he is advised by David
Culler and Scott Shenker. His research interests straddle the
hardware/software interface and include systems, networking, and
architecture with a recent focus on low-power, wireless embedded
systems. His research has enabled some of the largest sensor networks
deployed to date including the 1,000+ node ExScal project and the 557
node DARPA NEST Final Experiment. His work has been commercialized by
Aginova, Arch Rock, Crossbow, and Moteiv, three of which are venture
financed UC Berkeley spinoffs. His research is funded in part by an
NSF Graduate Research Fellowship and a Microsoft Research Fellowship.
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