Campus Event Calendar
Event Entry
What and Who
"Cutting the Electrical Bill for Internet-Scale Systems"
Bruce Maggs
Duke University
SWS Colloquium
Bruce Maggs received the S.B., S.M., and Ph.D. degrees in computer
science from the Massachusetts Institute of Technology in 1985, 1986,
and 1989, respectively. His advisor was Charles Leiserson. After
spending one year as a Postdoctoral Associate at MIT, he worked as a
Research Scientist at NEC Research Institute in Princeton from 1990 to
1993. In 1994, he moved to Carnegie Mellon, where he stayed until
joining Duke University in 2009 as a Professor in the Department of
Computer Science. While on a two-year leave-of-absence from Carnegie
Mellon, Maggs helped to launch Akamai Technologies, serving as its
Vice President for Research and Development, before returning to
Carnegie Mellon. He retains a part-time role at Akamai as Vice
President for Research.
Maggs's research focuses on networks for parallel and distributed
computing systems. In 1986, he became the first winner (with Charles
Leiserson) of the Daniel L. Slotnick Award for Most Original Paper at
the International Conference on Parallel Processing, and in 1994 he
received an NSF National Young Investigator Award. He was co-chair of
the 1993-1994 DIMACS Special Year on Massively Parallel Computation
and has served on the steering committees for the ACM Symposium on
Parallel Algorithms and Architectures (SPAA) and ACM Internet
Measurement Conference (IMC), and on the program committees of
numerous ACM conferences including STOC, SODA, PODC, and SIGCOMM.
AG 1, SWS, RG1
Expert Audience
English
Note: We use this to send email in the morning.
Date, Time and Location
Friday, 18 September 2009
11:00
60 Minutes
E1 5
5th floor
Saarbrücken
Abstract
This talk shows how operators of Internet-scale distributed systems,
such as Google, Microsoft, and Akamai can reduce electricity costs
(but not necessarily energy consumption) by dynamically allocating
work among data centers in response to fluctuating energy prices.
The approach applies to systems consisting of fully replicated
clusters of servers installed in diverse geographical locations
where energy can be purchased through spot markets. Using
historical energy prices for major energy markets in the United
States, as well as usage data from Akamai's content delivery
network, we should how much can be saved now, and what might be
saved in the future given server technology trends.
Joint work with Asfandyar Quershi, Rick Weber, Hari Balakrishnan,
and John Guttag.
Contact
Brigitta Hansen
0681 - 9325691
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Brigitta Hansen, 09/16/2009 13:03
Brigitta Hansen, 09/14/2009 14:39 -- Created document.
Brigitta Hansen, 09/14/2009 14:39 -- Created document.