|
|
|
 |
Mor Harchol-Balter
Carnegie Mellon University
Friday, Sep. 16, 11:00am
LC 102, Brooklyn Campus, Polytechnic University
Abstract
In the first half of the talk, we focus on Web servers serving static
(GET file) requests. Here we ask the following question: "Is it
possible to reduce the expected response time of every request at a
Web server, simply by changing the order in which we schedule the
requests?" We present research results, including both queueing
theoretic and kernel-level implementation results, showing that the
answer is yes. This work appeared in [SIGMETRICS 01, 03] and
[Transactions on Computer Systems 03] and was extended to transient
overload scenarios in [ITC 03] and [Transactions on Internet
Technologies 06].
In the second half of the talk, we consider e-commerce Web sites, where
the backend database becomes the bottleneck. Our goal here is to
build a mechanism which allows the web vendors to prioritize in favor
of clients who are "big spenders," offering them lower delays. We
describe both QoS mechanisms "internal" to the database, at the lock
queue modules, and mechanisms "external" to the database. This work
appeared in [ICDE 04] and [ICDE 05].
Joint work with (my students) Bianca Schroeder, David McWherter, and Adam
Wierman.
Bio
Mor Harchol-Balter is an Associate Professor of Computer Science at
Carnegie Mellon University. She received her doctorate from the
Computer Science department at the University of California at
Berkeley under the direction of Manuel Blum. She is a recipient of the
McCandless Chair, the NSF CAREER award, the NSF Postdoctoral
Fellowship in the Mathematical Sciences, multiple best paper awards,
and several teaching awards, including the Herbert A. Simon Award for
Teaching Excellence.
Professor Harchol-Balter is heavily involved in the ACM SIGMETRICS
research community. Her work focuses on designing new
scheduling/resource allocation policies for various distributed
computer systems including Web servers, distributed supercomputing
servers, networks of workstations, and database systems. Her work
spans both queueing analysis and implementation and emphasizes
integrating measured workload distributions into the problem solution.
For further information please contact Torsten Suel (suel at poly.edu)