[Colloquium] Talk by Nesime Tatbul on Monday, May 8, 2006

[Margery Ishmael]

DEPARTMENT OF COMPUTER SCIENCE - TALK

Date: Monday, May 8, 2006
Time: 2:30 p.m.
Place: Ryerson 251

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Speaker:  NESIME TATBUL

From:  Brown University

Url:  http://www.cs.brown.edu/~tatbul/

Title:  Load Shedding Techniques for Data Stream Management Systems

Abstract:

In recent years, we have witnessed the emergence of a new class of  
applications
that must deal with large volumes of streaming data. Examples include  
financial
data analysis on feeds of stock tickers, sensor-based environmental  
monitoring,
and network traffic monitoring. Traditional database management  
systems (DBMS)
which are very good at managing large volumes of stored data, fall  
short in
serving this new class of applications, which require low-latency  
processing
on live data from push-based sources. Aurora is a data stream management
system (DSMS) that has been developed to meet these needs.

A DSMS such as Aurora may be subject to higher input rates than its  
resources
can handle. When input rates exceed system capacity, the system will  
become
overloaded and Quality of Service (QoS) at system outputs will fall  
below
acceptable levels. Under these conditions, the system will shed load by
selectively dropping tuples, thus degrading the answer, in order to  
improve
the observed latency of the results. In this talk, I will present a  
load shedding
framework for data stream management systems which handles the
overload problem in a light-weight manner, while minimizing the loss
in result accuracy and guaranteeing subset results at query outputs.

One of the triggering factors behind the data stream processing research
has been the rapid development in sensor-based technologies and  
applications.
In my talk, I will also briefly describe a real sensor network  
application.
I will show that significant resource efficiency can be achieved through
other forms of load management on streaming sensor data.

Bio:

Nesime Tatbul is a Ph.D. candidate in Computer Science at Brown  
University.
Her research interests are in database systems, with a current focus  
on stream
and sensor data management. She received her B.S. and M.S degrees in  
Computer
Engineering from the Middle East Technical University in Turkey, and  
she holds
an M.S. degree in Computer Science from Brown University.
During her graduate years at Brown, she also worked as a research  
intern at the
IBM Almaden Research Center, and as a consultant for the U.S. Army  
Research
Institute of Environmental Medicine.

***The talk will be followed by refreshments in Ryerson 255***

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Host:  Svetlozar Nestorov

People in need of assistance should call 773-834-8977 in advance.

For information on future CS talks: http://www.cs.uchicago.edu/events





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