By Topic

RTSTREAM: real-time query processing for data streams

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Yuan Wei ; Dept. of Comput. Sci., Virginia Univ., Charlottesville, VA ; Son, S.H. ; Stankovic, J.A.

Many real-time applications, such as traffic control systems, surveillance systems and health monitoring systems, need to operate on continuous unbounded streams of data. These applications also have inherent real-time performance requirements that have to be met under high-volume, time-varying incoming data streams. In this paper, we present a real-time data stream query model named PQuery, which provides periodic real-time queries on data streams for the aforementioned real-time applications. To support the PQuery model, a real-time data stream management prototype system named RTSTREAM is developed to provide deadline miss ratio guarantees for periodic queries over continuous and unbounded data streams. We describe the periodic query semantics and discuss why the periodic query model is appropriate for real-time applications. To handle irregular data arrival patterns and query workloads, we propose data admission as an overload protection mechanism. We conduct performance studies with synthetic workloads as well as real workloads from network traffic monitoring applications. The experimental results show that the proposed periodic query model suits the need of the real-time applications and the data admission overload protection approach is effective in managing the workload fluctuations

Published in:

Object and Component-Oriented Real-Time Distributed Computing, 2006. ISORC 2006. Ninth IEEE International Symposium on

Date of Conference:

24-26 April 2006