By Topic

Supporting sliding window queries for continuous 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)
Qiao, L. ; Dept. of Comput. Sci., California Univ., Santa Barbara, CA, USA ; Agrawal, D. ; El Abbadi, A.

Although traditional databases and data warehouses have been exploited widely to manage persistent data, a large number of applications from sensor network need functional supports for transient data in the continuous data stream. One of the crucial functions is to summarize the data items within a sliding window. A sliding window contains a fixed width span of data elements. The data items are implicitly deleted from the sliding window, when it moves out of the window scope. Several one-dimensional histograms have been proposed to store the succinct time information in a sliding window. Such histograms, however, only handle the data items with attribute values in unary domains. In this paper, we explore the problem of extending the value to a multi-valued domain. A two-dimensional histogram, the hybrid histogram, is proposed to support sliding window queries on a practical multi-valued domain. The basic building block of the hybrid histogram is the exponential histogram. The hybrid histogram is maintained to capture the changes of data distribution. To further compress the exponential histograms, we propose a condensed exponential histogram without losing the error bound. Results of an extensive experimental study are included to evaluate the benefits of the proposed technique.

Published in:

Scientific and Statistical Database Management, 2003. 15th International Conference on

Date of Conference:

9-11 July 2003