Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
6-2003
Abstract
We consider an environment where distributed data sources continuously stream updates to a centralized processor that monitors continuous queries over the distributed data. Significant communication overhead is incurred in the presence of rapid update streams, and we propose a new technique for reducing the overhead. Users register continuous queries with precision requirements at the central stream processor, which installs filters at remote data sources. The filters adapt to changing conditions to minimize stream rates while guaranteeing that all continuous queries still receive the updates necessary to provide answers of adequate precision at all times. Our approach enables applications to trade precision for communication overhead at a fine granularity by individually adjusting the precision constraints of continuous queries over streams in a multi-query workload. Through experiments performed on synthetic data simulations and a real network monitoring implementation, we demonstrate the effectiveness of our approach in achieving low communication overhead compared with alternate approaches.
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Publication
SIGMOD '03 Proceedings of the 2003 ACM SIGMOD international conference on Management of data
First Page
563
Last Page
574
ISBN
9781581136340
Identifier
10.1145/872757.872825
Publisher
ACM
City or Country
San Diego, CA, USA
Citation
OLSTON, Chris; JIANG, Jing; and Widom, Jennifer.
Adaptive Filters for Continuous Queries over Distributed Data Stream. (2003). SIGMOD '03 Proceedings of the 2003 ACM SIGMOD international conference on Management of data. 563-574.
Available at: https://ink.library.smu.edu.sg/sis_research/1258
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://dx.doi.org/10.1145/872757.872825
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons