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Adaptive Filters for Continuous Queries over Distributed Data Streams

Olston, Chris and Jiang, Jing and Widom, Jennifer (2002) Adaptive Filters for Continuous Queries over Distributed Data Streams. Technical Report. Stanford InfoLab.

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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.

Item Type:Techreport (Technical Report)
Additional Information:This paper supplants a previous February 2002 technical report by Olston and Widom entitled "Approximate Caching for Continuous Queries over Distributed Data Sources."
Uncontrolled Keywords:adaptive filters, distributed data streams, approximate answers
Subjects:Computer Science > Distributed Systems
Related URLs:Project Homepage
ID Code:744
Deposited By:Import Account
Deposited On:14 Nov 2002 16:00
Last Modified:25 Dec 2008 09:57

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