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Efficient Query Subscription Processing in a Multicast Environment (Extended Abstract)

Crespo, A. and Buyukkokten, O. and Garcia-Molina, H. (2000) Efficient Query Subscription Processing in a Multicast Environment (Extended Abstract). Technical Report. Stanford InfoLab. (Publication Note: 16th International Conference on Data Engineering (ICDE 2000). February 29 - March 3, 2000. San Diego, CA.)

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Abstract

This paper introduces techniques for reducing data dissemination costs of query subscriptions. The reduction is achieved by merging queries with overlapping, but not necessarily equal, answers. The paper formalizes the query-merging problem and introduces a general cost model for it. We prove that the problem is NP-hard and propose exhaustive algorithms and three heuristic algorithms: the Pair Merging Algorithm, the Directed Search Algorithm and the Clustering Algorithm. We develop a simulator for evaluating the different heuristics and show that the performance of our heuristics is close to optimal.

Item Type:Techreport (Technical Report)
Uncontrolled Keywords:Query Processing, Data Dissemination, Query Merging, Query Subscriptions, Multicast of Query Results.
Subjects:Computer Science > Query Processing
Projects:Digital Libraries
Related URLs:Project Homepagehttp://www-diglib.stanford.edu/diglib/pub/
ID Code:434
Deposited By:Import Account
Deposited On:25 Feb 2000 16:00
Last Modified:27 Dec 2008 12:04

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