DocumentCode :
3784680
Title :
Query merging: improving query subscription processing in a multicast environment
Author :
A. Crespo;O. Buyukkokten;H. Garcia-Molina
Author_Institution :
Dept. of Comput. Sci., Stanford Univ., CA, USA
Volume :
15
Issue :
1
fYear :
2003
Firstpage :
174
Lastpage :
191
Abstract :
This paper introduces techniques for reducing data dissemination costs of query subscriptions in a multicast environment. 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 framework and cost model for evaluating merging. 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, which uses geographical queries as a representative example for evaluating the different heuristics and show that the performance of our heuristics is close to optimal.
Keywords :
"Merging","Subscriptions","Multicast algorithms","Clustering algorithms","Telecommunication traffic","Costs","Heuristic algorithms","Internet","Network servers","Feeds"
Journal_Title :
IEEE Transactions on Knowledge and Data Engineering
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/TKDE.2003.1161589
Filename :
1161589
Link To Document :
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