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Query merging: improving query subscription processing in a multicast environment

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3 Author(s)
A. Crespo ; Dept. of Comput. Sci., Stanford Univ., CA, USA ; O. Buyukkokten ; H. Garcia-Molina

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.

Published in:

IEEE Transactions on Knowledge and Data Engineering  (Volume:15 ,  Issue: 1 )