Multi-Query Optimization in Distributed Databases Using an Ants Colony-Based Algorithm

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Abazari Torghabeh, Reza | 2014

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 46634 (19)
University: Sharif University of Technology
Department: Computer Engineering
Advisor(s): Mirian Hosseinabadi, Hassan
Abstract:
One important problem in query optimization in centralized and decentralized databases is optimizing queries containing common sub-expressions, known as multi-query optimization. In processing these queries, the goal is to process a group of queries together and find a global execution plan with minimum cost for the query set. In most of researches which have approached this problem the focus were on exhaustive algorithms. Since size of the problem space for these algorithms grows exponential with query set size, these approaches are impractical. In this research we have presented six algorithms based on Ant Colony Optimization metaheuristic. We have compared the efficiency of these methods with A* algorithm which is able to find the optimum solution of the problem. The results of our experiments show that ACO-based algorithms produce solutions with 98% efficiency for small query sets with 11 queries in a very shorter time in comparison with A-Star. Furthermore, these algorithms are scalable and can produce solutions for larger query sets with up to 200 queries in a reasonable time (about 300 seconds)
Keywords:
Ant Colony Optimization (ACO) ; A Star Search Method ; Distirbuted Databases ; Multi Query Optimization