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Dynamic Programming with Ant Colony Optimization Metaheuristic for Optimization of Distributed Database Queries
Date
2011-09-28
Author
Dokeroglu, Tansel
Coşar, Ahmet
Metadata
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In this paper, we introduce and evaluate a new query optimization algorithm based on Dynamic Programming (DP) and Ant Colony Optimization (ACO) metaheuristic for distributed database queries. DP algorithm is widely used for relational query optimization, however its memory, and time requirements are very large for the query optimization problem in a distributed database environment which is an NP-hard combinatorial problem. Our aim is to combine the power of DP with heuristic approaches so that we can have a polynomial time approximation algorithm based on a constructive method. DP and ACO algorithms together provide execution plans that are very close to the best performing solutions, and achieve this in polynomial time. This makes our algorithm viable for large multi-way join queries.
Subject Keywords
Query optimization
,
Dynamic programming
,
Ant colony
,
Metaheuristic
URI
https://hdl.handle.net/11511/31205
DOI
https://doi.org/10.1007/978-1-4471-2155-8_13
Conference Name
26th Annual International Symposium on Computer and Information Science
Collections
Graduate School of Natural and Applied Sciences, Conference / Seminar
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T. Dokeroglu and A. Coşar, “Dynamic Programming with Ant Colony Optimization Metaheuristic for Optimization of Distributed Database Queries,” presented at the 26th Annual International Symposium on Computer and Information Science, Royal Soc London, London, ENGLAND, 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/31205.
