DocumentCode :
585836
Title :
Particle Swarm Intelligence as a new heuristic for the optimization of distributed database queries
Author :
Dokeroglu, Tansel ; Tosun, Umut ; Cosar, Ahmet
Author_Institution :
Dept. of Comput. Eng., Middle East Tech. Univ., Ankara, Turkey
fYear :
2012
fDate :
17-19 Oct. 2012
Firstpage :
1
Lastpage :
7
Abstract :
Particle Swarm Optimization (PSO) is a member of the nature inspired algorithms. Its ability to solve many complex search problems efficiently and accurately has made it an interesting research area. In this study, we model Distributed Database Query Optimization problem as a Bare Bones PSO and develop a set of canonical and hybrid PSO algorithms. To the best of our knowledge, this is the first time that Bare Bones PSO is being used for solving this problem. We explore and evaluate the capabilities of PSO against Iterative Dynamic Programming, and a Genetic Algorithm. We experimentally show that PSO algorithms are able to find near-optimal solutions efficiently.
Keywords :
distributed databases; dynamic programming; genetic algorithms; particle swarm optimisation; search problems; Bare Bones PSO; DDB; canonical PSO algorithms; complex search problems; distributed database query optimization; genetic algorithm; hybrid PSO algorithms; iterative dynamic programming; nature inspired algorithms; near-optimal solutions; particle swarm intelligence; particle swarm optimization; Approximation algorithms; Heuristic algorithms; Mathematical model; Query processing; Sociology; Statistics; Topology; Bare Bones; Distributed database; Particle swarm intelligence; Query optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Application of Information and Communication Technologies (AICT), 2012 6th International Conference on
Conference_Location :
Tbilisi
Print_ISBN :
978-1-4673-1739-9
Type :
conf
DOI :
10.1109/ICAICT.2012.6398467
Filename :
6398467
Link To Document :
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