[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.1109/JCN.2014.000073

Distributed Database Design using Evolutionary Algorithms

Tosun, Umut (Department of Computer Engineering, Baskent University)

Publication Information

Journal of Communications and Networks / v.16, no.4, 2014 , pp. 430-435 More about this Journal

Abstract

The performance of a distributed database system depends particularly on the site-allocation of the fragments. Queries access different fragments among the sites, and an originating site exists for each query. A data allocation algorithm should distribute the fragments to minimize the transfer and settlement costs of executing the query plans. The primary cost for a data allocation algorithm is the cost of the data transmission across the network. The data allocation problem in a distributed database is NP-complete, and scalable evolutionary algorithms were developed to minimize the execution costs of the query plans. In this paper, quadratic assignment problem heuristics were designed and implemented for the data allocation problem. The proposed algorithms find near-optimal solutions for the data allocation problem. In addition to the fast ant colony, robust tabu search, and genetic algorithm solutions to this problem, we propose a fast and scalable hybrid genetic multi-start tabu search algorithm that outperforms the other well-known heuristics in terms of execution time and solution quality.

Keywords

Ant colony optimization; distributed database design; hybrid algorithms; robust tabu search;

Citations & Related Records

Reference

1	M. T. Ozsu and P. Valduriez, Principles of Distributed Database Systems, Springer Publishing Company, 2011.
2	Z.-J. Lee, S.-F. Su, C.-Y. Lee, and Y.-S. Hung, "A heuristic genetic algorithm for solving resource allocation problems," Knowledge and Information Systems, vol. 5, no. 4, pp. 503-511, 2003. DOI
3	T. C. Koopmans and M. Beckmann, "Assignment problems and the location of economics activities," Econometrica, vol. 25, no. 1, pp. 53-76, 1957. DOI
4	X. Gu, W. Lin, and B. Veeravalli, "Practically realizable efficient data allocation and replication strategies for distributed databases with buffer constraints," IEEE Trans. Parallel Distrib. Syst., vol. 17, no. 9, pp. 1001-1013, 2006. DOI
5	S. Ceri and G. Pelagatti, Distributed Databases Principles and Systems, McGraw-Hill, NY: Springer, 1984.
6	I. Ahmad and K. Karlapalem, "Evolutionary algorithms for allocating data in distributed database systems," Distributed and Parallel Databases, vol. 11, no. 1, pp. 5-32, 2002. DOI
7	R. K. Adl and S.M. T. R. Rankoohi, "A new ant colony optimization based algorithm for data allocation problem in distributed databases," Knowledge and Information Systems, vol. 21, no. 3, pp. 349-373, 2009.
8	O. Frieder, H. T. Siegelmann, "Multiprocessor document allocation: A genetic algorithm approach," IEEE Trans. Knowl. Data Eng., vol. 9, no. 4, pp. 640-642, 1997. DOI
9	D. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, MA: Addison-Wesley, 1989.
10	U. Tosun, T. Dokeroglu, and A. Cosar, "A new robust island parallel genetic algorithm for the quadratic assignment problem," International J. Production Research, vol. 51, no. 14., pp. 4117-4133, 2013. DOI
11	A. E. Eiben and J. E. Smith, Introduction to Evolutionary Computing, Springer, 2003.
12	M. Dorigo, V. Maniezzo, and A. Colorni, "Ant system: Optimization by a colony of cooperating Agents," IEEE Trans. Syst., Man, Cybern., Part B, vol. 26, no. 1, pp. 29-41, 1996. DOI
13	E. D. Taillard, L. M. Gambardella, M. Gendreau, and J. Y. Potvin, "Adaptive memory programming: A unifed iew of meta-heuristics," European J. Operational Research, vol. 135, no. 1, pp. 1-16, 2001. DOI
14	E. Taillard, "Robust taboo search for the quadratic assignment problem," Parallel Computing, vol. 17, no. 4-5, pp. 443-455, 1991. DOI
15	T. James, C. Rego, and F. Glover, "Multi-start tabu search and diversification strategies for the quadratic assignment problem," IEEE Trans. Syst., Man, and Cybern., Part A, vol. 39, no. 3, pp. 579-596, 2009. DOI
16	T. James, C. Rego, and F. Glover, "A cooperative parallel tabu search algorithm for the QAP," European J. Operational Research, vol. 195, no. 3, pp. 810-826, 2009. DOI