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A Learning Automaton Based Approach for Data Fragments Allocation in Distributed Database Systems

Published: 29 June 2010 Publication History

Abstract

Data Fragments Allocation is an important issue in designing Distributed Database System. This problem is NP-complete, and thus requires fast heuristics and random algorithms to generate efficient solutions, so many algorithms for solving that have been reported in the literature. In this paper we used an object migration learning automaton-based algorithm. This approach is able to get suitable solutions in a reasonable amount of time even for moderate sized problems. Experimental results show that proposed algorithm has significant superiority over the several well-known methods.

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  • (2015)A learning automata-based memetic algorithmGenetic Programming and Evolvable Machines10.1007/s10710-015-9241-916:4(399-453)Online publication date: 1-Dec-2015
  • (2011)The Bayesian pursuit algorithmProceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part II10.5555/2025816.2025869(522-531)Online publication date: 28-Jun-2011

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Published In

cover image Guide Proceedings
CIT '10: Proceedings of the 2010 10th IEEE International Conference on Computer and Information Technology
June 2010
3002 pages
ISBN:9780769541082

Publisher

IEEE Computer Society

United States

Publication History

Published: 29 June 2010

Author Tags

  1. Distributed Data fragment allocation
  2. Distributed systems
  3. Object migration learning automaton

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Cited By

View all
  • (2015)A learning automata-based memetic algorithmGenetic Programming and Evolvable Machines10.1007/s10710-015-9241-916:4(399-453)Online publication date: 1-Dec-2015
  • (2011)The Bayesian pursuit algorithmProceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part II10.5555/2025816.2025869(522-531)Online publication date: 28-Jun-2011

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