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

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.