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Computación y Sistemas
versión On-line ISSN 2007-9737versión impresa ISSN 1405-5546
Resumen
RODRIGUEZ MORFFI, Abel; ROSA PAZ, Darien; MAINEGRA HING, Marisela y GONZALEZ GONZALEZ, Luisa Manuela. A Reinforcement Learning Solution for Allocating Replicated Fragments in a Distributed Database. Comp. y Sist. [online]. 2007, vol.11, n.2, pp.117-128. ISSN 2007-9737.
Due to the complexity of the data distribution problem in Distributed Database Systems, most of the proposed solutions divide the design process into two parts: the fragmentation and the allocation of fragments to the locations in the network. Here we consider the allocation problem with the possibility to replicate fragments, minimizing the total cost, which is in general NP-complete, and propose a method based on Q-learning to solve the allocation of fragments in the design of a distributed database. As a result we obtain for several cases, logical allocation of fragments in a practical time
Palabras llave : Distributed database design; allocation; replication; reinforcement learning; Q-Learning.