Una solución de Aprendizaje Reforzado para ubicar fragmentos replicados en Bases de Datos Distribuidas
Abel Rodríguez Morffi1, Darien Rosa Paz1, Marisela Mainegra Hing2 and Luisa Manuela González González1
1Departamento de Ciencia de la Computación,
e–mail: arm@uclv.edu.cu , drosa@uclv.edu.cu , luisagon@uclv.edu.cu
2 Departamento de Matemática Universidad Central "Marta Abreu" de Las Villas, Carretera a Camajuaní km. 5.5, C.P. 54830, Santa Clara, Cuba. Tel: +(53)(42) 281515
e–mail: marisela@uclv.edu.cu
Article received on April 23, 2007; accepted on October 18, 2007
Abstract
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
Keywords: Distributed database design, allocation, replication, reinforcement learning, Q–Learning.
Resumen
Debido a la complejidad del problema de la distribución de los datos, la mayoría de las propuestas de solución presentadas hasta la fecha han coincidido en dividir el proceso de diseño de la distribución en dos fases seriadas: la fragmentación y la ubicación de los fragmentos en los sitios de la red. Este trabajo aborda el problema de ubicación de fragmentos partiendo de un modelo matemático que en su forma general es NP–Completo y propone un método metaheurístico basado en Q–Learning de Aprendizaje Reforzado que minimiza el costo total en un tiempo aceptable. Esta propuesta integra la replicación de fragmentos.
Palabras claves: Diseño de bases de datos distribuidas, ubicación, replicación, aprendizaje reforzado, Q–Learning.
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Acknowledgements
This work is part of a research and development Project "Database Technologies applied to problems", Number 01700031 from the National Program of Information Technology supported by the Cuban Ministry of Science, Technology and Environment. The authors would like to thanks to the Flemish Interuniversity Council (Vlaamse InterUniversitaire Raad) for their support through the IUC VLIR–UCLV Program.
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