A Reinforcement Learning Solution for Allocating Replicated Fragments in a Distributed Database
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Redalyc
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| Natura: | Artículo científico |
| Lingua: | en |
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Instituto Politécnico Nacional
2007
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| _version_ | 1876423886907637760 |
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| author | Abel Rodríguez Morff |
| author_facet | Abel Rodríguez Morff |
| contents | A Reinforcement Learning Solution for Allocating Replicated Fragments in a Distributed Database Abel Rodríguez Morff Darien Rosa Paz Luisa Manuela González González Marisela Mainegra Hing Computación Learning allocation replication reinforcement learning Distributed database design 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. 2007 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61511203 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.2 Vol.11 |
| format | Artículo científico |
| id | redalyc_61511203 |
| institution | Redalyc |
| language | en |
| publishDate | 2007 |
| publisher | Instituto Politécnico Nacional |
| spellingShingle | A Reinforcement Learning Solution for Allocating Replicated Fragments in a Distributed Database Abel Rodríguez Morff Computación Learning allocation replication reinforcement learning Distributed database design A Reinforcement Learning Solution for Allocating Replicated Fragments in a Distributed Database Abel Rodríguez Morff Darien Rosa Paz Luisa Manuela González González Marisela Mainegra Hing Computación Learning allocation replication reinforcement learning Distributed database design 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. 2007 artículo científico 1405-5546 https://www.redalyc.org/articulo.oa?id=61511203 en http://www.redalyc.org/revista.oa?id=615 Computación y Sistemas application/pdf Instituto Politécnico Nacional Computación y Sistemas (México) Num.2 Vol.11 |
| title | A Reinforcement Learning Solution for Allocating Replicated Fragments in a Distributed Database |
| topic | Computación Learning allocation replication reinforcement learning Distributed database design |
| url | https://www.redalyc.org/articulo.oa?id=61511203 |