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Partial Storage Optimization and Load Control Strategy of Cloud Data Centers

We present a novel approach to solve the cloud storage issues and provide a fast load balancing algorithm. Our approach is based on partitioning and concurrent dual direction download of the files from multiple cloud nodes. Partitions of the files are saved on the cloud rather than the full files, w...

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Detalles Bibliográficos
Autores principales: Al Nuaimi, Klaithem, Mohamed, Nader, Al Nuaimi, Mariam, Al-Jaroodi, Jameela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4417988/
https://www.ncbi.nlm.nih.gov/pubmed/25973444
http://dx.doi.org/10.1155/2015/836561
Descripción
Sumario:We present a novel approach to solve the cloud storage issues and provide a fast load balancing algorithm. Our approach is based on partitioning and concurrent dual direction download of the files from multiple cloud nodes. Partitions of the files are saved on the cloud rather than the full files, which provide a good optimization to the cloud storage usage. Only partial replication is used in this algorithm to ensure the reliability and availability of the data. Our focus is to improve the performance and optimize the storage usage by providing the DaaS on the cloud. This algorithm solves the problem of having to fully replicate large data sets, which uses up a lot of precious space on the cloud nodes. Reducing the space needed will help in reducing the cost of providing such space. Moreover, performance is also increased since multiple cloud servers will collaborate to provide the data to the cloud clients in a faster manner.