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OCEDS: Optimal Cost-Effective Data Storage in Cloud Data Centers

机译:OCEDS:云数据中心中最佳成本高效的数据存储

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摘要

Many organizations require handling a massive quantity of data. The rapid growth of data in size leads to the demand for a new large space for storage. It is impossible to store bulk data individually. The data growth issues compel organizations to search novel cost-efficient ways of storage. In cloud computing, reducing an execution cost and reducing a storage price are two of several problems. This work proposed an optimal cost-effective data storage (OCEDS) algorithm in cloud data centres to deal with this problem. Storing the entire database in the cloud on the cloud client is not the best approach. It raises processing costs on both the customer and the cloud service provider. Execution and storage cost optimization is achieved through the proposed OCEDS algorithm. Cloud CSPs present their clients profit-maximizing services while clients want to reduce their expenses. The previous works concentrated on only one side of cost optimization (CSP point of view or consumer point of view), but this OCEDS reduces execution and storage costs on both sides.
机译:许多组织需要处理大量数据。数据的快速增长尺寸导致对新型存储空间的需求。不可能单独存储批量数据。数据增长问题强迫组织以搜索新颖的成本效益的存储方式。在云计算中,降低执行成本并降低存储价格是几个问题的两个问题。这项工作提出了云数据中心的最佳成本效益数据存储(OCEDS)算法来处理此问题。将整个数据库存储在云客户端上的云中不是最好的方法。它提高了客户和云服务提供商的处理成本。通过所提出的OCEDS算法实现执行和存储成本优化。 Cloud CSP呈现他们的客户利润最大化服务,而客户则希望减少其费用。以前的作品仅集中于成本优化的一侧(CSP观点或消费者观点),但这一原因可以减少两侧的执行和储存成本。

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