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Data Storage Management in Cloud Environments: Taxonomy, Survey, and Future Directions

机译:云环境中的数据存储管理:分类,调查和未来方向

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Storage as a Service (StaaS) is a vital component of cloud computing by offering the vision of a virtually infinite pool of storage resources. It supports a variety of cloud-based data store classes in terms of availability, scalability, ACID (Atomicity, Consistency, Isolation, Durability) properties, data models, and price options. Application providers deploy these storage classes across different cloud-based data stores not only to tackle the challenges arising from reliance on a single cloud-based data store but also to obtain higher availability, lower response time, and more cost efficiency. Hence, in this article, we first discuss the key advantages and challenges of data-intensive applications deployed within and across cloud-based data stores. Then, we provide a comprehensive taxonomy that covers key aspects of cloud-based data store: data model, data dispersion, data consistency, data transaction service, and data management cost. Finally, we map various cloud-based data stores projects to our proposed taxonomy to validate the taxonomy and identify areas for future research.
机译:通过提供虚拟的无限存储资源池的愿景,存储即服务(StaaS)是云计算的重要组成部分。它在可用性,可伸缩性,ACID(原子性,一致性,隔离性,耐久性)属性,数据模型和价格选项方面支持各种基于云的数据存储类。应用程序提供商在不同的基于云的数据存储区中部署这些存储类,不仅可以解决由于依赖单个基于云的数据存储区而带来的挑战,而且还可以获得更高的可用性,更短的响应时间以及更高的成本效率。因此,在本文中,我们首先讨论在基于云的数据存储中和跨云数据存储部署的数据密集型应用程序的主要优势和挑战。然后,我们提供全面的分类法,涵盖基于云的数据存储的关键方面:数据模型,数据分散性,数据一致性,数据事务服务和数据管理成本。最后,我们将各种基于云的数据存储项目映射到我们建议的分类法中,以验证分类法并确定将来的研究领域。

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