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Orchestration of Distributed Storage Targets through Storage Flows

机译:通过存储流量的分布式存储目标编排

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Distributed data storage is a topic of growing importance due to the mounting pressure to find the right balance between capacity, cost, privacy and other non-functional properties. Compared to central storage on physical media, on the network or in a cloud storage service, advanced data distribution techniques offer additional safety, security and performance. On the downside, these advantages come with a much higher complexity regarding the choice and configuration of where to store which parts of the data, and subsequent verification of where which data had been stored. Often, the storage targets must be configured individually while a centrally and locally accessible configuration interface with an appropriate propagation and verification mechanism would be more suitable. The complexity is further increased by additional data pre-processing tasks which are selectively applied to some of the targets. Compression, encryption and deduplication are typically present in pre-processing. With Storage Flows, we propose a new concept to manage distributed storage flows through systematic orchestration. The flows connect clients flexibly with intermediate data pre-processing tasks and finally the storage targets. We show that Storage Flows can be formalised and demonstrate their practical usefulness with implemented configuration and verification tools.
机译:分布式数据存储是由于安装压力,以找到能力,成本,隐私和其他非功能性质之间的正确平衡,这是一个越来越重要的主题。与物理媒体上的中央存储相比,在网络或云存储服务中,高级数据分配技术提供额外的安全性,安全性和性能。在缺点方面,这些优点具有更高的复杂性,关于存储哪些部分的选择和配置以及随后验证已经存储了数据的位置。通常,必须单独配置存储目标,而具有适当传播和验证机制的集中和本地可访问的配置界面将更合适。通过额外的数据预处理任务进一步增加了复杂性,这些任务是选择性地应用于一些目标。压缩,加密和重复数据删除通常在预处理中存在。使用存储流,我们提出了一种新的概念来通过系统编排来管理分布式存储流。流程可灵活地连接客户端,使用中间数据预处理任务,最后存储目标。我们表明,存储流可以正式化并展示其具有所实现的配置和验证工具的实际用途。

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