Locating data efficiently is a key process in every distributed data storage solution and particularly those deployed in multi-site environments, such as found in Cloud and Fog computing. Nevertheless, the existing protocols dedicated to this task are not compatible with the requirements of the infrastructures that underlie such computing paradigms. In this paper, we initially review three fundamental mechanisms from which the existing protocols are used to locate data. We will demonstrate that these mechanisms all face the same set of limitations and seem to have a trade-off in three distinct domains of interest, namely, i) the scalability, ii) the ability to deal with the network topology changes and iii) the constraints on the data naming process. After laying out our motivation and identifying the related trade-offs in existing systems, we finally propose a conjecture (and provide a proof for this conjecture) stating that these three properties cannot be met simultaneously, which we believe is a new fundamental trade-off the distributed storage systems using the three fundamental mechanisms have to face. We conclude by discussing some of the implications of this novel result.
翻译:高效地分配数据是每一个分布式数据存储解决方案的关键过程,特别是在多地点环境中部署的数据,如云和雾计算中发现的数据。然而,专门用于这项任务的现有协议与这种计算模式所依据的基础设施的要求不相容。我们最初审查的是使用现有协议查找数据的三个基本机制。我们将表明,这些机制都面临一系列相同的限制,似乎在三个不同的利益领域,即(一) 缩放性、(二) 处理网络地形变化的能力和(三) 数据命名程序的限制。在提出我们的动机和查明现有系统中的相关权衡之后,我们最后提出一个假设(并为这一假设提供证据),指出这三个属性不能同时并存,我们认为,这是利用三个基本机制分布式储存系统必须面对的一个新的基本交换。我们通过讨论这一新结果的一些影响来结束我们的讨论。