地理分布数据市场中的联合数据购买和数据放置
Joint Data Purchasing and Data Placement in a Geo-Distributed Data Market
摘要：
本文研究了地理分布的云数据市场所面临的两个设计任务：购买哪些数据（数据购买）和在哪里放置/复制数据交付（数据放置）。我们表明，在云数据市场的数据购买和数据放置的联合问题可以被视为一个设施的位置问题，因此是NP难的。然而，我们给出了一个可证明的最佳算法的情况下，由一个单一的数据中心组成的数据市场，然后概括的结构，从单一的数据中心设置，以开发一个接近最佳的，多项式时间算法的地理分布的数据市场。由此产生的设计，基准，分解成两个子问题，一个数据采购和数据放置，使用底层带宽成本的转换的联合采购和放置问题。我们表明，通过案例研究，基准是接近最佳的（在1.6%）在实际环境中。
英文摘要：
This paper studies two design tasks faced by a geo-distributed cloud data market: which data to purchase (data purchasing) and where to place/replicate the data for delivery (data placement). We show that the joint problem of data purchasing and data placement within a cloud data market can be viewed as a facility location problem, and is thus NP-hard. However, we give a provably optimal algorithm for the case of a data market made up of a single data center, and then generalize the structure from the single data center setting in order to develop a near-optimal, polynomial-time algorithm for a geo-distributed data market. The resulting design, Datum, decomposes the joint purchasing and placement problem into two subproblems, one for data purchasing and one for data placement, using a transformation of the underlying bandwidth costs. We show, via a case study, that Datum is near-optimal (within 1.6%) in practical settings.
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