A Data Placement Strategy for Data-Intensive Cloud Storage

Abstract

Data-Intensive applications in power systems often perform complex computations which always involve large amount of datasets. In a distributed environment, an application may needs several datasets located in different data centers which faces two challenges including the high cost of data movements between data centers and data dependencies within the same data centers. In this paper, a data placement strategy among and within data centers in a cloud environment is proposed. Datasets are placed in different centers by a clustering scheme based on the data dependencies. And within the center, data is partitioned and replicated using consistent hashing. Simulations show that the algorithm can effectively reduce the cost of data movements and perform a evenly data distribution.