E2FS: an elastic storage system for cloud computing

Longbin Chen, Meikang Qiu, Jeungeun Song, Zenggang Xiong, Houcine Hassan

Abstract: In cloud storage, replication technologies are essential to fault tolerance and high availability of data. While achieving the goal of high availability, replication brings extra number of active servers to the storage system. Extra active servers mean extra power consumption and capital expenditure. Furthermore, the lack of classification of data makes replication scheme fixed at the very beginning. This paper proposes an elastic and efficient file storage called E2FS for big data applications. E2FS can dynamically scale in/out the storage system based on real-time demands of big data applications. We adopt a novel replication scheme based on data blocks, which provides a fine-grained maintenance of the data in the storage system. E2FS analyzes features of data and makes dynamic replication decision to balance the cost and performance of cloud storage. To evaluate the performance of proposed work, we implement a prototype of E2FS and compare it with HDFS. Our experiments show E2FS can outperform HDFS in elasticity while achieving guaranteed performance for big data applications.