A RAMCloud Storage System based on HDFS: Architecture, implementation and evaluation

  • Authors:

  • Yifeng Luo;Siqiang Luo;Jihong Guan;Shuigeng Zhou

  • Affiliations:

  • Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China;Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China;Department of Computer Science and Technology, Tongji University, Shanghai, China;Shanghai Key Lab of Intelligent Information Processing, and School of Computer Science, Fudan University, Shanghai, China

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2013

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Abstract

Few cloud storage systems can handle random read accesses efficiently. In this paper, we present a RAMCloud Storage System, RCSS, to enable efficient random read accesses in cloud environments. Based on the Hadoop Distributed File System (HDFS), RCSS integrates the available memory resources in an HDFS cluster to form a cloud storage system, which backs up all data on HDFS-managed disks, and fetches data from disks into memory for handy accesses when files are opened for read or specified by users for memory storage. We extend the storage capacity of RCSS to that of the substrate disk-based HDFS by multiplexing all the available memory resources. Furthermore, RCSS supports MapReduce, which is a popular cloud computing paradigm. By serving data from memory instead of disks, RCSS can yield high random I/O performance with low latency and high throughput, and can achieve good availability and scalability as HDFS.