• DocumentCode
    576914
  • Title

    Sedna: A Memory Based Key-Value Storage System for Realtime Processing in Cloud

  • Author

    Dai, Dong ; Li, Xi ; Wang, Chao ; Sun, Mingming ; Zhou, Xuehai

  • Author_Institution
    Comput. Sci. Coll., Univ. of Sci. & Technol. of China, Hefei, China
  • fYear
    2012
  • fDate
    24-28 Sept. 2012
  • Firstpage
    48
  • Lastpage
    56
  • Abstract
    Comparing with the traditional disk based distributed storage system, RAM based storage has been proven to be an effective way to accelerate real time applications processing speed. In this paper, we propose a memory based distributed Cloud storage system called Sedna. Managing ´big data´ across lots of commodity servers, Sedna provides high scalability, simple effective data access APIs with data consistency and persistency, and a new trigger based APIs for real time applications. To guarantee the scalability with low latency, we design and implement a hierarchical structure to manage huge size data center which is simple and effective. Except the high speed provided by memory based storage, Sedna absorbs advantages from state-of-art cloud programming frameworks, and gives programmers a new way to write massive data real time applications. These data read/write triggers APIs are necessary but are missing parts of modern distributed storage system. Experiments and examples show Sedna achieve comparable speed to widely-used distributed cache system, and provide a more efficient way to use distributed storage.
  • Keywords
    application program interfaces; cache storage; cloud computing; computer centres; data integrity; random-access storage; RAM based storage; Sedna; big data management; cloud programming frameworks; cloud realtime processing; commodity servers; data access API; data center management; data consistency; data persistency; disk based distributed storage system; distributed cache system; memory based distributed cloud storage system; memory based key-value storage system; trigger based API; Cloud computing; Data models; Educational institutions; Programming; Random access memory; Scalability; Servers;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster Computing Workshops (CLUSTER WORKSHOPS), 2012 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4673-2893-7
  • Type

    conf

  • DOI
    10.1109/ClusterW.2012.28
  • Filename
    6355846