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Pyxis+: A Scalable and Adaptive Data Replication Framework

  • Yuwei Yang
  • Beihong Jin
  • Sen Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8210)

Abstract

Data replication can improve the performance and availability for applications, and when it is employed by big data applications, it has to solve the challenges posed by big data applications, i.e., offering scalability and varying consistency levels. In this paper, we design and implement a data replication framework Pyxis+, whereby replication-aware applications can be developed in a rapid and convenient way. Pyxis+ allows the applications to register different consistency levels and automatically switches the consistency levels according to the change of requirements and performance. Meanwhile, on the basis of the consistency guarantees, Pyxis+ takes advantage of the consistent hashing technology to improve the scalability of data access. Simulation experimental results show that Pyxis+ can obtain relatively stable throughputs and response time by adding or removing replica managers while facing the increase of user requests.

Keywords

Replication Framework Consistency Level Scalability 

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Yuwei Yang
    • 1
    • 2
  • Beihong Jin
    • 1
    • 2
  • Sen Li
    • 1
    • 2
  1. 1.Institute of SoftwareChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina

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