An Efficient Overload Control Strategy in Cloud

  • Xiling Sun
  • Jiajie Xu
  • Zhiming Ding
  • Xu Gao
  • Kuien Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7234)


In cloud, service performances are expected to meet various QoS requirements stably, and a great challenge for achieving this comes from the great workload fluctuations in stateful systems. So far, few previous works have endeavored for handling overload caused by such fluctuations. In this paper, we propose an efficient overload control strategy to solve this problem. Crucial server status information is indexed by R-tree to provide global view for data movement. Based on index, a two-step filtering approach is introduced to eliminate irrational server candidates. A server selection algorithm considering workload patterns is presented afterwards to acquire load-balancing effects. Extensive experiments are conducted to evaluate the performance of our strategy.


Cloud Computing Data Movement Server Selection Elasticity Provision Server Candidate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Xiling Sun
    • 1
  • Jiajie Xu
    • 1
  • Zhiming Ding
    • 1
  • Xu Gao
    • 1
  • Kuien Liu
    • 1
  1. 1.NFS, Institute of SoftwareChinese Academy of SciencesBeijingChina

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