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Efficient Live Migration of Virtual Machines with a Novel Data Filter

  • Yonghui Ruan
  • Zhongsheng Cao
  • Yuanzhen Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8707)

Abstract

Live migration of virtual machines (VM) is useful for resource management of data centers and cloud platforms. The pre-copy algorithm is widely used for memory migration. It is very efficient to deal with the memory migration of read-intensive workloads. But for write-intensive workloads, the pre-copy’s straightforward iteration strategy will become inefficient. In this paper, we propose a novel data filter to improve the pre-copy algorithm in this inefficient situation. In each round of iteration, the data filter forecasts the pages which will be subsequently dirtied, and then filters them from the send list. This prevents the pages from being repeatedly transmitted, thus reducing migration time and bandwidth resource consumption. Meanwhile, the data filter also checks if the previously filtered pages should be re-added to the send list. This ensures that the downtime will not be increased. Experimental results show that the improved algorithm effectively reduces the amount of migrated data, while keeping the downtime at the same level.

Keywords

Virtual Machine Migration Time State Transition Matrix Data Filter Virtual Machine Migration 
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

© IFIP International Federation for Information Processing 2014

Authors and Affiliations

  • Yonghui Ruan
    • 1
  • Zhongsheng Cao
    • 1
  • Yuanzhen Wang
    • 1
  1. 1.School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhanChina

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