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Title: Efficient Checkpointing of Virtual Machines using Virtual Machine Introspection

Cloud Computing environments rely heavily on system-level virtualization. This is due to the inherent benefits of virtualization including fault tolerance through checkpoint/restart (C/R) mechanisms. Because clouds are the abstraction of large data centers and large data centers have a higher potential for failure, it is imperative that a C/R mechanism for such an environment provide minimal latency as well as a small checkpoint file size. Recently, there has been much research into C/R with respect to virtual machines (VM) providing excellent solutions to reduce either checkpoint latency or checkpoint file size. However, these approaches do not provide both. This paper presents a method of checkpointing VMs by utilizing virtual machine introspection (VMI). Through the usage of VMI, we are able to determine which pages of memory within the guest are used or free and are better able to reduce the amount of pages written to disk during a checkpoint. We have validated this work by using various benchmarks to measure the latency along with the checkpoint size. With respect to checkpoint file size, our approach results in file sizes within 24% or less of the actual used memory within the guest. Additionally, the checkpoint latency of our approach is upmore » to 52% faster than KVM s default method.« less
 [1] ;  [1] ;  [2] ;  [2]
  1. Tennessee Technological University
  2. ORNL
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Conference: International Symposium on Cluster, Cloud and Grid Computing~(CCGrid), Chicago, IL, USA, 20140526, 20140529
Research Org:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org:
USDOE Office of Science (SC)
Country of Publication:
United States