VMShadow: optimizing the performance of virtual desktops in distributed clouds

Authors:
Tian Guo;Vijay Gopalakrishnan;K. K. Ramakrishnan;Prashant Shenoy;Arun Venkataramani;Seungjoon Lee
Affiliations:
University of Massachusetts Amherst;AT&T Labs - Research;AT&T Labs - Research;University of Massachusetts Amherst;University of Massachusetts Amherst;AT&T Labs - Research
Venue:
Proceedings of the 4th annual Symposium on Cloud Computing
Year:
2013

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Abstract

We present VMShadow, a system that automatically optimizes the location and performance of applications based on their dynamic workloads. We prototype VMShadow and demonstrate its efficacy using VM-based desktops in the cloud as an example application. Our experiments on a private cloud as well as the EC2 cloud, using a nested hypervisor, show that VMShadow is able to discriminate between location-sensitive and location-insensitive desktop VMs and judiciously moves only those that will benefit the most from the migration. For example, VMShadow performs transcontinental VM migrations in ~ 4 mins and can improve VNC's video refresh rate by up to 90%.