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VMShadow: optimizing the performance of virtual desktops in distributed clouds

Published: 01 October 2013 Publication History

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%.

References

[1]
S. Barker, Y. Chi, H. J. Moon, H. Hacigümüş, and P. Shenoy. "Cut me some slack": latency-aware live migration for databases. In Proceedings of Conference on Extending Database Technology, 2012.
[2]
D. Williams, H. Jamjoom, and H. Weatherspoon. The xen-blanket: virtualize once, run everywhere. In Proceedings of ACM EuroSys, 2012.
[3]
T. Wood, K. K. Ramakrishnan, P. Shenoy, and J. Van der Merwe. CloudNet: Dynamic Pooling of Cloud Resources by Live WAN Migration of Virtual Machines. In Proceedings of ACM SIGPLAN/SIGOPS conference on Virtual Execution Environments (VEE), Mar. 2011.

Cited By

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  • (2016)GScheduler: Reducing Mobile Device Energy Consumption2016 4th Intl Conf on Applied Computing and Information Technology/3rd Intl Conf on Computational Science/Intelligence and Applied Informatics/1st Intl Conf on Big Data, Cloud Computing, Data Science & Engineering (ACIT-CSII-BCD)10.1109/ACIT-CSII-BCD.2016.014(1-6)Online publication date: Dec-2016
  • (2016)Resource provision algorithms in cloud computingJournal of Network and Computer Applications10.1016/j.jnca.2015.12.01864:C(23-42)Online publication date: 1-Apr-2016

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Published In

cover image ACM Conferences
SOCC '13: Proceedings of the 4th annual Symposium on Cloud Computing
October 2013
427 pages
ISBN:9781450324281
DOI:10.1145/2523616
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 October 2013

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  • Research-article

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SOCC '13
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SOCC '13: ACM Symposium on Cloud Computing
October 1 - 3, 2013
California, Santa Clara

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SOCC '13 Paper Acceptance Rate 23 of 114 submissions, 20%;
Overall Acceptance Rate 169 of 722 submissions, 23%

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Cited By

View all
  • (2016)GScheduler: Reducing Mobile Device Energy Consumption2016 4th Intl Conf on Applied Computing and Information Technology/3rd Intl Conf on Computational Science/Intelligence and Applied Informatics/1st Intl Conf on Big Data, Cloud Computing, Data Science & Engineering (ACIT-CSII-BCD)10.1109/ACIT-CSII-BCD.2016.014(1-6)Online publication date: Dec-2016
  • (2016)Resource provision algorithms in cloud computingJournal of Network and Computer Applications10.1016/j.jnca.2015.12.01864:C(23-42)Online publication date: 1-Apr-2016

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