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CloudNet: dynamic pooling of cloud resources by live WAN migration of virtual machines

Published:09 March 2011Publication History
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Abstract

Virtual machine technology and the ease with which VMs can be migrated within the LAN, has changed the scope of resource management from allocating resources on a single server to manipulating pools of resources within a data center. We expect WAN migration of virtual machines to likewise transform the scope of provisioning compute resources from a single data center to multiple data centers spread across the country or around the world. In this paper we present the CloudNet architecure as a cloud framework consisting of cloud computing platforms linked with a VPN based network infrastructure to provide seamless and secure connectivity between enterprise and cloud data center sites. To realize our vision of efficiently pooling geographically distributed data center resources, CloudNet provides optimized support for live WAN migration of virtual machines. Specifically, we present a set of optimizations that minimize the cost of transferring storage and virtual machine memory during migrations over low bandwidth and high latency Internet links. We evaluate our system on an operational cloud platform distributed across the continental US. During simultaneous migrations of four VMs between data centers in Texas and Illinois, CloudNet's optimizations reduce memory migration time by 65% and lower bandwidth consumption for the storage and memory transfer by 19GB, a 50% reduction.

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      • Published in

        cover image ACM SIGPLAN Notices
        ACM SIGPLAN Notices  Volume 46, Issue 7
        VEE '11
        July 2011
        231 pages
        ISSN:0362-1340
        EISSN:1558-1160
        DOI:10.1145/2007477
        Issue’s Table of Contents
        • cover image ACM Conferences
          VEE '11: Proceedings of the 7th ACM SIGPLAN/SIGOPS international conference on Virtual execution environments
          March 2011
          250 pages
          ISBN:9781450306874
          DOI:10.1145/1952682

        Copyright © 2011 ACM

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        Association for Computing Machinery

        New York, NY, United States

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        • Published: 9 March 2011

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