• Login
    View Item 
    •   SMARTech Home
    • Center for Experimental Research in Computer Systems (CERCS)
    • CERCS Technical Reports
    • View Item
    •   SMARTech Home
    • Center for Experimental Research in Computer Systems (CERCS)
    • CERCS Technical Reports
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    CCM: Scalable, On-Demand Compute Capacity Management for Cloud Datacenters

    Thumbnail
    View/Open
    git-cercs-13-01.pdf (381.9Kb)
    Date
    2013
    Author
    Kesavan, Mukil
    Ahmad, Irfan
    Krieger, Orran
    Soundararajan, Ravi
    Gavrilovska, Ada
    Schwan, Karsten
    Metadata
    Show full item record
    Abstract
    We present CCM (Cloud Capacity Manager) – a prototype system, and, methods for dynamically multiplexing the compute capacity of cloud datacenters at scales of thousands of machines, for diverse workloads with variable demands. This enables mitigation of resource consumption hotspots and handling unanticipated demand surges, leading to improved resource availability for applications and better datacenter utilization levels. Extending prior studies primarily concerned with accurate capacity allocation and ensuring acceptable application performance, CCM also focuses on the tradeoffs due to two unavoidable issues in large scale commodity datacenters: (i) maintaining low operational overhead, and (ii) coping with the increased incidences of management operation failures. CCM is implemented in an industry-strength cloud infrastructure built on top of the VMware vSphere virtualization platform and is currently deployed in a 700 physical host datacenter. Its experimental evaluation uses production workload traces and a suite of representative cloud applications to generate dynamic scenarios. Results indicate that the pragmatic cloud-wide nature of CCM provides up to 25% more resources for workloads and improves datacenter utilization by up to 20%, compared to the alternative approach of multiplexing capacity within multiple smaller datacenter partitions.
    URI
    http://hdl.handle.net/1853/53368
    Collections
    • CERCS Technical Reports [193]

    Browse

    All of SMARTechCommunities & CollectionsDatesAuthorsTitlesSubjectsTypesThis CollectionDatesAuthorsTitlesSubjectsTypes

    My SMARTech

    Login

    Statistics

    View Usage StatisticsView Google Analytics Statistics
    facebook instagram twitter youtube
    • My Account
    • Contact us
    • Directory
    • Campus Map
    • Support/Give
    • Library Accessibility
      • About SMARTech
      • SMARTech Terms of Use
    Georgia Tech Library266 4th Street NW, Atlanta, GA 30332
    404.894.4500
    • Emergency Information
    • Legal and Privacy Information
    • Human Trafficking Notice
    • Accessibility
    • Accountability
    • Accreditation
    • Employment
    © 2020 Georgia Institute of Technology