Rice Univesrity Logo
    • FAQ
    • Deposit your work
    • Login
    View Item 
    •   Rice Scholarship Home
    • Rice University Graduate Electronic Theses and Dissertations
    • Rice University Electronic Theses and Dissertations
    • View Item
    •   Rice Scholarship Home
    • Rice University Graduate Electronic Theses and Dissertations
    • Rice University Electronic Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Workload shaping for QoS and power efficiency of storage systems

    Thumbnail
    Name:
    1466801.PDF
    Size:
    2.766Mb
    Format:
    PDF
    View/Open
    Author
    Lu, Lanyue
    Date
    2009
    Advisor
    Varman, Peter J.
    Degree
    Master of Science
    Abstract
    The growing popularity of hosted storage services and shared storage infrastructure in data centers is driving the recent interest in resource management and QoS in storage systems. The bursty nature of storage workloads raises significant performance and provisioning challenges, leading to increased resource requirements, management costs, and energy consumption. We present a novel dynamic workload shaping framework to handle bursty server workloads, where the arrival stream is dynamically decomposed to isolate its bursty, and then rescheduled to exploit available slack. An optimal decomposition algorithm RTT and a recombination algorithm Miser make up the scheduling framework. We evaluate this framework using several real world storage workloads traces. The results show that workload shaping: (i) reduces the server capacity requirements and power consumption dramatically while affecting QoS guarantees minimally, (ii) provides better response time distributions over non-decomposed traditional scheduling methods, and (iii) decomposition can be used to provide more accurate capacity estimates for multiplexing several clients on a shared server.
    Keyword
    Computer science; Applied sciences
    Citation
    Lu, Lanyue. "Workload shaping for QoS and power efficiency of storage systems." (2009) Master’s Thesis, Rice University. https://hdl.handle.net/1911/61886.
    Metadata
    Show full item record
    Collections
    • ECE Theses and Dissertations [597]
    • Rice University Electronic Theses and Dissertations [13783]

    Home | FAQ | Contact Us | Privacy Notice | Accessibility Statement
    Managed by the Digital Scholarship Services at Fondren Library, Rice University
    Physical Address: 6100 Main Street, Houston, Texas 77005
    Mailing Address: MS-44, P.O.BOX 1892, Houston, Texas 77251-1892
    Site Map

     

    Searching scope

    Browse

    Entire ArchiveCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsTypeThis CollectionBy Issue DateAuthorsTitlesSubjectsType

    My Account

    Login

    Statistics

    View Usage Statistics

    Home | FAQ | Contact Us | Privacy Notice | Accessibility Statement
    Managed by the Digital Scholarship Services at Fondren Library, Rice University
    Physical Address: 6100 Main Street, Houston, Texas 77005
    Mailing Address: MS-44, P.O.BOX 1892, Houston, Texas 77251-1892
    Site Map