• DocumentCode
    2440198
  • Title

    Power-aware resource provisioning in cluster computing

  • Author

    Xiong, Kaiqi

  • Author_Institution
    Dept. of Comput. Sci., Texas A&M Univ., Commerce, TX, USA
  • fYear
    2010
  • fDate
    19-23 April 2010
  • Firstpage
    1
  • Lastpage
    11
  • Abstract
    The high power consumption of cluster computing infrastructures has become a major concern. It leads to the increased heat dissipation and decreased reliability of cluster servers. Power management becomes a critical issue in cluster computing. In this paper, we start with an analysis of the relationship between cluster performance and power consumption. We study both the problem of minimizing the average end-to-end delay with the constraint of average energy consumption and the problem of minimizing the average energy consumption of cluster service requests with the constraint of an average end-to-end delay for customer services. We propose novel approaches to solving these two problems. In an effort to maximize profits, a service provider only provides sufficient resources to ensure quality of services (QoS) but often avoid over provisioning to meet QoS defined in a service level agreement (SLA) which is a contract agreed between a customer and a service provider. We present an approach for optimizing SLA-based resource provisioning in cluster computing in that we minimize the total cost of cluster servers owned by a service provider while satisfying the requirements of both a percentile of the end-to-end delay and average energy consumption. Numerical experiments show that the proposed approach is efficient and accurate for the SLA-based resource provisioning problem in cluster computing.
  • Keywords
    performance evaluation; power aware computing; workstation clusters; average end-to-end delay; average energy consumption; cluster computing infrastructures; cluster performance; cluster servers; heat dissipation; power consumption; power management; power-aware resource; quality of services; service level agreement; Business; Computer science; Contracts; Customer service; Delay; Energy consumption; Energy management; High performance computing; Performance analysis; Quality of service;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel & Distributed Processing (IPDPS), 2010 IEEE International Symposium on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1530-2075
  • Print_ISBN
    978-1-4244-6442-5
  • Type

    conf

  • DOI
    10.1109/IPDPS.2010.5470395
  • Filename
    5470395