• DocumentCode
    2194900
  • Title

    Unifying Cloud Management: Towards Overall Governance of Business Level Objectives

  • Author

    Sedaghat, Mina ; Hernandez, F. ; Elmroth, Erik

  • Author_Institution
    Dept. of Comput. Sci., Umea Univ., Umea, Sweden
  • fYear
    2011
  • fDate
    23-26 May 2011
  • Firstpage
    591
  • Lastpage
    597
  • Abstract
    We address the challenge of providing unified cloud resource management towards an overall business level objective, given the multitude of managerial tasks to be performed and the complexity of any architecture to support them. Resource level management tasks include elasticity control, virtual machine and data placement, autonomous fault management, etc, which are intrinsically difficult problems since services normally have unknown lifetime and capacity demands that varies largely over time. To unify the management of these problems, (for optimization with respect to some higher level business level objective, like optimizing revenue while breaking no more than a certain percentage of service level agreements)becomes even more challenging as the resource level managerial challenges are far from independent. After providing the general problem formulation, we review recent approaches taken by the research community, including mainly general autonomic computing technology for large-scale environments and resource level management tools equipped with some business oriented or otherwise qualitative features. We propose and illustrate a policy-driven approach where a high-level management system monitors overall system and services behavior and adjusts lower level policies (e.g., thresholds for admission control, elasticity control, server consolidation level, etc) for optimization towards the measurable business level objectives.
  • Keywords
    business data processing; cloud computing; fault tolerant computing; optimisation; resource allocation; virtual machines; architecture complexity; autonomic computing technology; autonomous fault management; business level objective; data placement; elasticity control; high-level management system; large-scale environment; managerial tasks; optimization; qualitative feature; research community; resource level management tasks; resource level management tools; services behavior; unified cloud resource management; virtual machine; Adaptation models; Elasticity; Engines; Monitoring; Optimization; Resource management; Autonomic Computing; Cloud governance; Policy-driven Management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cluster, Cloud and Grid Computing (CCGrid), 2011 11th IEEE/ACM International Symposium on
  • Conference_Location
    Newport Beach, CA
  • Print_ISBN
    978-1-4577-0129-0
  • Electronic_ISBN
    978-0-7695-4395-6
  • Type

    conf

  • DOI
    10.1109/CCGrid.2011.65
  • Filename
    5948652