• DocumentCode
    3657154
  • Title

    Revenue Driven Resource Allocation for Virtualized Data Centers

  • Author

    Sajib Kundu;Raju Rangaswami;Ming Zhao;Ajay Gulati;Kaushik Dutta

  • Author_Institution
    Nat. Univ. of Singapore, Singapore, Singapore
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    197
  • Lastpage
    206
  • Abstract
    The increasing VM density in cloud hosting services makes careful management of physical resources such as CPU, memory, and I/O bandwidth within individual virtualized servers a priority. To maximize cost-efficiency, resource management needs to be coupled with the revenue generating mechanisms of cloud hosting: the service level agreements (SLAs) of hosted client applications. In this paper, we develop a server resource management framework that reduces data center resource management complexity substantially. Our solution implements revenue-driven dynamic resource allocation which continuously steers the resource distribution across hosted VMs within a server such as to maximize the SLA-generated revenue from the server. Our experimental evaluation for a VMware ESX hyper visor highlights the importance of both resource isolation and resource sharing across VMs. The empirical data shows a 7%-54% increase in total revenue generated for a mix of 10-25 VMs hosting either similar or diverse workloads when compared to using the currently available resource distribution mechanisms in ESX.
  • Keywords
    "Resource management","Servers","Dynamic scheduling","Virtual machine monitors","Robustness","Accuracy","Optimization"
  • Publisher
    ieee
  • Conference_Titel
    Autonomic Computing (ICAC), 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/ICAC.2015.40
  • Filename
    7266964