• DocumentCode
    170720
  • Title

    Let´s stay together: Towards traffic aware virtual machine placement in data centers

  • Author

    Xin Li ; Jie Wu ; Shaojie Tang ; Sanglu Lu

  • Author_Institution
    State Key Lab. for Novel Software Technol., Nanjing Univ., Nanjing, China
  • fYear
    2014
  • fDate
    April 27 2014-May 2 2014
  • Firstpage
    1842
  • Lastpage
    1850
  • Abstract
    As tenants take networked virtual machines (VMs) as their requirements, effective placement of VMs is needed to reduce the network cost in cloud data centers. The cost is one of the major concerns for the cloud providers. In addition to the cost caused by network traffics (N-cost), the cost caused by the utilization of physical machines (PM-cost) is also non-negligible. In this paper, we focus on the optimized placement of VMs to minimize the cost, the combination of N-cost and PM-cost. We define N-cost by various functions, according to different communication models. We formulate the placement problem, and prove it to be NP-hard. We investigate the problem from two aspects. Firstly, we put a special emphasis on minimizing the N-cost with fixed PM-cost. For the case that tenants request the same amount of VMs, we present optimal algorithms under various definitions of N-cost. For the case that tenants require different numbers of VMs, we propose an approximation algorithm. Also, a greedy algorithm is implemented as the baseline to evaluate the performance. Secondly, we study the general case of the VM placement problem, in which both N-cost and PM-cost are taken into account. We present an effective binary-search-based algorithm to determine how many PMs should be used, which makes a tradeoff between PM-cost and N-cost. For all of the algorithms, we conduct theoretical analysis and extensive simulations to evaluate their performance and efficiency.
  • Keywords
    approximation theory; cloud computing; computational complexity; computer centres; cost reduction; greedy algorithms; search problems; virtual machines; N-cost; NP-hard problem; PM-cost; VM; approximation algorithm; binary-search-based algorithm; cloud data centers; different communication models; greedy algorithm; network cost reduction; network traffic; networked virtual machines; optimal algorithms; physical machines; traffic aware virtual machine placement; Algorithm design and analysis; Approximation algorithms; Computers; Conferences; Cost function; Optimized production technology; Virtual machining; Clouds; cost optimization; data center; subset-sum problem; vector bin packing; virtual machine placement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    INFOCOM, 2014 Proceedings IEEE
  • Conference_Location
    Toronto, ON
  • Type

    conf

  • DOI
    10.1109/INFOCOM.2014.6848123
  • Filename
    6848123