• DocumentCode
    1817587
  • Title

    Heavy traffic optimal resource allocation algorithms for cloud computing clusters

  • Author

    Maguluri, Siva Theja ; Srikant, R. ; Ying, Lei

  • Author_Institution
    Dept. of ECE & CSL, Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • fYear
    2012
  • fDate
    4-7 Sept. 2012
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Cloud computing is emerging as an important platform for business, personal and mobile computing applications. In this paper, we study a stochastic model of cloud computing, where jobs arrive according to a stochastic process and request resources like CPU, memory and storage space. We consider a model where the resource allocation problem can be separated into a routing or load balancing problem and a scheduling problem. We study the join-the-shortest-queue routing and power-of-two-choices routing algorithms with MaxWeight scheduling algorithm. It was known that these algorithms are throughput optimal. In this paper, we show that these algorithms are queue length optimal in the heavy traffic limit.
  • Keywords
    cloud computing; queueing theory; resource allocation; scheduling; stochastic processes; telecommunication network routing; telecommunication traffic; MaxWeight scheduling algorithm; cloud computing clusters; heavy traffic optimal resource allocation algorithms; join-the-shortest-queue routing algorithms; load balancing problem; power-of-two-choices routing algorithms; request resources; stochastic model; stochastic process; Cloud computing; Routing; Scheduling algorithms; Servers; Steady-state; Upper bound; Vectors; Scheduling; cloud computing; load balancing; resource allocation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Teletraffic Congress (ITC 24), 2012 24th International
  • Conference_Location
    Krakow
  • Print_ISBN
    978-1-4673-1292-9
  • Electronic_ISBN
    978-0-9836283-3-0
  • Type

    conf

  • Filename
    6331819