• DocumentCode
    571709
  • Title

    Cloud-Based Simulation: The State-of-the-Art Computer Simulation Paradigm

  • Author

    Liu, Xiaocheng ; Qiu, Xiaogang ; Chen, Bin ; Huang, Kedi

  • Author_Institution
    Syst. Simulation Lab., Nat. Univ. of Defense Technol., Changsha, China
  • fYear
    2012
  • fDate
    15-19 July 2012
  • Firstpage
    71
  • Lastpage
    74
  • Abstract
    The cloud computing paradigm attracts increasing amount of Modeling&Simulation (M&S) practitioners to perform their simulations in the cloud. Two issues, namely, the architecture of the Cloud-based Simulation (CSim) and the parallel simulation job scheduling in the CSim, should be addressed ï¬rst to make the CSim practical. This paper reports our recent work on the two issues. The architecture we proposed covers the software involved in the whole process of M&S by providing the Modeling as a Service (MaaS), the Execution as a Service (EaaS) and the Analysis as a Service (AaaS). The architecture also encourages the reuse of available simulation resources with the aid of the Simulation Resource as a Service (SRaaS). For the issue of parallel simulation job scheduling in the CSim, we ï¬rst propose a two-tier processor partition method to organize virtual machines (VMs) for parallel simulation workload consolidation, the two-tier VMs have different CPU priority. We then present four scheduling algorithms under such a partition method to cope with four common situations. Our extensive experiments on well-known traces show that all the four algorithms signiï¬cantly outperform their competitors.
  • Keywords
    cloud computing; digital simulation; parallel processing; processor scheduling; resource allocation; software architecture; software reusability; virtual machines; AaaS; CPU priority; CSim; EaaS; M-and-S practitioners; MaaS; SRaaS; analysis-as-a-service; cloud computing paradigm; cloud-based simulation architecture; execution-as-a-service; modeling-and-simulation practitioners; modeling-as-a-service; parallel simulation job scheduling; parallel simulation workload consolidation; scheduling algorithms; simulation resource reusability; simulation resource-as-a-service; two-tier VM; two-tier processor partition method; two-tier virtual machines; Cloud computing; Computational modeling; Computer architecture; Scheduling; Scheduling algorithms; Cloud Computing; M&S; Parallel Job scheduling; Resource Consolidation; Simulation as a Service;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Principles of Advanced and Distributed Simulation (PADS), 2012 ACM/IEEE/SCS 26th Workshop on
  • Conference_Location
    Zhangjiajie
  • ISSN
    1087-4097
  • Print_ISBN
    978-1-4673-1797-9
  • Type

    conf

  • DOI
    10.1109/PADS.2012.11
  • Filename
    6305887