• DocumentCode
    3746910
  • Title

    The impact of Big Data on M&S: do we need to get “big”?

  • Author

    Siman J. E. Taylor

  • Author_Institution
    Brunel University London, St. Johns Building, Kingston Lane, UB8 3PH, UK
  • fYear
    2015
  • Firstpage
    3085
  • Lastpage
    3085
  • Abstract
    Driven by innovations such as mass customisation, complex supply chains, smart cities and emerging cyber-physical and Internet of Things systems, Big Data is presenting a fascinating range of challenges to Analytics. New fields are emerging such as Big Data Analytics and Data Science. Modeling & Simulation (M&S) is core to Analytics. Arguably, contemporary M&S practices cannot deal with the demands of Big Data. The implication of this is that M&S may not feature in the Big Data Analytics techniques and tools of the future. Based on recent experiences from the i4MS FP7 European Cloudbased Simulation platform for Manufacturing and Engineering (CloudSME) and associated industrial projects, this talk will outline the key challenges that Big Data has to M&S and strongly argue that M&S has to get “Big” to meet these challenges. Exciting opportunities lie ahead for multi-disciplinary teams of practitioners and researchers from OR/MS, Computer Science and domain specific fields. Indeed “Big” Simulation presents its own possibilities and the talk will conclude with thoughts on the potential for “Big” Simulation Analytics to move beyond Big Data into future Dynamic Data Driven Application Systems.
  • Keywords
    "Big data","Computational modeling","Biological system modeling","Analytical models","Cloud computing","Data models","Manufacturing"
  • Publisher
    ieee
  • Conference_Titel
    Winter Simulation Conference (WSC), 2015
  • Electronic_ISBN
    1558-4305
  • Type

    conf

  • DOI
    10.1109/WSC.2015.7408411
  • Filename
    7408411