• DocumentCode
    1711782
  • Title

    Realizing the Potential of IoT Using Software-Defined Ecosystems

  • Author

    Parashar, Manish ; Abdelbaky, Moustafa ; Mengsong Zou ; Zamani, Ali Reza ; Diaz-Montes, Javier

  • Author_Institution
    Rutgers Discovery Inf. Inst., Rutgers Univ., Piscataway, NJ, USA
  • fYear
    2015
  • Firstpage
    1149
  • Lastpage
    1158
  • Abstract
    Pervasive computational ecosystems that combine data sources and computing/communication resources in self-managed environments, such as the ones powered by Internet of Things (IoT) devices, have the potential to automate and facilitate many aspects of our lives, and impact a variety of applications, from the management of extreme events to the optimization of everyday processes. However, this vision remains mostly unrealized despite the fact that the technology to achieve it exists, largely because of the gap between our ability to collect data and our ability to gain insight from it. In this paper, we discuss the challenges associated with providing a pervasive computational ecosystem. We then present our vision of how to best support data-driven computational ecosystems and propose a conceptual architecture that leverages ideas from software-defined environments in order to combine data, computing, and communication resources. In addition, we show how this proposed architecture enables the execution of data-driven workflows on top of these resources.
  • Keywords
    Internet of Things; cloud computing; Internet of Things devices; IoT; optimization; pervasive computational ecosystems; software-defined ecosystems; Computational modeling; Computer architecture; Distributed databases; Dynamic scheduling; Ecosystems; Runtime; Uncertainty; Autonomics; Cloud computing; Data-driven workflows; Federated computing; Internet of Things; Software-defined environments; Software-defined infrastructure; Software-defined networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing (CLOUD), 2015 IEEE 8th International Conference on
  • Conference_Location
    New York City, NY
  • Print_ISBN
    978-1-4673-7286-2
  • Type

    conf

  • DOI
    10.1109/CLOUD.2015.169
  • Filename
    7214179