• DocumentCode
    2343573
  • Title

    Kansei: a testbed for sensing at scale

  • Author

    Ertin, Emre ; Arora, Abhishek ; Ramnath, Rajiv ; Nesterenko, Mikhail ; Naik, Vinayak ; Bapat, Sandip ; Kulathumani, Vinod ; Sridharan, Mukundan ; Zhang, Hongwei ; Cao, Hui

  • Author_Institution
    Ohio State Univ., Columbus, OH
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    399
  • Lastpage
    406
  • Abstract
    The Kansei testbed at the Ohio State University is designed to facilitate research on networked sensing applications at scale. Kansei embodies a unique combination of characteristics as a result of its design focus on sensing and scaling: (i) Heterogeneous hardware infrastructure with dedicated node resources for local computation, storage, data exfiltration and back-channel communication, to support complex experimentation, (ii) Time accurate hybrid simulation engine for simulating substantially larger arrays using testbed hardware resources, (iii) High fidelity sensor data generation and real-time data and event injection, (iv) Software components and associated job control language to support complex multi-tier experiments utilizing real hardware resources and data generation and simulation engines. In this paper, we present the elements of Kansei testbed architecture, including its hardware and software platforms as well as its hybrid simulation and sensor data generation engines
  • Keywords
    Hi-Fi equipment; intelligent sensors; wireless channels; wireless sensor networks; Kansei testbed; back-channel communication; hardware-software platform; heterogeneous hardware infrastructure; high fidelity sensor data generation; hybrid simulation engine; software component; Character generation; Communication system control; Computational modeling; Discrete event simulation; Engines; Hardware; Hybrid power systems; Job design; Sensor arrays; Software testing; Hybrid Simulation; Sensor Modeling; Sensor Network Testbed;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Processing in Sensor Networks, 2006. IPSN 2006. The Fifth International Conference on
  • Conference_Location
    Nashville, TN
  • Print_ISBN
    1-59593-334-4
  • Type

    conf

  • DOI
    10.1109/IPSN.2006.243879
  • Filename
    1662484