Adverstise Based Adaptive Model for IoT Device in Network Virtualization Environment

  • YunHee Kang
  • Younhoon Park
  • Jonghee Yoon
  • KwngMan KoEmail author
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 474)


Internet of Things (IoT) systems are inherently dynamic. The number of such systems has been grow so fast. Network virtualization technology has changed the networking industry dramatically. In this paper, we introduce a configuration of common device metadata (CDM) for IoT device including device sensing data configuration, device communication and non-functional requirement. We discuss an advertise-based adaptive model for IoT devices composed of soft-sensor for the implementation of services like data source monitoring.


IoT Network virtualization Advertise-based adaptive model Soft-sensor 



This work was supported by Institute for Information & Communication Technology Promotion (IITP) grant funded by Korea Government (MSIP 2017-0-01705). This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (2017030223).


  1. 1.
    Atzori, L., Iera, A., Morabito, G.: The internet of things: a survey. Comput. Netw. Int. J. Comput. Telecommun. Netw. 54(15), 2787–2805 (2010)zbMATHGoogle Scholar
  2. 2.
    Gubbi, J., Buyya, R., Marusic, S., Palaniswami, M.: Internet of things (IoT): a vision, architectural elements, and future directions. Future Gener. Comput. Syst. 29(7), 1645–1660 (2013)CrossRefGoogle Scholar
  3. 3.
  4. 4.
    Haleplidis, E., Pentikousis, K., Denazis, S., Salim, J.H., Meyer, D., Koufopavlou, O.: Software-Defined Networking (SDN): Layers and Architecture Terminology, RFC 7426, IETF, January 2015. ISSN 2070-1721Google Scholar
  5. 5.
    Fortuna, L., Graziani, S., Rizzo, A., Xibilia, M.G.: Soft Sensors for Monitoring and Control of Industrial Processes. Springer, London (2007). ISBN 978-1-84628-479-3zbMATHGoogle Scholar
  6. 6.
    Kadlec, P., Gabrys, B., Strandt, S.: Data-driven soft sensors in the process industry. Comput. Chem. Eng. 33(4), 795–814 (2009)CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • YunHee Kang
    • 1
  • Younhoon Park
    • 2
  • Jonghee Yoon
    • 3
  • KwngMan Ko
    • 4
    Email author
  1. 1.Division of Information CommunicationBaekseok UniversityCheonanSouth Korea
  2. 2.Department of Computer EngineeringSookmyung Women’s UniversitySeoulSouth Korea
  3. 3.Department of Computer EngineeringYoungnam UniversityGyeongsanSouth Korea
  4. 4.Department of Computer EngineeringSangji UniversityWonjuSouth Korea

Personalised recommendations