• DocumentCode
    3659228
  • Title

    Integrating machine-to-machine measurement framework into oneM2M architecture

  • Author

    Amelie Gyrard;Soumya Kanti Datta;Christian Bonnet;Karima Boudaoud

  • Author_Institution
    Mobile Communications Department, Eurecom, Biot, France
  • fYear
    2015
  • Firstpage
    364
  • Lastpage
    367
  • Abstract
    Recent challenges in Internet of Things (IoT) include - (i) providing interoperability among IoT data, (ii) interpreting data generated by IoT devices, and (iii) assisting developers in accomplishing these tasks. Current standard development organizations such as oneM2M are designing semantic-based IoT architecture to address such challenges. However, the recent release of oneM2M standards does not provide any concrete tool for the semantic treatment of the IoT data. Previously, we proposed the Machine-to-Machine Measurement (M3) Framework which mitigates the challenges and assist developers in building semantic based IoT applications easily. Considering the usefulness and novel aspects of the M3 framework, the paper proposes to integrate it seamlessly into oneM2M architecture. The semantic requirements from oneM2M are pointed out and the M3 components addressing them are identified. A common service function (CSF) dedicated to semantic engine is introduced to the oneM2M architecture which extends the capabilities of common services entity (CSE) in terms of semantic treatment of IoT data. The new CSF also includes a catalog of semantic based IoT templates which are exploited by Application Entities to easily utilize the semantic engine. Two deployment scenarios of the upgraded oneM2M architecture have been discussed. Finally these extensions have been communicated to the oneM2M Management, Abstraction and Semantics (MAS) Group (Working Group 5).
  • Keywords
    "Decision support systems","Hafnium"
  • Publisher
    ieee
  • Conference_Titel
    Network Operations and Management Symposium (APNOMS), 2015 17th Asia-Pacific
  • Type

    conf

  • DOI
    10.1109/APNOMS.2015.7275364
  • Filename
    7275364