• DocumentCode
    130813
  • Title

    A multi-dimensional ontology-based IoT resource model

  • Author

    Huijuan Zhang ; Chao Meng

  • Author_Institution
    Sch. of Software Eng., Tongji Univ., Shanghai, China
  • fYear
    2014
  • fDate
    27-29 June 2014
  • Firstpage
    124
  • Lastpage
    127
  • Abstract
    Nowadays researches related to resource management and representation of IoT (Internet of Things) emphasize on making identify regulation or describing device working principle. However they could not represent dynamic feature and multi-dimensional feature of interaction. This paper propose a multi-dimensional ontology-based IoT resource model to solve above defects. For resource management, searching and reasoning, this model divides resource into 4 key concepts: general situation, variable feature, function and enforce. Then this paper classify resource into 5 dimensions. Experimental result shows that when IoT resource contains time feature, location feature and priority feature, resource model works well to accomplish management and searching task. In addition, this model lays a foundation for service model, which is in upper layer of resource model.
  • Keywords
    Internet of Things; ontologies (artificial intelligence); resource allocation; ubiquitous computing; Internet of Things; device working principle; dynamic interaction feature; enforce concept; function concept; general situation concept; location feature; multidimensional interaction feature; multidimensional ontology-based IoT resource model; priority feature; reasoning; resource management; resource representation; resource searching; time feature; variable feature concept; Cognition; Computational modeling; Context; Dynamic scheduling; Internet of Things; Ontologies; Sensors; IoT; Multi-dimensional Ontology; Resource Description; Search;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
  • Conference_Location
    Beijing
  • ISSN
    2327-0586
  • Print_ISBN
    978-1-4799-3278-8
  • Type

    conf

  • DOI
    10.1109/ICSESS.2014.6933527
  • Filename
    6933527