A QoC-Aware Discovery Service for the Internet of Things

  • Porfírio Gomes
  • Everton Cavalcante
  • Thais Batista
  • Chantal Taconet
  • Sophie Chabridon
  • Denis Conan
  • Flavia C. Delicato
  • Paulo F. Pires
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10070)


The Internet of Things (IoT) is an emergent paradigm characterized by a plethora of smart objects connected to the Internet. An inherent characteristic of IoT is the high heterogeneity and the wide distribution of objects, thereby calling for ways to describe in an unambiguous and machine-interpretable way the resources provided by objects, their properties, and the services they offer. In this context, discovery services play a significant role as they allow clients (middleware platforms, end-users, applications) to retrieve available resources based on appropriate search criteria, such as resource type, capabilities, location, and Quality of Context (QoC) parameters. To cope with these concerns, we introduce QoDisco, a QoC-aware discovery service relying on multiple-attribute searches, range queries, and synchronous/asynchronous operations. QoDisco also comprises an ontology-based information model for semantically describing resources, services, and QoC-related information. In this paper, we describe the QoDisco architecture and information model as well as an evaluation of the search procedure in an urban air pollution monitoring scenario.


Information Model Range Query Discovery Service Context Data SPARQL Query 


  1. 1.
  2. 2.
  3. 3.
    Mosquitto: an open source MQTT Broker. http://mosquitto.org/
  4. 4.
    SPARQL Query Language for RDF. http://www.w3.org/TR/rdf-sparql-query/
  5. 5.
    Atzori, L., Iera, A., Morabito, G.: The Internet of Things: a survey. Comput. Netw. 54(15), 2787–2805 (2010)CrossRefMATHGoogle Scholar
  6. 6.
    Barnaghi, P., et al.: Semantic sensor network XG final report, June 2011. http://www.w3.org/2005/Incubator/ssn/XGR-ssn-20110628/
  7. 7.
    Bassi, A., et al. (eds.): Enabling Things to Talk: Designing IoT Solutions with the IoT Architectural Reference Model. Springer, Berlin (2013)Google Scholar
  8. 8.
    Bellavista, P., Corradi, A., Fanelli, M., Foschini, L.: A survey of context data distribution for mobile ubiquitous systems. ACM Comput. Surv. 44(4), 24:1–24:45 (2012)CrossRefGoogle Scholar
  9. 9.
    Buchholz, T., Küpper, A., Schiffers, M.: Quality of context: what it is and why we need it. In: Proceedings of the 10th International Workshop of the OpenView University Association (2003)Google Scholar
  10. 10.
    Chabridon, S., Laborde, R., Desprats, T., Oglaza, A., Marie, P., Marquez, S.M.: A survey on addressing privacy together with quality of context for context management in the Internet of Things. Ann. Telecommun. 69(1), 47–62 (2014)CrossRefGoogle Scholar
  11. 11.
    Chen, H., Finin, T., Joshi, A.: The SOUPA ontology for pervasive computing. In: Tamma, V., Cranefield, S., Finin, T.W., Willmott, S. (eds.) Ontologies for Agents: Theory and Experiences. Whitestein Series in Software Agent Technologies, pp. 233–258. Birkhäuser, Basel (2005)CrossRefGoogle Scholar
  12. 12.
    Chun, S., Seo, S., Oh, B., Lee, K.H.: Semantic description, discovery and integration for the Internet of Things. In: Proceedings of the 2015 IEEE International Conference on Semantic Computing, pp. 272–275. IEEE, USA (2015)Google Scholar
  13. 13.
    Eugster, P.T., Felber, P.A., Guerraoui, R., Kermarrec, A.M.: The many faces of publish/subscribe. ACM Comput. Surv. 35(2), 114–131 (2003)CrossRefGoogle Scholar
  14. 14.
    Evdokimov, S., Fabian, B., Kunz, S., Schoenemann, N.: Comparison of discovery service architectures for the Internet of Things. In: Proceedings of the 2010 IEEE International Sensor Networks. Ubiquitous, and Trustworthy Computing, pp. 237–244. IEEE, USA (2010)Google Scholar
  15. 15.
    Fielding, R.T.: Architectural styles and the design of network-based software architectures. Ph.D. Dissertation, University of California-Irvine, USA (2000)Google Scholar
  16. 16.
    Holler, J., Tsiatsis, V., Mulligan, C., Avesand, S., Karnouskos, S., Boyle, D.: From Machine-to-Machine to the Internet of Things: Introduction to a New Age of Intelligence. Academic Press, Oxford (2014)Google Scholar
  17. 17.
    Juszczyk, L., Psaier, H., Manzoor, A., Dustdar, S.: Adaptive query routing on distributed context - the COSINE framework. In: Proceedings of the 10th International Conference on Mobile Data Management: Systems, Services and Middleware, pp. 588–593. IEEE Computer Society, USA (2009)Google Scholar
  18. 18.
    Li, J., Zaman, N., Li, H.: A decentralized locality-preserving context-aware service discovery framework for the Internet of Things. In: Proceedings of the 2015 IEEE International Conference on Services Computing, pp. 317–323. IEEE Computer Society, USA (2015)Google Scholar
  19. 19.
    Marie, P., Desprats, T., Chabridon, S., Sibilla, M.: Extending ambient intelligence to the Internet of Things: new challenges for QoC management. In: Hervás, R., Lee, S., Nugent, C., Bravo, J. (eds.) UCAmI 2014. LNCS, vol. 8867, pp. 224–231. Springer, Heidelberg (2014). doi: 10.1007/978-3-319-13102-3_37 Google Scholar
  20. 20.
    Marie, P., Desprats, T., Chabridon, S., Sibilla, M.: The QoCIM framework: concepts and tools for quality of context management. In: Brézillon, P., Gonzalez, A.J. (eds.) Context in Computing: A Cross-disciplinary Approach for Modeling the Real World, pp. 155–172. Springer, New York (2014)Google Scholar
  21. 21.
    Martin, D., et al.: Bringing semantics to web services: the OWL-S approach. In: Cardoso, J., Sheth, A. (eds.) SWSWPC 2004. LNCS, vol. 3387, pp. 26–42. Springer, Heidelberg (2005). doi: 10.1007/978-3-540-30581-1_4 CrossRefGoogle Scholar
  22. 22.
    Mayer, S., Guinard, D.: An extensible discovery service for smart things. In: Proceedings of the Second International Workshop on Web of Things. ACM, USA (2011)Google Scholar
  23. 23.
    Paganelli, F., Parlanti, D.: A DHT-based discovery service for the Internet of Things. J. Comput. Netw. Commun. 2012, 1–11 (2012)CrossRefGoogle Scholar
  24. 24.
    Perera, C., Zaslavsky, A., Christen, P., Compton, M., Georgakopoulos, D.: Context-aware sensor search, selection and ranking model for Internet of Things middleware. In: Proceedings of the 14th IEEE International Conference on Mobile Data Management (2013)Google Scholar
  25. 25.
    Perera, C., Zaslavsky, A., Christen, P., Georgakopoulos, D.: Context aware computing for the Internet of Things: a survey. IEEE Commun. Surv. Tutorials 16(1), 414–454 (2014)CrossRefGoogle Scholar
  26. 26.
    Ranganathan, A., Al-Muhtadi, J., Chetan, S., Campbell, R., Mickunas, M.D.: MiddleWhere: a middleware for location awareness in ubiquitous computing applications. In: Jacobsen, H.-A. (ed.) Middleware 2004. LNCS, vol. 3231, pp. 397–416. Springer, Heidelberg (2004). doi: 10.1007/978-3-540-30229-2_21 CrossRefGoogle Scholar
  27. 27.
    Schmidt, C., Parashar, M.: A peer-to-peer approach to Web service discovery. World Wide Web 7(2), 211–229 (2004)CrossRefGoogle Scholar
  28. 28.
    Spalazzi, L., Taccari, G., Bernardini, A.: An Internet of Things ontology for earthquake emergency evaluation and response. In: Proceedings of the 2014 International Conference on Collaboration Technologies and Systems, pp. 528–534. IEEE, USA (2014)Google Scholar
  29. 29.
    van Kranenburg, H., Bargh, M.S., Iacob, S., Peddemors, A.: A context management framework for supporting context-aware distributed applications. IEEE Commun. Mag. 44(8), 67–74 (2006)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Porfírio Gomes
    • 1
  • Everton Cavalcante
    • 1
  • Thais Batista
    • 1
  • Chantal Taconet
    • 2
  • Sophie Chabridon
    • 2
  • Denis Conan
    • 2
  • Flavia C. Delicato
    • 3
  • Paulo F. Pires
    • 3
  1. 1.DIMApFederal University of Rio Grande do NorteNatalBrazil
  2. 2.SAMOVAR, Télécom SudParis, CNRS, Université Paris-SaclayTélécom SudParisÉvryFrance
  3. 3.PPGI/DCCFederal University of Rio de JaneiroRio de JaneiroBrazil

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