A semantic-based discovery service for the Internet of Things
Tóm tắt
With the Internet of Things (IoT), applications should interact with a huge number of devices and retrieve context data produced by those objects, which have to be discovered and selected a priori. Due to the number, heterogeneity, and dynamicity of resources, discovery services are required to consider many selection criteria, e.g., device capabilities, location, context data type, contextual situations, and quality. In this paper, we describe QoDisco, a semantic-based discovery service that addresses this requirement in IoT. QoDisco is composed of a set of repositories storing resource descriptions according to an ontology-based information model and it provides multi-attribute and range querying capabilities. We have evaluated different approaches to reduce the inherent cost of semantic search, namely parallel interactions with multiple repositories and publish-subscribe interactions. This paper also reports the results of some performance experiments on QoDisco with respect to these approaches to handle resource discovery requests in IoT.
Tài liệu tham khảo
Object Management Group. Trading Object Service Specification Version 1.0. https://www.omg.org/spec/TRADE/About-TRADE/.
Aziez M, Benharzallah S, Bennoui H. A comparative analysis of service discovery approaches for the Internet of Things. Int Res J Electron Comput Eng. 2017; 3(1):17–22.
Guinard D, Trifa V, Karnouskos S, Spiess P, Savio D. Interacting with the SOA-based Internet of Things: Discovery, query, selection, and on-demand provisioning of Web services. IEEE Trans Serv Comput. 2010; 3(3):223–35.
Issarny V, Georgantas N, Hachem S, Zarras A, Vassiliadist P, Autili M, et al.Service-oriented middleware for the Future Internet: State of the art and research directions. J Internet Serv Appl. 2011; 2(1):23–45.
Wei Q, Jin Z. Service discovery for Internet of Things: A context-awareness perspective. In: Proceedings of the Fourth Asia-Pacific Symposium on Internetware. New York: ACM: 2012.
Cassar G, Barnaghi P, Wang W, Moessner K. A hybrid semantic matchmaker for IoT services. In: Proceedings of the 2012 IEEE International Conference on Green Computing and Communications. USA: IEEE: 2012. p. 210–6.
Paganelli F, Parlanti D. A DHT-based discovery service for the Internet of Things. J Comput Netw Commun. 2012; 2012:1–11.
Cirani S, Davoli L, Ferrari G, Léone R, Medagliani P, Picone M, et al.A scalable and self-configuring architecture for service discovery in the Internet of Things. IEEE Internet of Things J. 2014; 1(5):508–21.
Li J, Zaman N, Li H. A decentralized locality-preserving context-aware service discovery framework for Internet of Things. In: Proceedings of the 2015 IEEE International Conference on Services Computing. USA: IEEE: 2015. p. 317–23.
Hussein D, Park S, Crespi N. A cognitive context-aware approach for adaptives services provisioning in Social Internet of Things. In: Proceedings of the 2015 IEEE International Conference on Consumer Electronics. USA: IEEE: 2015. p. 192–3.
Jo HJ, Kwon JH, Ko IY. Distributed service discovery in mobile IoT environments using Hierarchical Bloom Filters In: Cimiano P, Frasincar F, Houben GJ, Schwabe D, editors. Proceedings of the 15th International Conference on Engineering the Web in the Big Data Era. vol. 9114 of Lecture Notes in Computer Science. Cham, Switzerland: Springer International Publishing: 2015. p. 498–514.
Delicato FC, Pires PF, Batista T. Resource management for the Internet of Things. Cham. Switzerland: Springer International Publishing AG; 2017.
Chun S, Seo S, Oh B, Lee KH. Semantic description, discovery and integration for the Internet of Things. USA: IEEE; 2015, pp. 272–5.
Wang W, De S, Toenjes R, Reetz E, Moessner K. A comprehensive ontology for knowledge representation in the Internet of Things. USA: IEEE; 2012, pp. 1793–8.
Perera C, Zaslavsky A, Christen P, Georgakopoulos D. Context aware computing for the Internet of Things: A survey. IEEE Commun Surv Tutor. 2014; 16(1):414–54.
Henricksen K, Indulska J. Modelling and using imperfect context information. In: Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops. USA: IEEE: 2004. p. 33–37.
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. Geneva: 2003. p. 1–14.
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, editors. Proceedings of the 8th International Conference on Ubiquitous Computing and Ambient Intelligence. vol. 8867 of Lecture Notes in Computer Science. Cham, Switzerland: Springer International Publishing: 2014. p. 224–31.
Chabridon S, Laborde R, Desprats T, Oglaza A, Marie P, Marquez SM. A survey on addressing privacy together with quality of context for context management in the Internet of Things. Annals Telecommun. 2014; 69(1):47–62.
Gomes P, Cavalcante E, Batista T, Taconet C, Chabridon S, Conan D, et al. In: García CR, Caballero-Gil P, Burmester M, Quesada-Arencibia A, (eds).A QoC-aware discovery service for the Internet of Things. Cham, Switzerland: Springer International Publishing; 2016, pp. 344–55.
Gomes P, Cavalcante E, Rodrigues T, Batista T, Delicato FC, Pires PF. A federated discovery service for the Internet of Things. In: Proceedings of the 2nd Workshop on Middleware for Context-Aware Applications in the IoT. New York: ACM: 2015. p. 25–30.
Schmidt C, Parashar M. A peer-to-peer approach to Web service discovery. World Wide Web. 2004; 7(2):211–29.
Brambilla M, Umuhoza E, Acerbis R. Model-driven development of user interfaces for IoT systems via domain-specific components and patterns. J Internet Serv Appl. 2017; 8.
Cabrera C, Palade A, Clarke S. An evaluation of service discovery protocols in the Internet of Things. New York: ACM; 2017, pp. 469–76.
Eugster PT, Felber PA, Guerraoui R, Kermarrec AM. The many faces of publish/subscribe. ACM Comput Surv. 2003; 35(2):114–31.
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. USA: IEEE: 2014. p. 528–34.
Barnaghi P, et al. Semantic Sensor Network XG Final Report. http://www.w3.org/2005/Incubator/ssn/XGR-ssn-20110628/. Accessed Dec 2018.
Chen H, Finin T, Joshi A. The SOUPA ontology for Pervasive Computing In: Tamma V, Cranefield S, Finin TW, Willmott S, editors. Ontologies for agents: Theory and experiences. Whitestein Series in Software Agent Technologies. Birkhäuser Basel: Cham, Switzerland: 2005. p. 233–58.
Martin D, et al. Bringing semantics to Web services: The OWL-S approach In: Cardoso J, Sheth A, editors. Proceedings of the First International Workshop on Semantic Web Services and Web Process Composition. vol. 3387 of Lecture Notes in Computer Science. Germany: Springer Berlin Heidelberg: 2005. p. 26–42.
Marie P, Desprats T, Chabridon S, Sibilla M. The QoCIM Framework: Concepts and tools for Quality of Context management In: Brézillon P, Gonzalez AJ, editors. Context in Computing: A cross-disciplinary approach for modeling the real world. USA: Springer New York: 2014. p. 155–72.
World Wide Web Consortium (W3C). SPARQL Query Language for RDF. https://www.w3.org/TR/sparql11-overview//. Accessed Dec 2018.
Bröring A, Datta SK, Bonnet C. A categorization of discovery technologies for the Internet of Things. In: Proceedings of the 6th International Conference on the Internet of Things. New York: ACM: 2016. p. 131–9.
Apache Software Foundation. Jena: A free and open source Java framework for building Semantic Web and Linked Data applications. https://jena.apache.org/. Accessed Dec 2018.
Apache Software Foundation. Apache Jena Fuseki. https://jena.apache.org/documentation/fuseki2/. Accessed Dec 2018.
Selva A. Moquette MQTT broker. http://moquette.io/. Accessed Dec 2018.
Apache Software Foundation. Apache JMeter. http://jmeter.apache.org/. Accessed Dec 2018.
Coulouris G, Dollimore J, Kindberg T, Blair G. Distributed systems: Concepts and design, 5th ed. Boston: Addison-Wesley/Pearson Education, Inc.; 2012.
Muhammad H. htop - An interactive process viewer for Unix. http://hisham.hm/htop/. Accessed Dec 2018.
Sommer P, Schellroth F, Fischer MT, Schlechtendahl J. Message-oriented middleware for industrial production systems. In: Proceedings of the 14th IEEE International Conference on Automation Science and Engineering. USA: IEEE: 2018. p. 1217–23.
Issarny V, Bouloukakis G, Georgantas N, Billet B. Revisiting Service-Oriented Architecture for the IoT: A middleware perspective In: Sheng QZ, Stroulia E, Tata S, Bhiri S, editors. Proceedings of the 14th International Conference on Service-Oriented Computing. vol. 9936 of Lecture Notes in Computer Science. Cham, Switzerland: Springer International Publishing: 2016. p. 3–17.
Fortino G, Lackovic M, Russo W, Trunfio P. A discovery service for smart objects over an agent-based middleware In: Pathan M, Wei G, Fortino G, editors. Proceedings of the 6th International Conference on Internet and Distributed Computing Systems. vol. 8223 of Lecture Notes in Computer Science. Germany: Springer Berlin Heidelberg: 2013. p. 281–93.
Kamilaris A, Yumusak S, Ali MI. WOTS2E: A search engine for a Semantic Web of Things. In: Proceedings of the 3rd IEEE World Forum on Internet of Things. USA: IEEE: 2016. p. 436–41.
Chirila S, Lemnaru C, Dinsoreanu M. Semantic-based IoT device discovery and recommendation mechanism. In: Proceedings of the 12th International Conference on Intelligent Computer Communication and Processing. USA: IEEE: 2016. p. 111–6.
Vandana CP, Chikkamannur AA. Study of resource discovery trends in Internet of Things (IoT). Int J Adv Netw Appl. 2016; 8(3):3084–9.
Ketema G, Hoebeke J, Moerman I, Demeester P, Tao LS, Jara AJ. Efficiently observing Internet of Things resources. In: Proceedings of the 2012 IEEE International Conference on Green Computing and Communications. USA: IEEE: 2012. p. 446–9.
Perera C, Zaslavsky A, Christen P, Compton M, search GeorgakopoulosD. Context-awaresensor. selection and ranking model for Internet of Things middleware. In: Proceedings of the 14th IEEE International Conference on Mobile Data Management. USA: IEEE: 2013. p. 314–22.
Wang W, Deb S, Cassarc G, Moessner K. An experimental study on geospatial indexing for sensor service discovery. Expert Syst Appl. 2015; 42(7):3528–38.
Fredj SB, Boussard M, Kofman D, Noirie L. Efficient semantic-based IoT service discovery mechanism for dynamic environments. In: Proceedings of the 25th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communication.USA: IEEE: 2014. p. 2088–92.