Loughborough University
Adaptive and Context-aware Service Discovery for the Internet of Things.pdf (308.12 kB)

Adaptive and context-aware service discovery for the Internet of Things

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posted on 2013-11-01, 14:50 authored by Talal A. Butt, Lin GuanLin Guan, Iain PhillipsIain Phillips, George Oikonomou
The Internet of Things (IoT) vision foresees a future Internet encompassing the realm of smart physical objects, which offer hosted functionality as services. The role of service discovery is crucial when providing application-level, end-to-end integration. In this paper, we propose trendy: a RESTful web services based Service Discovery protocol to tackle the challenges posed by constrained domains while offering the required interoperability. It provides a service selection technique to offer the appropriate service to the user application depending on the available context information of user and services. Furthermore, it employs a demand-based adaptive timer and caching mechanism to reduce the communication overhead and to decrease the service invocation delay. trendy’s grouping technique creates location-based teams of nodes to offer service composition. Our simulation results show that the employed techniques reduce the control packet overhead, service invocation delay and energy consumption. In addition, the grouping technique provides the foundation for group-based service mash-ups and localises control traffic to improve scalability.



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  • Computer Science


BUTT, T.A. ... et al., 2013. Adaptive and context-aware service discovery for the Internet of Things. IN: Balandin, S. et al. (Eds.) Internet of Things, Smart Spaces, and Next Generation Networking: Proceedings of the 13th International Conference, NEW2AN 2013 and 6th Conference, ruSMART 2013, St. Petersburg, Russia, August 28-30, 2013, Lecture Notes in Computer Science 8121, pp. 36–47.


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This article was published in Lecture Notes in Computer Science [© Springer Verlag] and the definitive version is available at: http://dx.doi.org/10.1007/978-3-642-40316-3_4



Book series

Lecture Notes in Computer Science;8121


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