The cluster between Internet of Things (IoT) and Social Networks (SN) enables the connection of people to the ubiquitous computing universe. In this framework, the information coming from the environment is provided by the IoT, and the SN brings the glue to allow human-to-device interactions. This article explores the novel paradigm for ubiquitous computing beyond IoT, denoted by Social Internet of Things (SIoT). Although there have been early-stage studies in social-driven IoT, they merely use one or some properties of SIoT to improve a number of specific performance variables. Therefore, this article first addresses a complete view on SIoT and key perspectives to envision the real ubiquitous computing. Thereafter, a literature review is presented along with the evolutionary history of IoT research from Intranet of Things to SIoT. Finally, this article proposes a generic SIoT architecture, and presents a discussion about enabling technologies, research challenges, and open issues.
International audienceService-oriented architecture (SOA) is realized by independent, standardized, and self-describing units known as services. This architecture has been widely used and verified for automatic, dynamic, and self-configuring distributed systems such as in building automation. This paper presents a building automation system adopting SOA paradigm with devices implemented by device profile for web service (DPWS) in which context information is collected, processed, and sent to a composition engine to coordinate appropriate devices/services based on the context, composition plan, and predefined policy rules. A six-phased composition process is proposed to carry out the task. In addition, two other components are designed to support the composition process: building ontology as a schema for representing semantic data and composition plan description language to describe context-based composite services in form of composition plans. A prototype consisting of a DPWSim simulator and SamBAS is developed to illustrate and test the proposed idea. Comparison analysis and experimental results imply the feasibility and scalability of the system
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