Abstract
The Internet of Things (IoT) is currently considered the new frontier of the Internet, and a lot of research results about this topic can be found in the literature. One of the most effective ways to investigate and implement IoT is based on the use of the social network paradigm: Social Internet of Things (SIoT) is an excellent attempt in this direction. In the last years, social network researchers have introduced new paradigms capable of capturing the growing complexity of this scenario. One of the most known of them is Social Internetworking System, which models a scenario comprising several related social networks. In this paper, we investigate the possibility of applying the ideas underlying Social Internetworking System to IoT, and we propose a new paradigm, called MIoT (Multiple Internets of Things), capable of modeling and handling the increasing complexity of this last context. Furthermore, in order to facilitate knowledge extraction and exploitation in presence of a huge number of things, we also propose a crawler specifically designed for an MIoT. Finally, through an experimental campaign, we show that classical crawlers are not adequate for MIoTs, whereas our own is well suited and outperforms all of them in this context.
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