Society is moving towards an “always connected” paradigm, where the Internet user is shifting from persons to things, leading to the so called Internet of Things (IoT) scenario. The IoT vision integrates a large number of technologies and foresees to embody a variety of smart objects around us (such as sensors, actuators, smartphones, RFID, etc.) that, through unique addressing schemes and standard communication protocols, are able to interact with each Others and cooperate with their neighbors to reach common goals [2, 3]. IoT is a hot research topic, as
demonstrated by the increasing attention and the large worldwide investments devoted to it.
It is believed that the IoT will be composed of trillions of elements interacting in an extremely heterogeneous way in terms of requirements, behavior and capabilities; according to [4], by 2015 the RIFD devices alone will reach hundreds of billions. Unquestionably, the
IoT will pervade every aspect of our world and will have a huge impact in our everyday life: indeed, as stated by the US National Intelligence Council (NIC) [5], “by 2025 Internet nodes may reside in everyday things − food packages, furniture, paper documents, and more”.
Then, communications will not only involve persons but also things thus bringing about the IoT environment in which objects will have virtual counterparts on the Internet. Such virtual entities will produce and consume services, collaborate toward common goals and should be
integrated with all the other services.
One of the biggest challenges that the research community is facing right now is to be able to organize such an ocean of devices so that the discovery of objects and services is performed efficiently and in a scalable way. Recently, several attempts have been made to apply concepts
of social networking to the IoT. There are scientific evidences that a large number of individuals tied in a social network can provide far more accurate answers to complex problems than a single individual (or a small group of – even knowledgeable – individuals) [1]. The exploitation of such a principle, applied
to smart objects, has been widely investigated in Internet-related researches. Indeed, several
schemes have been proposed that use social networks to search Internet resources, to route
traffic, or to select effective policies for content distribution. The idea that the convergence of the “Internet of Things” and the “Social Networks”
worlds, which up to now were mostly kept separate by both scientific and industrial communities, is possible or even advisable is gaining momentum very quickly. This is due to the growing awareness that a “Social Internet of Things” (SIoT) paradigm carries with it many desirable
implications in a future world populated by objects permeating the everyday life of human beings.
Therefore, the goal of this thesis is to define a possible architecture for the SIoT, which includes the functionalities required to integrate things into a social network, and the needed strategies to help things to create their relationships in such a way that the resulting social network is navigable. Moreover, it focuses on the trustworthiness management, so that interaction
among objects that are friends can be done in a more reliable way and proposes a possible
implementation of a SIoT network. Since this thesis covers several aspects of the Social internet of Things, I will present the state of the art related to the specific research activities at the beginning of every Chapter. The
rest of the thesis is structured as follows.
In Chapter 1, I identify appropriate policies for the establishment and the management of social relationships between objects, describe a possible architecture for the IoT that includes the functionalities required to integrate things into a social network and analyze the characteristics
of the SIoT network structure by means of simulations.
Chapter 2 addresses the problem of the objects to manage a large number of friends, by analyzing possible strategies to drive the objects to select the appropriate links for the benefit of overall network navigability and to speed up the search of the services.
In Chapter 3, I focus on the problem of understanding how the information provided by members of the social IoT has to be processed so as to build a reliable system on the basis of the behavior of the objects and define two models for trustworthiness management starting from
the solutions proposed for P2P and social networks.
Chapter 4 presents an implementation of a SIoT platform and its major functionalities: how to register a new social object to the platform, how the system manages the creation of new relationships, and how the devices create groups of members with similar characteristics.
Finally, in Chapter 5, conclusions will be drawn regarding the effectiveness of the proposed
Introduction 3 algorithms, and some possible future works will be sketche
