Abstract

The social Internet of Things (IoT) (SIoT) helps to enable an autonomous interaction between the two architectures that have already been established: social networks and the IoT. SIoT also integrates the concepts of social networking and IoT into collaborative edge computing (CEC), the so-called CEC-based SIoT architecture. In closer proximity, IoT devices self-organize into a CEC-based SIoT computing cluster and provide social device-to-device (S-D2D) services, such as computation offloading, service discovery, and content delivery. In the CEC-based SIoT, however, cooperation based on social connections leads to a problem called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">social and spatial physical trade-off</i> . This problem is also referred to as the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">mismatch</i> problem, which arises because the spatial neighbors in the social layer cannot always be related. The spatial distance thus calls for additional multi-hop transmissions. This work presents a novel solution called 3-D-social identifier structure <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(3-D-SIS)</i> model. The 3-D-SIS model is based on 3-D social space (3-D-SS) and considers social ties and physical connections (i.e., intra-neighbor) of the SIoT devices and utilizes a 3-D structure to evaluate that relationship. Moreover, it minimizes the end-to-end delay and communication cost to address the mismatch problem. To validate the performance of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(3-D-SIS)</i> model, we use the real traces of social networks <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">(INFOCOM06)</i> . The results show that the 3-D-SIS selects the best neighbor in S-D2D communication and improves performance in terms of end-to-end delay and throughput.

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