3-D-SIS : A 3-D-Social Identifier Structure for Collaborative Edge Computing Based Social IoT
Muhammad Ibrar, Lei Wang, Aamir Akbar, Mian Ahmad Jan, Nadir Shah, Shahbaz Akhtar Abid, Michael Segal · IEEE Transactions on Computational Social Systems · 2021
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 calledsocial and spatial physical trade-off. This problem is also referred to as themismatchproblem, 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(3-D-SIS)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(3-D-SIS)model, we use the real traces of social networks(INFOCOM06). 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.