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A 3-D-Social Identifier Structure for Collaborative Edge Computing Based Social IoT

Bibliographic Data

ID22106985
AuthorsMuhammad Ibrar (0000-0002-3488-2967, Dalian University of Technology), Lei Wang (0000-0001-5326-565X, Dalian University of Technology), Aamir Akbar (0000-0002-9421-7379, Abdul Wali Khan University Mardan), Mian Ahmad Jan (0000-0001-5326-8279, Abdul Wali Khan University Mardan), Nadir Shah (0000-0003-1173-4272, COMSATS University Islamabad), Shahbaz Akhtar Abid (0000-0002-3558-470X, COMSATS University Islamabad), Michael Segal (0000-0001-7606-6522, Ben-Gurion University of the Negev)
Year2022
Volume9
Issue1
Pages313-323
Publication date2022-02-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueIEEE Transactions on Computational Social Systems (JOURNAL)
Journal identifiersISSN: 2329-924X • E-ISSN: 2373-7476
PublisherInstitute of Electrical and Electronics Engineers (IEEE) (PUBLISHER)
DOI10.1109/tcss.2021.3064716
OpenAlexW3136299196
LanguageEN
Citations received2
References cited32

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 social and spatial physical trade-off . This problem is also referred to as the mismatch 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 (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

Computer network · Identifier · Computer Science · IoT and Edge/Fog Computing · Mobile Crowdsensing and Crowdsourcing · Opportunistic and Delay-Tolerant Networks · Artificial Intelligence · Theoretical Computer Science

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Unique citing works2
Citations per year1
Citation span2024 - 2024 (1)
Citation velocityrecent
Highly citedNo
Citation typesNeutral: 2

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