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Efficient service discovery in mobile social networks for smart cities

journal contribution
posted on 26.06.2020, 15:02 by Yonghong Guo, Lu Liu, John Panneerselvam, Rongbo Zhu
Mobile social networks (MSNs) play an important role in the process of the development of smart cities. Citizens can interact and engage with services provided by MSNs. Smart city services enhance their quality of life. With the popularity of smart phones, mobile social activities have become an important component of citizens’ daily life. People can post their social contents to their remote friends and can access shared information in the cycles of friends anytime and anywhere through their mobile devices. This human-centered social approach generates enormous amounts of social data that are distributed across various smart devices. Efficient service discovery from such cycles of friends is a fundamental challenge for MSNs. This paper proposes a friends’ cycle service discovery (FCSD) model for searching social services in MSNs based on human sociological theories and social strategies. In the proposed FCSD network, intelligent network nodes with common social interests can self-organize to interact and form social cycles with other potential nodes, and further can co-operate autonomously to identify and discover useful services from cycles of friends and cycles of friends’ friends. The proposed model has been simulated and evaluated in a decentralized mobile social environment with an evolving network. The experimental results show that the FCSD model exhibits better performance compared with relevant state-of-the-art services search methods.

Funding

This work was partially supported by the Natural Science Foundation of Jiangsu Province under Grant BK20170069, UK-Jiangsu 20-20 World Class University Initiative programme, UK-Jiangsu 20-20 Initiative Pump Priming Grant, and Chang Zhou College of Information Technology Overseas Research & Training Program for Prominent Teachers under Grant CCITFX201801.

History

Citation

Computing (2020). https://doi.org/10.1007/s00607-020-00824-7

Author affiliation

School of Informatics

Version

AM (Accepted Manuscript)

Published in

Computing

Publisher

Springer

issn

0010-485X

eissn

1436-5057

Acceptance date

29/05/2020

Copyright date

2020

Available date

10/06/2021

Language

English

Publisher version

https://link.springer.com/article/10.1007/s00607-020-00824-7

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