%0 Journal Article %A Guo, Yonghong %A Liu, Lu %A Panneerselvam, John %A Zhu, Rongbo %D 2020 %T Efficient service discovery in mobile social networks for smart cities %U https://figshare.le.ac.uk/articles/journal_contribution/Efficient_service_discovery_in_mobile_social_networks_for_smart_cities/12562280 %2 https://figshare.le.ac.uk/ndownloader/files/23419670 %K Science & Technology %K Technology %K Computer Science, Theory & Methods %K Computer Science %K Smart cities %K Smart services %K Mobile social networks %K Self-organization %K Decentralization %K TERM-MEMORY %K KNOWLEDGE %K DYNAMICS %K SEARCH %X 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. %I University of Leicester