Efficient service discovery in decentralized online social networks

Yuan, Bo; Liu, Lu; Antonopoulos, Nick

Abstract

Online social networks (OSN) have attracted millions of users worldwide over the last decade. There are a series of urgent issues faced by existing OSN such as information overload, single-point of failure and privacy concerns. The booming Internet of Things (IoT) and Cloud Computing provide paradigms for the development of decentralized OSN. In this paper, we build a self-organized decentralized OSN (SDOSN) on the overlay network of an IoT infrastructure resembling real life social graph. A user model based on homophily features is proposed considering social relationships and user interests and focuses on the key OSN functionality of efficient information dissemination. A swarm intelligence search method is also proposed to facilitate adaptive forwarding and effective service discovery. Our evaluation, performed in simulation using real-world datasets, shows that our approach achieves better performance when compared with the state-of-the-art methods in a dynamic network environment.

Citation

Yuan, B., Liu, L., & Antonopoulos, N. (2018). Efficient service discovery in decentralized online social networks. Future Generation Computer Systems, 86, 775-791. https://doi.org/10.1016/j.future.2017.04.022

• Journal Article Type: Article
• Acceptance Date: Apr 13, 2017
• Online Publication Date: May 19, 2017
• Publication Date: 2018-09
• Deposit Date: Feb 12, 2019
• Journal: Future Generation Computer Systems
• Print ISSN: 0167-739X
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 86
• Pages: 775-791
• DOI: https://doi.org/10.1016/j.future.2017.04.022
• Keywords: Service discovery, decentralized online social networks, Peer-to-Peer, Swarm intelligence
• Public URL: http://researchrepository.napier.ac.uk/Output/1557227