Efficient service discovery in decentralized online social networks

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.

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