Efficient service discovery in decentralized online social networks
Bo Yuan, Lu Liu, Nick Antonopoulos · 2016
Online social networks (OSNs) have attracted millions of users worldwide over the last decade. In response to a series of urgent issues faced by existing OSNs, such as information overload, single-point failure, and the privacy issue, this paper introduces a self-organized decentralized OSN (SDOSN) over a social overlay resembling real-life social graph. The social overlay considers social relationship and semantic content of users and focuses on the key OSNs functionality of efficient information dissemination and service discovery. Then a swarm intelligence search method is proposed to facilitate adaptive learning and effective service discovery in decentralized environments. Our evaluation, performed in simulation over a real-world dataset, shows that the proposed approach achieves better performance comparing with the state-of-the-art methods on different network structures.