Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3006299.3006338 | Future Generation Comp. Syst. |
Keywords | DocType | Volume |
Service discovery,Decentralized online social networks,Peer-to-Peer,Swarm intelligence | Journal | 86 |
ISSN | ISBN | Citations |
0167-739X | 978-1-5090-4468-9 | 5 |
PageRank | References | Authors |
0.44 | 24 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuan Bo | 1 | 32 | 4.24 |
| Lu Liu | 2 | 134 | 25.39 |
| Nick Antonopoulos | 3 | 531 | 48.72 |