Research Output
Efficient service discovery in decentralized online social networks
  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.

  • Type:

    Article

  • Date:

    19 May 2017

  • Publication Status:

    Published

  • Publisher

    Elsevier

  • DOI:

    10.1016/j.future.2017.04.022

  • Cross Ref:

    S0167739X17306465

  • ISSN:

    0167-739X

  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    004 Data processing & computer science

  • Funders:

    Historic Funder (pre-Worktribe); National Natural Science Foundation of China; UK–China Knowledge Economy Education Partnership

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

Authors

Keywords

Service discovery, decentralized online social networks, Peer-to-Peer, Swarm intelligence

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