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A Self-Organized Architecture for Efficient Service Discovery in Future Peer-to-Peer Online Social Networks

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conference contribution
posted on 2024-04-22, 09:50 authored by Bo Yuan, Lu Liu, Nick Antonopoulos

With the unprecedented growing information services in online social networks (OSNs), Internet users are increasingly struggling to keep pace with the sheer volume of massively unstructured social data being created online through information services on a daily base. However, most of OSNs are based on centralized client-server architecture which can easily suffer from problems such as performance bottleneck and vulnerability to the single point of failure in large-scale networks. Moreover, all the data and services are stored in the service providers' data center, users could lose control of their privacy and ownership of their own data. This visionary paper is to propose a novel self-organized architecture and supporting mechanisms for efficient service discovery in next-generation peer-to-peer (P2P) online social networks which enables dynamic interaction, collaboration, social information sharing and discovering and improve the scalability, availability and efficiency of current centralized OSNs. In the architecture, users have more control over their own private information and have better access to the social network services online and offline.

Funding

National Natural Science Foundation of China under Grants No.61502209and No.61502207, the Natural Science Foundation of Jiangsu Province under Grant No.BK20130528, China Postdoctoral Science Foundation(2015M580396) and Jiangsu Planned Projects for Postdoctoral Research Funds(1501023A

History

Author affiliation

College of Science & Engineering/Comp' & Math' Sciences

Source

2016 IEEE Symposium on Service-Oriented System Engineering (SOSE)

Version

  • AM (Accepted Manuscript)

Published in

2016 IEEE Symposium on Service-Oriented System Engineering (SOSE)

Pagination

415 - 422

Publisher

IEEE

isbn

9781509022533

Copyright date

2016

Available date

2024-04-22

Spatial coverage

Oxford, ENGLAND

Temporal coverage: start date

2016-03-29

Temporal coverage: end date

2016-04-02

Language

en

Deposited by

Professor Lu Liu

Deposit date

2024-04-21

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