Efficient service discovery in decentralized online social networks.
|Authors||Yuan, Bo, Liu, Lu and Antonopoulos, Nikolaos|
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.
|Keywords||Service discovery; Social networks; Peer-to-peer networks; Swarm intelligence|
|Journal||Future Generation Computer Systems|
|Digital Object Identifier (DOI)||https://doi.org/10.1016/j.future.2017.04.022|
|Web address (URL)||http://hdl.handle.net/10545/622072|
|Publication dates||19 May 2017|
|Publication process dates|
|Deposited||22 Jan 2018, 15:44|
|Contributors||Tongji University and University of Derby|
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