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Efficient service discovery in decentralized online social networks

机译:分散式在线社交网络中的高效服务发现

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摘要

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.
机译:在过去十年中,在线社交网络(OSN)吸引了全球数百万用户。现有OSN面临着一系列紧急问题,例如信息过载,单点故障和隐私问题。蓬勃发展的物联网(IoT)和云计算为去中心化OSN的开发提供了范例。在本文中,我们在类似于现实社会图的物联网基础设施的覆盖网络上构建了自组织的去中心化OSN(SDOSN)。提出了一种基于同质特征的用户模型,该模型考虑了社会关系和用户兴趣,并着重于有效信息分发的关键OSN功能。还提出了一种群体智能搜索方法,以促进自适应转发和有效的服务发现。我们使用真实的数据集在仿真中进行的评估显示,与动态网络环境中的最新方法相比,我们的方法具有更好的性能。

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