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Design and performance evaluation of ContentPlace, a social-aware data dissemination system for opportunistic networks

机译:ContentPlace的设计和性能评估,ContentPlace是机会网络的社交感知数据分发系统

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In this paper we present and evaluate ContentPlace, a data dissemination system for opportunistic networks, i.e., mobile networks in which stable simultaneous multi-hop paths between communication endpoints cannot be provided. We consider a scenario in which users both produce and consume data objects. ContentPlace takes care of moving and replicating data objects in the network such that interested users receive them despite possible long disconnections, partitions, etc. Thanks to ContentPlace, data producers and consumers are completely decoupled, and might be never connected to the network at the same point in time. The key feature of ContentPlace is learning and exploiting information about the social behaviour of the users to drive the data dissemination process. This allows ContentPlace to be more efficient both in terms of data delivery and in terms of resource usage with respect to reference alternative solutions. The performance of ContentPlace is thoroughly investigated both through simulation and analytical models.
机译:在本文中,我们介绍并评估ContentPlace,这是一种用于机会网络(即移动网络)的数据分发系统,在该系统中无法提供通信端点之间的稳定的同时多跳路径。我们考虑用户同时产生和消费数据对象的情况。 ContentPlace负责在网络中移动和复制数据对象,以便有兴趣的用户尽管长时间断开连接,进行分区等也可以接收它们。多亏了ContentPlace,数据生产者和使用者完全脱钩了,可能永远不会同时连接到网络时间点。 ContentPlace的关键功能是学习和利用有关用户社交行为的信息,以驱动数据分发过程。与参考替代解决方案相比,这使ContentPlace在数据传递和资源使用方面都更加高效。通过仿真和分析模型对ContentPlace的性能进行了彻底的研究。

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