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Multi-graph regularization for efficient delivery of user generated content in online social networks

机译:多图正则化,可有效交付在线社交网络中用户生成的内容

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摘要

We present a methodology for enhancing the delivery of user-generated content in online social networks. To this end, we first regularize the social graph via node capacity and link cost information associated with the underlying data network. We then design a technique for constructing the most efficient delivery tree over the regularized social graph. Finally, we derive an optimization algorithm for allocating the nodes' uplink capacities over the content distribution tree. Our system substantially outperforms the conventional method of flooding data over the social graph, over multiple criteria. In particular, a 100% reduction in terms of network cost and data delivery delay is registered.
机译:我们提出了一种用于增强在线社交网络中用户生成的内容的传递的方法。为此,我们首先通过节点容量和与基础数据网络关联的链接成本信息对社交图进行正则化。然后,我们设计一种在正则化社交图上构造最有效的传递树的技术。最后,我们推导了一种优化算法,用于在内容分发树上分配节点的上行链路容量。我们的系统大大优于传统方法,即在多个条件下通过社交图泛洪数据。特别地,在网络成本和数据传送延迟方面减少了100%。

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