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Mignon: A Fast Decentralized Content Consumption Estimation in Large-Scale Distributed Systems

机译:Mignon:大型分布式系统中的快速分散式内容消耗估计

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摘要

Although many fully decentralized content distribution systems have been proposed, they often lack key capabilities that make them difficult to deploy and use in practice. In this paper, we look at the particular problem of content consumption prediction, a crucial mechanism in many such systems. We propose a novel, fully decentralized protocol that uses the tags attached by users to on-line content, and exploits the properties of self-organizing kNN overlays to rapidly estimate the potential of a particular content without explicit aggregation.
机译:尽管已经提出了许多完全分散的内容分发系统,但是它们通常缺少关键功能,这使其很难在实践中部署和使用。在本文中,我们着眼于内容消耗预测的特殊问题,这是许多此类系统中的关键机制。我们提出了一种新颖的,完全分散的协议,该协议使用用户附加到在线内容的标签,并利用自组织kNN叠加层的属性来快速估计特定内容的潜力,而无需进行显式聚合。

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