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Were You There? Bridging the Gap to Unveil Users' Online Sessions in Networked, Distributed Systems

机译:你在吗? 在网络,分布式系统中缩小缩写揭示用户在线会话

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The comprehension of users' behavior is paramount for evaluating improvements to networked, distributed systems. To this end, several strategies have been proposed to obtain traces, based on the capture of usage information, which can then serve for evaluation purposes. One main strategy consists of taking snapshots of online users, using instrumented clients. In spite of its popularity, related proposals have fallen short in ensuring accuracy of obtained data. For a variety of reasons, users may fail to appear in some snapshots, although online. In this paper, we propose a methodology to correct ill-collected snapshots and build more accurate traces from them. In summary, we estimate the probability that a given snapshot is missing some users. The snapshot is corrected if the probability exceeds a given threshold. We use ground-truth data to assess the effectiveness of our methodology. The impact of our proposal is evidenced by means of an analysis of traces from a BitTorrent swarm.
机译:对用户行为的理解是评估对网络,分布式系统的改进的方式。 为此,提出了基于捕获使用信息的捕获来获得迹线的几种策略,然后可以用于评估目的。 一个主要策略包括使用仪器客户端拍摄在线用户的快照。 尽管其受欢迎程度,相关提案在确保获得数据的准确性方面已经简短。 出于各种原因,用户可能无法出现在某些快照中,虽然在线。 在本文中,我们提出了一种方法来纠正收集的快照并从中构建更准确的痕迹。 总之,我们估计给定快照缺少一些用户的概率。 如果概率超过给定阈值,则纠正快照。 我们使用地面真实数据来评估我们方法的有效性。 我们提案的影响通过分析来自BitTorrent群的痕迹来证明。

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