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Preserving Consistency of Dynamic Data in Peer-Based Caching Systems

机译:在基于对等的缓存系统中保持动态数据的一致性

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On-line decision making often involves significant amount of time-varying data, which can be regarded as dynamic data. Maintaining dynamic data consistency in existing P2P systems is often inefficient. Most of the previous P2P research works are predominantly remaining at the static files management. In this paper, we focus on the problem of maintaining consistency of dynamic data items in an overlay network of cooperating peers. We present CC-Buddy, an adaptive framework for efficiently disseminating dynamic data in P2P environments. Our approach combines application-level multicasting and demand-driven dissemination filtering techniques. We evaluate CC-Buddy with a prototype system built on top of BestPeer infrastructure. We examine our approach using real-world traces of dynamically changing data items. The results show our techniques can efficiently satisfy the consistency requirements by different users.
机译:在线决策通常涉及大量随时间变化的数据,这些数据可以被视为动态数据。在现有的P2P系统中维持动态数据一致性通常效率不高。以前的大多数P2P研究工作主要保留在静态文件管理中。在本文中,我们关注于在合作伙伴的覆盖网络中保持动态数据项一致性的问题。我们介绍CC-Buddy,这是一种用于在P2P环境中有效分发动态数据的自适应框架。我们的方法结合了应用程序级多播和需求驱动的传播过滤技术。我们使用建立在BestPeer基础架构之上的原型系统评估CC-Buddy。我们使用动态变化的数据项的真实记录来检查我们的方法。结果表明,我们的技术可以有效地满足不同用户的一致性要求。

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