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Leveraging caching for Internet-scale content-based publish/subscribe networks

机译:利用基于互联网级内容的发布/订阅网络的缓存

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This work is concerned with scaling decentralized content-based publish/subscribe (CBPS) networks for Internet-wide content distribution. A fundamental step for CBPS networks to reach the Internet-scale is to move from the exhaustive filtering service model, where a subscription selects every relevant publication, to a service model capturing the quantitative and qualitative heterogeneity of information consumers' requirements. In previous work [1], we described a service model allowing information consumers to express the maximum number of publications they would like to receive per service period and how to take advantage of such knowledge to pace the dissemination process. This paper extends [1] by introducing a generic service model that seamlessly supports content-based information retrieval and dissemination and investigates through extensive simulations the performances of six caching policies in terms of consumers satisfaction and bandwidth usage.
机译:这项工作涉及扩展分散的基于内容的发布/订阅(CBPS)网络,用于Internet-Internet-ide-ide内容分发。 CBPS网络到达Internet级的基本步骤是从穷举过滤服务模型移动,其中订阅选择每个相关的发布,以捕获信息消费者要求的定量和定性异质性的服务模型。在以前的工作[1]中,我们描述了一种服务模型,允许信息消费者表达每次服务期间的最大出版物数量以及如何利用这些知识来加速传播过程。本文通过引入一种通用服务模型来扩展[1],该模型无缝地支持基于内容的信息检索和传播,并通过广泛的模拟来调查六个缓存政策的性能满意度和带宽使用。

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