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A content-based publish/subscribe framework for large-scale content delivery

机译:基于内容的发布/订阅框架,用于大规模内容交付

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摘要

The publish/subscribe communication paradigm has become an important architectural style for designing distributed systems and has recently been considered one of the most promising future network architectures that solves many challenges of content delivery in the current Internet. This work is concerned with scaling decentralized content-based publish/subscribe (CBPS) networks for large-scale content distribution. A fundamental step for CBPS networks to reach the large-scale is to move from the current 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. Moreover, the proposed work aims at leveraging caching for increasing the communication efficiency of CBPS operating at large-scale characterized by widely spread information consumers with heterogeneous requirements, large number of publications and scarcity of end-to-end bandwidth. We propose and design a service model for addressing the consumers' requirements for content-based information retrieval and describe the relevant protocols necessary to implement such a service. We evaluate the proposed approach, by using realistic workload scenarios and comparing different content and interest forwarding strategies as well as caching policies in terms of resource efficiency and user perceived QoS metrics.
机译:发布/订阅通信范例已成为设计分布式系统的重要体系结构样式,并且最近被认为是解决当前Internet内容交付挑战的最有前途的未来网络体系结构之一。这项工作与扩展用于大型内容分发的分散式基于内容的发布/订阅(CBPS)网络有关。 CBPS网络要达到大规模的基本步骤是,从当前的穷举过滤服务模型(其中订阅会选择每个相关出版物),过渡到捕获信息消费者需求的定量和定性异质性的服务模型。此外,拟议的工作旨在利用缓存来提高大规模运行的CBPS的通信效率,其特点是信息消费者广泛散布,具有异构的需求,大量的出版物和端到端带宽的匮乏。我们提出并设计了一种服务模型,以解决消费者对基于内容的信息检索的需求,并描述实现这种服务所必需的相关协议。我们通过使用实际的工作负载方案并在资源效率和用户感知的QoS指标方面比较不同的内容和兴趣转发策略以及缓存策略,来评估所提出的方法。

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