Shared dictionary compression in publish/subscribe systems

Christoph Doblander, Tanuj Ghinaiya, Kaiwen Zhang, H. Jacobsen
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引用次数: 12

Abstract

Publish/subscribe is known as a scalable and efficient data dissemination mechanism. Its efficiency comes from the optimized routing algorithms, yet few works exist on employing compression to save bandwidth, which is especially important in mobile environments. State of the art compression methods such as GZip or Deflate can be generally employed to compress messages. In this paper, we show how to reduce bandwidth even further by employing Shared Dictionary Compression (SDC) in pub/sub. However, SDC requires a dictionary to be generated and disseminated prior to compression, which introduces additional computational and bandwidth overhead. To support SDC, we propose a novel and lightweight protocol for pub/sub which employs a new class of brokers, called sampling brokers. Our solution generates, and disseminates dictionaries using the sampling brokers. Dictionary maintenance is performed regularly using an adaptive algorithm. The evaluation of our proposed design shows that it is possible to compensate for the introduced overhead and achieve significant bandwidth reduction over Deflate.
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发布/订阅系统中的共享字典压缩
发布/订阅是一种可伸缩且高效的数据传播机制。它的效率主要来自于优化的路由算法,但利用压缩来节省带宽的研究很少,这在移动环境中尤为重要。通常可以使用最先进的压缩方法,如GZip或Deflate来压缩消息。在本文中,我们展示了如何通过在pub/sub中使用共享字典压缩(SDC)进一步减少带宽。然而,SDC需要在压缩之前生成和分发字典,这会带来额外的计算和带宽开销。为了支持SDC,我们提出了一种新颖的轻量级pub/sub协议,该协议采用了一类新的代理,称为采样代理。我们的解决方案使用抽样代理生成和传播字典。字典维护使用自适应算法定期执行。对我们提出的设计的评估表明,它可以补偿引入的开销,并在Deflate上实现显著的带宽减少。
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