基于类的增量编码:用于缓存动态Web内容的可伸缩方案

K. Psounis
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引用次数: 18

摘要

由于不可缓存的动态web文档的数量不断增加,web缓存性能很难进一步提高。增量编码是一种很有前途的技术,它利用动态文档的不同快照之间的时间相关性,并使动态流量可缓存。但是,由于与服务器端基本文件的存储需求相关的重大可伸缩性问题,它尚未部署。我们介绍了基于类的增量编码,这是一种可扩展的对动态web流量进行增量编码的方案。其思想是将文档分组为类,并在服务器端为每个类存储一个文档。因此,该方案既利用了动态发展文档中的时间相关性,又利用了不同文档之间的空间相关性。最后,我们提出了一个架构来部署该方案,该架构对客户端、代理缓存和web服务器是透明的。实验结果表明,基于类的增量编码与压缩相结合,可以将带宽消耗减少30倍,将大多数用户感知到的延迟平均减少10倍,而不会对服务器端产生巨大的存储需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Class-based delta-encoding: a scalable scheme for caching dynamic Web content
Web-caching performance is hard to increase further due to the growing number of non-cachable dynamic Web-documents. Delta-encoding is a promising technique that exploits temporal correlation among different snapshots of a dynamic document, and renders dynamic traffic cachable. However, it has not yet been deployed due to the significant scalability concerns related to the storage requirements for base-files on the server-side. We introduce class-based delta-encoding, a scalable scheme to perform delta-encoding on dynamic Web-traffic. The idea is to group documents into classes, and store one document per class on the server-side. Thus, the proposed scheme exploits both temporal correlation in a dynamically evolving document, and spatial correlation among different documents. Finally, we present an architecture to deploy the scheme, that is transparent to clients, proxy-caches, and Web-servers. Experimental results report that class-based delta-encoding combined with compression reduces the bandwidth consumption by a factor of 30, and the latency perceived by most users by a factor of 10 on average, without suffering from enormous storage requirements on the server-side.
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