一种新的用于内容传递的web缓存策略

G. Haßlinger, K. Ntougias, Frank Hasslinger
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引用次数: 10

摘要

最近最少使用(Least recently used, LRU)是最常用的策略,用于更新计算和数据库系统以及Web缓存中的缓存内容。尽管一些案例研究表明,与能够了解过去请求的完整统计数据的Web缓存策略相比,LRU的命中率可能较低,但所提出的替代方案似乎过于复杂,无法应对LRU不断更新的工作。在这项工作中,我们首先评估了LRU的命中率,并将其与基于统计的Zipf分布式网络内容流行度缓存策略进行了比较,Zipf分布式网络内容流行度缓存策略已被广泛证实为互联网上内容的相关访问配置文件。我们得出结论,LRU在Zipf定律访问模式的整个相关参数范围内,不仅在某些特殊情况下存在超过10%的绝对命中率缺陷。我们表明,通过评分LRU的变体已经实现了比LRU命中率增加10%的增益,其平均更新工作量与纯LRU相当。作为另一个主要优势,计分LRU避免了纯LRU策略的大部分输入流量,因为纯LRU策略经常将对象重新加载到缓存中。分数门控LRU在流行度不变的情况下保持缓存内容稳定,只有当新对象的分数增加直到超过缓存对象的分数时才加载新对象。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new class of web caching strategies for content delivery
Least recently used (LRU) is the most commonly applied strategy to update the content of caches in computing and database systems as well as for Web caching. Although some case studies have shown that LRU hit rates can be low when compared to Web caching strategies being aware of complete statistics of past requests, proposed alternatives seem too complex to cope with constant update effort of LRU. In this work we start with an evaluation of the hit rates for LRU as compared to statistic-based caching strategies for Zipf distributed popularity of web content, which has been confirmed manifold as the relevant access profile to content on the Internet. We conclude that LRU has more than 10% absolute hit rate deficits not only in some special cases but over the entire relevant parameter range of Zipf law access pattern. We show that a 10% gain over LRU hit rates is already realized by the variant of score-gated LRU, whose mean updating effort is comparable to pure LRU. As another main advantage, score-gated LRU avoids most of the input traffic of a pure LRU strategy, which frequently reloads objects into the cache. Score-gated LRU keeps the cache content stable in case of unchanged popularity and loads new objects only when their score is increasing until it exceeds the score of a cached object.
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