首页> 外文期刊>Operations Research: The Journal of the Operations Research Society of America >Analysis of a least recently used cache management policy for web browsers
【24h】

Analysis of a least recently used cache management policy for web browsers

机译:分析用于Web浏览器的最近最少使用的缓存管理策略

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

Experience shows that document caching by a web browser is a cheap and effective way to improve the performance of the World Wide Web. This study analyzes a LRU (Least Recently Used) policy for cache management in a web browser. In this policy, the cache is filled with documents based upon a document's "age," defined as the time elapsed since the document was last accessed. The user's preference for a document is modeled as a general function that declines with the document's age. Two popular measures-the expected delay per document access, and the hit-ratio- are used to evaluate the LRU policy. Unlike many previous studies that evaluate caching policies using simulation methods, this study derives analytical expressions to evaluate performance. The study also presents an approximate, easy-to-compute method to evaluate performance. Numerical tests show this approximation to be extremely accurate. A variety of other numerical results are presented that help describe the behavior of the LRU policy under different situations (e.g., when the documents need to be updated periodically). We also compare the LRU policy with other caching policies (both static and dynamic) for small problems. Our comparison suggests that finding a good caching policy that is conscious of document size and delay may be difficult. [References: 30]
机译:经验表明,通过Web浏览器进行文档缓存是一种提高万维网性能的廉价有效方法。本研究分析了用于Web浏览器中的缓存管理的LRU(最近最少使用)策略。在此策略中,基于文档的“年龄”(定义为自上次访问文档以来经过的时间),文档中填充了缓存。用户对文档的偏好被建模为随文档的年龄而下降的一般功能。两种流行的度量方法(每个文档访问的预期延迟和命中率)用于评估LRU策略。与许多以前的使用模拟方法评估缓存策略的研究不同,本研究得出分析表达式来评估性能。该研究还提出了一种近似,易于计算的方法来评估性能。数值测试表明,这种近似非常精确。提出了各种其他数值结果,这些结果有助于描述在不同情况下(例如,当文档需要定期更新时)LRU策略的行为。对于小问题,我们还将LRU策略与其他缓存策略(静态和动态)进行比较。我们的比较表明,找到一个意识到文档大小和延迟的良好缓存策略可能很困难。 [参考:30]

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号