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Performance optimization for web caching based on input modeling

机译:基于输入建模的Web缓存性能优化

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摘要

In this paper, the adaptive replacement policy and the pre-fetching technique for Web caching systems are studied with two user request models and their combinations. Performance results from two most commonly used replacement policies: LRU (Least Recently Used) and LFU (Least Frequently Used) are compared. It is shown that LRU performs better for one of the user request models and LFU is on the opposite. The adaptive replacement policy is intelligent in finding the best candidate policy as the user access pattern changes. The learning speed of the system is tested by different switch thresholds.
机译:本文研究了两种用户请求模型及其组合对Web缓存系统的自适应替换策略和预取技术。比较了两种最常用的替换策略的性能结果:LRU(最近最少使用)和LFU(最近最少使用)。结果表明,LRU在其中一种用户请求模型中表现更好,而LFU相反。当用户访问模式改变时,自适应替换策略可以智能地找到最佳的候选策略。系统的学习速度通过不同的开关阈值进行测试。

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