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An Enhanced Semantic-Based Cache Replacement Algorithm for Web Systems

机译:Web系统的一种基于语义的增强型缓存替换算法

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As Web traffics is increasing on the Internet, caching solutions for Web systems are becoming more important since they can greatly expand system scalability. An important part of a caching solution is cache replacement policy, which is responsible for selecting victim items that should be removed in order to make space for new objects. Typical replacement policies used in practice only take advantage of temporal reference locality by removing the least recently/frequently requested items from the cache. Although those policies work well in memory or filesystem cache, they are inefficient for Web systems since they do not exploit semantic relationship between Web items. This paper presents a semantic-aware caching policy that can be used in Web systems to enhance scalability. The proposed caching mechanism defines semantic distance from a web page to a set of pivot pages and use the semantic distances as a metric for choosing victims. Also, it use a function-based metric that combines access frequency and cache item size for tie-breaking. Our simulations show that out enhancements outperform traditional methods in terms of hit rate, which can be useful for websites with many small and similar-in-size web objects.
机译:随着Internet上Web流量的增加,Web系统的缓存解决方案变得越来越重要,因为它们可以大大扩展系统的可伸缩性。缓存解决方案的重要组成部分是缓存替换策略,该策略负责选择应删除的受害者项,以便为新对象腾出空间。在实践中使用的典型替换策略仅通过从缓存中删除最近/经常请求的项目来利用时间参考位置。尽管这些策略在内存或文件系统缓存中运行良好,但由于它们未利用Web项之间的语义关系,因此它们对于Web系统效率不高。本文提出了一种语义感知的缓存策略,该策略可用于Web系统中以增强可伸缩性。所提出的缓存机制定义了从网页到一组透视页面的语义距离,并使用语义距离作为选择受害者的度量。此外,它使用基于功能的度量标准,将访问频率和缓存项大小结合在一起以进行平局。我们的模拟结果表明,在点击率方面,出众的性能优于传统方法,这对于具有许多小型且尺寸相似的Web对象的网站很有用。

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