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Evaluation of an Evolutionary Algorithm to Dynamically Alter Partition Sizes in Web Caching Systems

机译:评估进化算法在Web缓存系统中动态改变分区大小的评估

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There has been an explosion in the volume of data that is being accessed from the Internet. As a result, the risk of a Web server being inundated with requests is ever-present. One approach to reducing the performance degradation that potentially comes from Web server overloading is to employ Web caching where data content is replicated in multiple locations. In this paper, we investigate the use of evolutionary algorithms to dynamically alter partition size in Web caches. We use established modeling techniques to compare the performance of our evolutionary algorithm to that found in statically-partitioned systems. Our results indicate that utilizing an evolutionary algorithm to dynamically alter partition sizes can lead to performance improvements especially in environments where the relative size of large to small pages is high.
机译:从Internet访问的数据卷中存在爆发。因此,遍历与请求淹没的Web服务器的风险是持久存在的。一种降低可能来自Web服务器重载的性能劣化的一种方法是使用Web高速缓存,其中数据内容在多个位置复制。在本文中,我们调查了进化算法的使用来动态改变Web高速缓存中的分区大小。我们使用建立的建模技术来比较我们的进化算法在静态分区系统中的表现。我们的结果表明,利用进化算法动态改变分区大小,可以导致性能改进,特别是在大于小页的相对大小的环境中。

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