Intelligent Dynamic Aging Approaches in Web Proxy Cache Replacement

• 作者: Siti Mariyam Shamsuddin Waleed Ali
• 来源期刊: 智能学习系统与应用(英文)
• 学科: 工学
• 关键词: CACHE REPLACEMENT Web PROXY Server Dynamic-Aging APPROACHES Machine Learning
• 年，卷（期）: 2015,（4）
• 页码范围: 117-127
• 页数: 11页
• 分类号: TP39

摘要

One of commonly used approach to enhance the Web performance is Web proxy caching technique. In Web proxy caching, Least-Frequently-Used-Dynamic-Aging (LFU-DA) is one of the common proxy cache replacement methods, which is widely used in Web proxy cache management. LFU-DA accomplishes a superior byte hit ratio compared to other Web proxy cache replacement algorithms. However, LFU-DA may suffer in hit ratio measure. Therefore, in this paper, LFU-DA is enhanced using popular supervised machine learning techniques such as a support vector machine (SVM), a naive Bayes classifier (NB) and a decision tree (C4.5). SVM, NB and C4.5 are trained from Web proxy logs files and then intelligently incorporated with LFU-DA to form Intelligent Dynamic- Aging (DA) approaches. The simulation results revealed that the proposed intelligent Dynamic- Aging approaches considerably improved the performances in terms of hit and byte hit ratio of the conventional LFU-DA on a range of real datasets.