TITLE:
Intelligent Dynamic Aging Approaches in Web Proxy Cache Replacement
AUTHORS:
Waleed Ali, Siti Mariyam Shamsuddin
KEYWORDS:
Cache Replacement, Web Proxy Server, Dynamic-Aging Approaches, Machine Learning
JOURNAL NAME:
Journal of Intelligent Learning Systems and Applications,
Vol.7 No.4,
November
13,
2015
ABSTRACT: 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.