Impact of Machine Learning Techniques with Cache Replacement Algorithmsinenhancingthe Performance of theWebserver

Abstract

Inthe era of information age, internet plays pivotal role in disseminating knowledge to the consumers. Time taken to access the required web object is the main bottleneck in the pretext of voluminous web traffic. Web cache is one of the traditional techniques used to improve the performance of the web. Various algorithms like LRU, LFU, SIZE, GD-Size and GDSF are initially used to enhance the system. This paper discusses the impact of coupling machine learning techniques like Decision Tree, Support Vector Machine and Naïve Bayes along with traditional algorithms in reducing the user perceived latency and in improving the HitRatio(HR) and Byte Hit Ratio (BHR). Keywords-Web log mining, caching, machine learning, hit ratio, byte hit ratio, decision tree, support vector machine, naïve bayes