Improvement of Web Performance Using Optimized Prediction Algorithm and Dynamic Webpage Content Updation in Proxy Cache

Abstract

Identifying web user activity and interest of the users helps to improve the web access performance. Web usage mining applications like website enhancement, web personalization, prediction and prefetching etc. are used to improve the web performance. Increasing web usage in internet leads to network traffic, user latency, and server burden. Proxy server acts as an intermediate between the web user and web server to reduce the server burden. Updating dynamic content in a proxy cache is the major drawback in proxy server. In recent days various new add-on algorithms are given to server to reduce user latency but then it has become additional overload of the server. In this paper, the work is organised with three portions; the first portion focused in optimized way of running Monte Carlo prediction algorithm to reduce the server load. Second portion works on dynamic content to get update in the proxy cache to improve the performance of the website and finally the third portion deals with the prefetching engine in proxy server which maintains two caches to reduce server load and also to reduce user latency. The successful implementation shows the optimized way of reducing server load for add-on programs.