Web Proxy Cache Replacement Strategies: Simulation, Implementation, and Performance Evaluation

ISBN-13: 9781447148920 / Angielski / Miękka / 2012 / 103 str.

Hala Elaarag; Sam Romano; Jake Cobb

Opis

Presents a study of cache replacement strategies designed for static web content. This work describes a novel approach to web proxy cache replacement that uses neural networks for decision making, evaluates its performance and decision structures, and examines its implementation in a real environment, namely, in the Squid proxy server.

Spis treści

Introduction

Background Information

Artificial Neural Networks

A Quantitative Study of Web Cache Replacement Strategies using Simulation

Web Proxy Cache Replacement Scheme Based on Back Propagation Neural Network

Implementation of a Neural Network Proxy Cache Replacement Strategy in the Squid Proxy Server

Blurb

This work presents a study of cache replacement strategies designed for static web content. Proxy servers can improve performance by caching static web content such as cascading style sheets, java script source files, and large files such as images. This topic is particularly important in wireless ad hoc networks, in which mobile devices act as proxy servers for a group of other mobile devices. Opening chapters present an introduction to web requests and the characteristics of web objects, web proxy servers and Squid, and artificial neural networks. This is followed by a comprehensive review of cache replacement strategies simulated against different performance metrics. The work then describes a novel approach to web proxy cache replacement that uses neural networks for decision making, evaluates its performance and decision structures, and examines its implementation in a real environment, namely, in the Squid proxy server.