Intelligent Web Caching for E-learning Log Data

Abstract

E-learning has been a common online service to support teaching and learning in education. Universiti Teknologi Malaysia (UTM) has been using such service that is known as e-Learning@UTM since 2005.  The demand for e-learning content increases dramatically every semester. The performance of e-learning servers reduces when the number of users for each semester keeps growing. Hence users often experience poor performance in accessing the e-learning contents or downloading files. Such problems are due to the problem in the performance of servers, network infrastructure and majority of users tend to access the same piece of information repetitively. Web caching has been recognized as an effective scheme to reduce service bottleneck, users’ access latency and  network traffic. Therefore this paper will discuss an alternative way to tackle these problems by implementing a log data detection tool. This tool is capable to automatically directing either to cache or not to cache the objects in a document based on the log data (number of object hits, script size of objects, and time to receive object) in e-Learning@UTM to enhance such Web access.