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Intelligent Web caching using neurocomputing and particle swarm optimization algorithm

Sulaiman, Sarina and Shamsuddin, Siti Mariyam and Forkan, Fadni and Abraham, Ajith (2008) Intelligent Web caching using neurocomputing and particle swarm optimization algorithm. In: Proceedings - 2nd Asia International Conference on Modelling and Simulation, AMS 2008 , 13-15 May 2008 .

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Official URL: http://dx.doi.org/10.1109/AMS.2008.40

Abstract

Web caching is a technology for improving network traffic on the internet. It is a temporary storage of Web objects (such as HTML documents) for later retrieval. There are three significant advantages to Web caching; reduced bandwidth consumption, reduced server load, and reduced latency. These rewards have made the Web less expensive with better performance. In this paper, an Artificial Intelligence (AI) approach is introduced for Web caching to determine the type of Web request, either to cache or not, and to optimize the performance on Web cache. Two methods are employed in this study; Artificial Neural Network (ANN), and Particle Swarm Optimization (PSO). The experimental results have revealed that some improvements have been accomplished compared to the existing technique in terms of Web cache size.

Item Type:Conference or Workshop Item (Paper)
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computer Science and Information System
ID Code:7770
Deposited By: Maznira Sylvia Azra Mansor
Deposited On:21 Jan 2009 07:39
Last Modified:16 Oct 2017 08:45

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