Abstract
Web users are experiencing a long latency while retrieving the Web pages due to the amount of network traffic increased with the WWW expansion. Potential sources of latency are the Web servers’ heavy load, network congestion, low bandwidth, bandwidth underutilization, and propagation delay. To solve the latency problem, prefetching technique that predicts the destination pages for user community has become critical to save the communication overhead. Prefetching means fetching of Web pages before the users request them so as to reduce the user perceived latency. A novel Cluster and Prefetch (CPF) approach is proposed in this paper. Experimental results shows that the CPF approach effectively reduces the user perceived latency without wasting the network resources with high prediction accuracy.
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Keywords
- Joint Probability Density Function
- High Prediction Accuracy
- Continuous Random Variable
- Access Link
- Page Size
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2013 Springer India
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Raju, G.T., Sudhamani, M.V. (2013). A Novel Approach for Prefetching of Web Pages through Clustering of Web Users to Reduce the Web Latency. In: Kumar M., A., R., S., Kumar, T. (eds) Proceedings of International Conference on Advances in Computing. Advances in Intelligent Systems and Computing, vol 174. Springer, New Delhi. https://doi.org/10.1007/978-81-322-0740-5_119
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DOI: https://doi.org/10.1007/978-81-322-0740-5_119
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-0739-9
Online ISBN: 978-81-322-0740-5
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