Intelligent web proxy caching approaches based on support vector machine

Web proxy caching is one of the most successful solutions for improving the performance of Web-based systems. In Web proxy caching, the popular web objects that are likely to be revisited in the near future are stored on the proxy server which plays the key roles between users and web sites in reduc...

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Main Authors: Ali, Waleed, Shamsuddin, Siti Mariyam, Ismail, Abdul Samed
Format: Article
Published: Springer 2011
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Online Access:http://eprints.utm.my/id/eprint/44998/
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spelling my.utm.449982017-09-20T04:42:52Z http://eprints.utm.my/id/eprint/44998/ Intelligent web proxy caching approaches based on support vector machine Ali, Waleed Shamsuddin, Siti Mariyam Ismail, Abdul Samed TK Electrical engineering. Electronics Nuclear engineering Web proxy caching is one of the most successful solutions for improving the performance of Web-based systems. In Web proxy caching, the popular web objects that are likely to be revisited in the near future are stored on the proxy server which plays the key roles between users and web sites in reducing the response time of user requests and saving the network bandwidth. However, the difficulty in determining the ideal web objects that will be re-visited in the future is still a problem faced by existing conventional Web proxy caching techniques. In this paper, support vector machine (SVM) is used to enhance the performance of conventional web proxy caching such as Least-Recently-Used (LRU) and Greedy-Dual-Size-Frequency (GDSF). SVM is intelligently incorporated with conventional Web proxy caching techniques to form intelligent caching approaches called SVM_LRU and SVM_GDSF with better performance. Experimental results have revealed that the proposed SVM_LRU and SVM_GDSF improve significantly the performances of LRU and GDSF respectively across several proxy datasets. Springer 2011 Article PeerReviewed Ali, Waleed and Shamsuddin, Siti Mariyam and Ismail, Abdul Samed (2011) Intelligent web proxy caching approaches based on support vector machine. Communications in Computer and Information Science, 252 (2). pp. 559-572. ISSN 1865-0929
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Ali, Waleed
Shamsuddin, Siti Mariyam
Ismail, Abdul Samed
Intelligent web proxy caching approaches based on support vector machine
description Web proxy caching is one of the most successful solutions for improving the performance of Web-based systems. In Web proxy caching, the popular web objects that are likely to be revisited in the near future are stored on the proxy server which plays the key roles between users and web sites in reducing the response time of user requests and saving the network bandwidth. However, the difficulty in determining the ideal web objects that will be re-visited in the future is still a problem faced by existing conventional Web proxy caching techniques. In this paper, support vector machine (SVM) is used to enhance the performance of conventional web proxy caching such as Least-Recently-Used (LRU) and Greedy-Dual-Size-Frequency (GDSF). SVM is intelligently incorporated with conventional Web proxy caching techniques to form intelligent caching approaches called SVM_LRU and SVM_GDSF with better performance. Experimental results have revealed that the proposed SVM_LRU and SVM_GDSF improve significantly the performances of LRU and GDSF respectively across several proxy datasets.
format Article
author Ali, Waleed
Shamsuddin, Siti Mariyam
Ismail, Abdul Samed
author_facet Ali, Waleed
Shamsuddin, Siti Mariyam
Ismail, Abdul Samed
author_sort Ali, Waleed
title Intelligent web proxy caching approaches based on support vector machine
title_short Intelligent web proxy caching approaches based on support vector machine
title_full Intelligent web proxy caching approaches based on support vector machine
title_fullStr Intelligent web proxy caching approaches based on support vector machine
title_full_unstemmed Intelligent web proxy caching approaches based on support vector machine
title_sort intelligent web proxy caching approaches based on support vector machine
publisher Springer
publishDate 2011
url http://eprints.utm.my/id/eprint/44998/
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score 13.187197