Intelligent web caching using adaptive regression trees, splines, random forest and tree net
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 rewa...
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| Format: | Conference or Workshop Item |
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2011
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| _version_ | 1796858855283490816 |
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| author | Abraham, Ajith Sulaiman, Sarina Shamsuddin, Siti Mariyam |
| author_facet | Abraham, Ajith Sulaiman, Sarina Shamsuddin, Siti Mariyam |
| author_sort | Abraham, Ajith |
| collection | ePrints |
| description | 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. The aim of this research is to introduce advanced machine learning approaches for Web caching to decide either to cache or not to the cache server, which could be modelled as a classification problem. The challenges include identifying attributes ranking and significant improvements in the classification accuracy. Four methods are employed in this research; Classification and Regression Trees (CART), Multivariate Adaptive Regression Splines (MARS), Random Forest (RF) and TreeNet (TN) are used for classification on Web caching. The experimental results reveal that CART performed extremely well in classifying Web objects from the existing log data and an excellent attribute to consider for an accomplishment of Web cache performance enhancement. |
| first_indexed | 2024-03-05T19:18:35Z |
| format | Conference or Workshop Item |
| id | utm.eprints-45954 |
| institution | Universiti Teknologi Malaysia - ePrints |
| last_indexed | 2024-03-05T19:18:35Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | utm.eprints-459542017-07-10T02:12:19Z http://eprints.utm.my/45954/ Intelligent web caching using adaptive regression trees, splines, random forest and tree net Abraham, Ajith Sulaiman, Sarina Shamsuddin, Siti Mariyam T Technology (General) 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. The aim of this research is to introduce advanced machine learning approaches for Web caching to decide either to cache or not to the cache server, which could be modelled as a classification problem. The challenges include identifying attributes ranking and significant improvements in the classification accuracy. Four methods are employed in this research; Classification and Regression Trees (CART), Multivariate Adaptive Regression Splines (MARS), Random Forest (RF) and TreeNet (TN) are used for classification on Web caching. The experimental results reveal that CART performed extremely well in classifying Web objects from the existing log data and an excellent attribute to consider for an accomplishment of Web cache performance enhancement. 2011 Conference or Workshop Item PeerReviewed Abraham, Ajith and Sulaiman, Sarina and Shamsuddin, Siti Mariyam (2011) Intelligent web caching using adaptive regression trees, splines, random forest and tree net. In: The 3rd Conference On Data Mining And Optimization(Dmo 11). http://dx.doi.org/10.1109/DMO.2011.5976513 |
| spellingShingle | T Technology (General) Abraham, Ajith Sulaiman, Sarina Shamsuddin, Siti Mariyam Intelligent web caching using adaptive regression trees, splines, random forest and tree net |
| title | Intelligent web caching using adaptive regression trees, splines, random forest and tree net |
| title_full | Intelligent web caching using adaptive regression trees, splines, random forest and tree net |
| title_fullStr | Intelligent web caching using adaptive regression trees, splines, random forest and tree net |
| title_full_unstemmed | Intelligent web caching using adaptive regression trees, splines, random forest and tree net |
| title_short | Intelligent web caching using adaptive regression trees, splines, random forest and tree net |
| title_sort | intelligent web caching using adaptive regression trees splines random forest and tree net |
| topic | T Technology (General) |
| work_keys_str_mv | AT abrahamajith intelligentwebcachingusingadaptiveregressiontreessplinesrandomforestandtreenet AT sulaimansarina intelligentwebcachingusingadaptiveregressiontreessplinesrandomforestandtreenet AT shamsuddinsitimariyam intelligentwebcachingusingadaptiveregressiontreessplinesrandomforestandtreenet |