Intelligent cooperative adaptive weight ranking policy via dynamic aging based on NB and J48 classifiers

The increased usage of World Wide Web leads to increase in network traffic and create a bottleneck over the internet performance. For most people, the accessing speed or the response time is the most critical factor when using the internet. Reducing response time was done by using web proxy cache te...

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Main Authors:	Al-Qudah,, Dua’A Mahmoud, Olanrewaju, Rashidah Funke, Azman, Amelia Wong
Format:	Article
Language:	English English
Published:	Institute of Advanced Engineering and Science (IAES) 2017
Subjects:	TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://irep.iium.edu.my/62957/ http://irep.iium.edu.my/62957/ http://irep.iium.edu.my/62957/ http://irep.iium.edu.my/62957/1/62957_Intelligent%20cooperative%20adaptive%20weight%20ranking_article.pdf http://irep.iium.edu.my/62957/2/62957_Intelligent%20cooperative%20adaptive%20weight%20ranking_scopus.pdf

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recordtype	eprints
spelling	iium-629572018-03-22T06:24:34Z http://irep.iium.edu.my/62957/ Intelligent cooperative adaptive weight ranking policy via dynamic aging based on NB and J48 classifiers Al-Qudah,, Dua’A Mahmoud Olanrewaju, Rashidah Funke Azman, Amelia Wong TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering The increased usage of World Wide Web leads to increase in network traffic and create a bottleneck over the internet performance. For most people, the accessing speed or the response time is the most critical factor when using the internet. Reducing response time was done by using web proxy cache technique that storing a copy of pages between client and server sides. If requested pages are cached in the proxy, there is no need to access the server. But, the cache size is limited, so cache replacement algorithms are used to remove pages from the cache when it is full. On the other hand, the conventional algorithms for replacement such as Least Recently Use (LRU), First in First Out (FIFO), Least Frequently Use (LFU), Randomised Policy, etc. may discard essential pages just before use. Furthermore, using conventional algorithms cannot be well optimized since it requires some decision to evict intelligently before a page is replaced. Hence, this paper proposes an integration of Adaptive Weight Ranking Policy (AWRP) with intelligent classifiers (NB-AWRP-DA and J48-AWRP-DA) via dynamic aging factor. To enhance classifiers power of prediction before integrating them with AWRP, particle swarm optimization (PSO) automated wrapper feature selection methods are used to choose the best subset of features that are relevant and influence classifiers prediction accuracy. Experimental Result shows that NB-AWRP-DA enhances the performance of web proxy cache across multi proxy datasets by 4.008%,4.087% and 14.022% over LRU, LFU, and FIFO while, J48-AWRP-DA increases HR by 0.483%, 0.563% and 10.497% over LRU, LFU, and FIFO respectively. Meanwhile, BHR of NB-AWRP-DA rises by 0.9911%,1.008% and 11.5842% over LRU, LFU, and FIFO respectively while 0.0204%, 0.0379% and 10.6136 for LRU, LFU, FIFO respectively using J48-AWRP-DA. Institute of Advanced Engineering and Science (IAES) 2017-12 Article PeerReviewed application/pdf en http://irep.iium.edu.my/62957/1/62957_Intelligent%20cooperative%20adaptive%20weight%20ranking_article.pdf application/pdf en http://irep.iium.edu.my/62957/2/62957_Intelligent%20cooperative%20adaptive%20weight%20ranking_scopus.pdf Al-Qudah,, Dua’A Mahmoud and Olanrewaju, Rashidah Funke and Azman, Amelia Wong (2017) Intelligent cooperative adaptive weight ranking policy via dynamic aging based on NB and J48 classifiers. Indonesian Journal of Electrical Engineering and Informatics, 5 (4). pp. 357-365. ISSN 2089-3272 http://section.iaesonline.com/index.php/IJEEI/article/view/362/pdf 10.11591/ijeei.v5i4.362
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Al-Qudah,, Dua’A Mahmoud Olanrewaju, Rashidah Funke Azman, Amelia Wong Intelligent cooperative adaptive weight ranking policy via dynamic aging based on NB and J48 classifiers
description	The increased usage of World Wide Web leads to increase in network traffic and create a bottleneck over the internet performance. For most people, the accessing speed or the response time is the most critical factor when using the internet. Reducing response time was done by using web proxy cache technique that storing a copy of pages between client and server sides. If requested pages are cached in the proxy, there is no need to access the server. But, the cache size is limited, so cache replacement algorithms are used to remove pages from the cache when it is full. On the other hand, the conventional algorithms for replacement such as Least Recently Use (LRU), First in First Out (FIFO), Least Frequently Use (LFU), Randomised Policy, etc. may discard essential pages just before use. Furthermore, using conventional algorithms cannot be well optimized since it requires some decision to evict intelligently before a page is replaced. Hence, this paper proposes an integration of Adaptive Weight Ranking Policy (AWRP) with intelligent classifiers (NB-AWRP-DA and J48-AWRP-DA) via dynamic aging factor. To enhance classifiers power of prediction before integrating them with AWRP, particle swarm optimization (PSO) automated wrapper feature selection methods are used to choose the best subset of features that are relevant and influence classifiers prediction accuracy. Experimental Result shows that NB-AWRP-DA enhances the performance of web proxy cache across multi proxy datasets by 4.008%,4.087% and 14.022% over LRU, LFU, and FIFO while, J48-AWRP-DA increases HR by 0.483%, 0.563% and 10.497% over LRU, LFU, and FIFO respectively. Meanwhile, BHR of NB-AWRP-DA rises by 0.9911%,1.008% and 11.5842% over LRU, LFU, and FIFO respectively while 0.0204%, 0.0379% and 10.6136 for LRU, LFU, FIFO respectively using J48-AWRP-DA.
format	Article
author	Al-Qudah,, Dua’A Mahmoud Olanrewaju, Rashidah Funke Azman, Amelia Wong
author_facet	Al-Qudah,, Dua’A Mahmoud Olanrewaju, Rashidah Funke Azman, Amelia Wong
author_sort	Al-Qudah,, Dua’A Mahmoud
title	Intelligent cooperative adaptive weight ranking policy via dynamic aging based on NB and J48 classifiers
title_short	Intelligent cooperative adaptive weight ranking policy via dynamic aging based on NB and J48 classifiers
title_full	Intelligent cooperative adaptive weight ranking policy via dynamic aging based on NB and J48 classifiers
title_fullStr	Intelligent cooperative adaptive weight ranking policy via dynamic aging based on NB and J48 classifiers
title_full_unstemmed	Intelligent cooperative adaptive weight ranking policy via dynamic aging based on NB and J48 classifiers
title_sort	intelligent cooperative adaptive weight ranking policy via dynamic aging based on nb and j48 classifiers
publisher	Institute of Advanced Engineering and Science (IAES)
publishDate	2017
url	http://irep.iium.edu.my/62957/ http://irep.iium.edu.my/62957/ http://irep.iium.edu.my/62957/ http://irep.iium.edu.my/62957/1/62957_Intelligent%20cooperative%20adaptive%20weight%20ranking_article.pdf http://irep.iium.edu.my/62957/2/62957_Intelligent%20cooperative%20adaptive%20weight%20ranking_scopus.pdf
first_indexed	2023-09-18T21:29:13Z
last_indexed	2023-09-18T21:29:13Z
_version_	1777412398232109056

Intelligent cooperative adaptive weight ranking policy via dynamic aging based on NB and J48 classifiers

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