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Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems

Web caching plays a key role in delivering web items to end users in World Wide Web (WWW).On the other hand, cache size is considered as a limitation of web caching.Furthermore, retrieving the same media object from the origin server many times consumes the network bandwidth. Furthermore, full cachi...

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Main Authors: Ibrahim, Hamidah, Yasin, Waheed, Udzir, Nur Izura, Abdul Hamid, Nor Asilah Wati
Format: Article
Language:English
Published: Universiti Utara Malaysia Press 2016
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://repo.uum.edu.my/24070/1/JICT%2015%202%202016%2085%E2%80%93116.pdf
http://repo.uum.edu.my/24070/
http://jict.uum.edu.my/index.php/previous-issues/149-1
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spelling my.uum.repo.240702018-04-29T01:43:31Z http://repo.uum.edu.my/24070/ Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems Ibrahim, Hamidah Yasin, Waheed Udzir, Nur Izura Abdul Hamid, Nor Asilah Wati QA75 Electronic computers. Computer science Web caching plays a key role in delivering web items to end users in World Wide Web (WWW).On the other hand, cache size is considered as a limitation of web caching.Furthermore, retrieving the same media object from the origin server many times consumes the network bandwidth. Furthermore, full caching for media objects is not a practical solution and consumes cache storage in keeping few media objects because of its limited capacity. Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. The proposed approaches take the advantages of structured peer-to-peer systems where the contents of peers’ caches are shared using Distributed Hash Table (DHT) in order to enhance the performance of the web caching policy. The performance of the proposed approaches is evaluated by running a trace-driven simulation on a dataset that is collected from IRCache network. The results demonstrate that the new proposed policies improve the performance of traditional web caching policies that are LRU, LFU, and GDS in terms of Hit Ratio (HR) and Byte Hit Ratio (BHR). Moreover, the results are compared to the most relevant and state-of-the-art web proxy caching policies. Ratio (HR) and Byte Hit Ratio (BHR). Moreover, the results are compared to the most relevant and state-of-the-art web proxy caching policies. Universiti Utara Malaysia Press 2016 Article PeerReviewed application/pdf en http://repo.uum.edu.my/24070/1/JICT%2015%202%202016%2085%E2%80%93116.pdf Ibrahim, Hamidah and Yasin, Waheed and Udzir, Nur Izura and Abdul Hamid, Nor Asilah Wati (2016) Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems. Journal of Information and Communication Technology, 15 (2). pp. 85-116. ISSN 2180-3862 http://jict.uum.edu.my/index.php/previous-issues/149-1
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Ibrahim, Hamidah
Yasin, Waheed
Udzir, Nur Izura
Abdul Hamid, Nor Asilah Wati
Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems
description Web caching plays a key role in delivering web items to end users in World Wide Web (WWW).On the other hand, cache size is considered as a limitation of web caching.Furthermore, retrieving the same media object from the origin server many times consumes the network bandwidth. Furthermore, full caching for media objects is not a practical solution and consumes cache storage in keeping few media objects because of its limited capacity. Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. The proposed approaches take the advantages of structured peer-to-peer systems where the contents of peers’ caches are shared using Distributed Hash Table (DHT) in order to enhance the performance of the web caching policy. The performance of the proposed approaches is evaluated by running a trace-driven simulation on a dataset that is collected from IRCache network. The results demonstrate that the new proposed policies improve the performance of traditional web caching policies that are LRU, LFU, and GDS in terms of Hit Ratio (HR) and Byte Hit Ratio (BHR). Moreover, the results are compared to the most relevant and state-of-the-art web proxy caching policies. Ratio (HR) and Byte Hit Ratio (BHR). Moreover, the results are compared to the most relevant and state-of-the-art web proxy caching policies.
format Article
author Ibrahim, Hamidah
Yasin, Waheed
Udzir, Nur Izura
Abdul Hamid, Nor Asilah Wati
author_facet Ibrahim, Hamidah
Yasin, Waheed
Udzir, Nur Izura
Abdul Hamid, Nor Asilah Wati
author_sort Ibrahim, Hamidah
title Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems
title_short Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems
title_full Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems
title_fullStr Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems
title_full_unstemmed Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems
title_sort intelligent cooperative web caching policies for media objects based on j48 decision tree and naive bayes supervised machine learning algorithms in structured peer-to-peer systems
publisher Universiti Utara Malaysia Press
publishDate 2016
url http://repo.uum.edu.my/24070/1/JICT%2015%202%202016%2085%E2%80%93116.pdf
http://repo.uum.edu.my/24070/
http://jict.uum.edu.my/index.php/previous-issues/149-1
_version_ 1644283955848937472
score 13.211869

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