Development of Web services fuzzy quality models using data clustering approach

This paper presents the fuzzy clustering of web services' quality of service (QoS) data using Fuzzy C-Means (FCM) algorithm. It was conducted based on actual QoS data gathered from the network. The work involved three data sets that represented three different QoS parameters. Each data set cont...

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Main Authors: Hasan, M.H., Jaafar, J., Hassan, M.F.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.31724 /
Published: Springer Verlag 2014
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84958525875&doi=10.1007%2f978-981-4585-18-7_71&partnerID=40&md5=bc4935cef15a33c6984490f16bb75966
http://eprints.utp.edu.my/31724/
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spelling utp-eprints.317242022-03-29T03:36:11Z Development of Web services fuzzy quality models using data clustering approach Hasan, M.H. Jaafar, J. Hassan, M.F. This paper presents the fuzzy clustering of web services' quality of service (QoS) data using Fuzzy C-Means (FCM) algorithm. It was conducted based on actual QoS data gathered from the network. The work involved three data sets that represented three different QoS parameters. Each data set contained 1500 data points. The clustering was validated using Xie-Beni index to ensure that it performed optimally. As a result, three fuzzy quality models were produced that represented the three QoS parameters. The work implies potential new findings on fuzzy-based web services' applications, mainly in reducing computational complexity. The work also benefits the less technical-knowledgeable requestors as the fuzzy quality models can guide them to find services with realistic QoS performance. For future work, the fuzzy quality models will be employed in web services' QoS monitoring application. They will also be equipped with an adaptive mechanism that supports the dynamic nature of web services. © Springer Science+Business Media Singapore 2014. Springer Verlag 2014 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84958525875&doi=10.1007%2f978-981-4585-18-7_71&partnerID=40&md5=bc4935cef15a33c6984490f16bb75966 Hasan, M.H. and Jaafar, J. and Hassan, M.F. (2014) Development of Web services fuzzy quality models using data clustering approach. Lecture Notes in Electrical Engineering, 285 LN . pp. 631-640. http://eprints.utp.edu.my/31724/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description This paper presents the fuzzy clustering of web services' quality of service (QoS) data using Fuzzy C-Means (FCM) algorithm. It was conducted based on actual QoS data gathered from the network. The work involved three data sets that represented three different QoS parameters. Each data set contained 1500 data points. The clustering was validated using Xie-Beni index to ensure that it performed optimally. As a result, three fuzzy quality models were produced that represented the three QoS parameters. The work implies potential new findings on fuzzy-based web services' applications, mainly in reducing computational complexity. The work also benefits the less technical-knowledgeable requestors as the fuzzy quality models can guide them to find services with realistic QoS performance. For future work, the fuzzy quality models will be employed in web services' QoS monitoring application. They will also be equipped with an adaptive mechanism that supports the dynamic nature of web services. © Springer Science+Business Media Singapore 2014.
format Article
author Hasan, M.H.
Jaafar, J.
Hassan, M.F.
spellingShingle Hasan, M.H.
Jaafar, J.
Hassan, M.F.
Development of Web services fuzzy quality models using data clustering approach
author_sort Hasan, M.H.
title Development of Web services fuzzy quality models using data clustering approach
title_short Development of Web services fuzzy quality models using data clustering approach
title_full Development of Web services fuzzy quality models using data clustering approach
title_fullStr Development of Web services fuzzy quality models using data clustering approach
title_full_unstemmed Development of Web services fuzzy quality models using data clustering approach
title_sort development of web services fuzzy quality models using data clustering approach
publisher Springer Verlag
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84958525875&doi=10.1007%2f978-981-4585-18-7_71&partnerID=40&md5=bc4935cef15a33c6984490f16bb75966
http://eprints.utp.edu.my/31724/
_version_ 1741197625255788544
score 11.62408

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