Clustering-based cloud migration strategies

The k-means algorithm of the partitioning clustering method is used to analyze cloud migration strategies in this study. The extent of assistance required to be provided to organizations while working on migration strategies was investigated for each cloud service model and concrete clusters were fo...

Full description

Saved in:
Bibliographic Details
Main Authors: Aslam, M., Rahim, L.B.A., Watada, J., Hashmani, M.
Format: Article
Published: Fuji Technology Press 2018
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047755942&doi=10.20965%2fjaciii.2018.p0295&partnerID=40&md5=ff598f11a0e3a3a5f8d8d13d26bd8bff
http://eprints.utp.edu.my/20941/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utp.eprints.20941
record_format eprints
spelling my.utp.eprints.209412019-02-26T02:58:37Z Clustering-based cloud migration strategies Aslam, M. Rahim, L.B.A. Watada, J. Hashmani, M. The k-means algorithm of the partitioning clustering method is used to analyze cloud migration strategies in this study. The extent of assistance required to be provided to organizations while working on migration strategies was investigated for each cloud service model and concrete clusters were formed. This investigation is intended to aid cloud consumers in selecting their required cloud migration strategy. It is not easy for businessmen to select the most appropriate cloud migration strategy, and therefore, we proposed a suitable model to solve this problem. This model comprises a web of migration strategies, which provides an unambiguous visualization of the selected migration strategy. The cloud migration strategy targets the technical aspects linked with cloud facilities and measures the critical realization factors for cloud acceptance. Based on similar features, a correlation among the migration strategies is suggested, and three main clusters are formed accordingly. This helps to link the cloud migration strategies across the cloud service models (software as a service, platform as a service, and infrastructure as a service). This correlation was justified using the digital logic approach. This study is useful for the academia and industry as the proposed migration strategy selection process aids cloud consumers in efficiently selecting a cloud migration strategy for their legacy applications. © 2018 Fuji Technology Press. All Rights Reserved. Fuji Technology Press 2018 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047755942&doi=10.20965%2fjaciii.2018.p0295&partnerID=40&md5=ff598f11a0e3a3a5f8d8d13d26bd8bff Aslam, M. and Rahim, L.B.A. and Watada, J. and Hashmani, M. (2018) Clustering-based cloud migration strategies. Journal of Advanced Computational Intelligence and Intelligent Informatics, 22 (3). pp. 295-305. http://eprints.utp.edu.my/20941/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description The k-means algorithm of the partitioning clustering method is used to analyze cloud migration strategies in this study. The extent of assistance required to be provided to organizations while working on migration strategies was investigated for each cloud service model and concrete clusters were formed. This investigation is intended to aid cloud consumers in selecting their required cloud migration strategy. It is not easy for businessmen to select the most appropriate cloud migration strategy, and therefore, we proposed a suitable model to solve this problem. This model comprises a web of migration strategies, which provides an unambiguous visualization of the selected migration strategy. The cloud migration strategy targets the technical aspects linked with cloud facilities and measures the critical realization factors for cloud acceptance. Based on similar features, a correlation among the migration strategies is suggested, and three main clusters are formed accordingly. This helps to link the cloud migration strategies across the cloud service models (software as a service, platform as a service, and infrastructure as a service). This correlation was justified using the digital logic approach. This study is useful for the academia and industry as the proposed migration strategy selection process aids cloud consumers in efficiently selecting a cloud migration strategy for their legacy applications. © 2018 Fuji Technology Press. All Rights Reserved.
format Article
author Aslam, M.
Rahim, L.B.A.
Watada, J.
Hashmani, M.
spellingShingle Aslam, M.
Rahim, L.B.A.
Watada, J.
Hashmani, M.
Clustering-based cloud migration strategies
author_facet Aslam, M.
Rahim, L.B.A.
Watada, J.
Hashmani, M.
author_sort Aslam, M.
title Clustering-based cloud migration strategies
title_short Clustering-based cloud migration strategies
title_full Clustering-based cloud migration strategies
title_fullStr Clustering-based cloud migration strategies
title_full_unstemmed Clustering-based cloud migration strategies
title_sort clustering-based cloud migration strategies
publisher Fuji Technology Press
publishDate 2018
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047755942&doi=10.20965%2fjaciii.2018.p0295&partnerID=40&md5=ff598f11a0e3a3a5f8d8d13d26bd8bff
http://eprints.utp.edu.my/20941/
_version_ 1738656253555507200
score 13.211869