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Cloud migration framework clustering method for social decision support in modernizing the legacy system

Cloud solutions accelerate the large-scale acceptance of IoT projects. By diminishing the need for maintaining on-premises infrastructure, the cloud has enabled corporations to surpass the traditional applications of IoT (e.g., in-home appliances) and opened the doors for large-scale deployment of I...

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Main Authors: Aslam, M., Rahim, L.A.B., Watada, J., Rubab, S., Khan, M.A., AlQahtani, S.A., Gadekallu, T.R.
Format: Article
Published: 2023
Online Access:http://scholars.utp.edu.my/id/eprint/38076/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173429435&doi=10.1002%2fett.4863&partnerID=40&md5=3808171081faa08303c9411265a57d5f
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id oai:scholars.utp.edu.my:38076
record_format eprints
spelling oai:scholars.utp.edu.my:380762023-12-11T02:55:47Z http://scholars.utp.edu.my/id/eprint/38076/ Cloud migration framework clustering method for social decision support in modernizing the legacy system Aslam, M. Rahim, L.A.B. Watada, J. Rubab, S. Khan, M.A. AlQahtani, S.A. Gadekallu, T.R. Cloud solutions accelerate the large-scale acceptance of IoT projects. By diminishing the need for maintaining on-premises infrastructure, the cloud has enabled corporations to surpass the traditional applications of IoT (e.g., in-home appliances) and opened the doors for large-scale deployment of IoT applications on the cloud. However, shifting legacy systems to the cloud environment can be considerably difficult. Accordingly, this article proposes a method that may support organizations in deciding to modernize their legacy systems. The main concept of this study is to discuss the modernization strategies in detail and to support organizations in selecting the most accurate and appropriate cloud migration strategy, based on their requirements of the legacy system. This article introduces a novel research process, called the K-means cosine cloud clustering method (K3CM). K3CM is a statistical knowledge-based method for identifying and clustering the most relevant and similar cloud migration strategies. The quality of a cluster is evaluated by measuring intra-cohesiveness. Simulation experiments statistically analyzed, evaluated, and verified the quality of K3CM clusters. Correspondence analysis explored the similarity and relationship among cloud migration frameworks and validated the proposed technique. The statistical and simulation results of this study focus on the analytics and decision support system implementation that provides a reliable, valid, and robust clustering method for modernizing the legacy system. © 2023 John Wiley & Sons Ltd. 2023 Article NonPeerReviewed Aslam, M. and Rahim, L.A.B. and Watada, J. and Rubab, S. and Khan, M.A. and AlQahtani, S.A. and Gadekallu, T.R. (2023) Cloud migration framework clustering method for social decision support in modernizing the legacy system. Transactions on Emerging Telecommunications Technologies. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173429435&doi=10.1002%2fett.4863&partnerID=40&md5=3808171081faa08303c9411265a57d5f 10.1002/ett.4863 10.1002/ett.4863 10.1002/ett.4863
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 Cloud solutions accelerate the large-scale acceptance of IoT projects. By diminishing the need for maintaining on-premises infrastructure, the cloud has enabled corporations to surpass the traditional applications of IoT (e.g., in-home appliances) and opened the doors for large-scale deployment of IoT applications on the cloud. However, shifting legacy systems to the cloud environment can be considerably difficult. Accordingly, this article proposes a method that may support organizations in deciding to modernize their legacy systems. The main concept of this study is to discuss the modernization strategies in detail and to support organizations in selecting the most accurate and appropriate cloud migration strategy, based on their requirements of the legacy system. This article introduces a novel research process, called the K-means cosine cloud clustering method (K3CM). K3CM is a statistical knowledge-based method for identifying and clustering the most relevant and similar cloud migration strategies. The quality of a cluster is evaluated by measuring intra-cohesiveness. Simulation experiments statistically analyzed, evaluated, and verified the quality of K3CM clusters. Correspondence analysis explored the similarity and relationship among cloud migration frameworks and validated the proposed technique. The statistical and simulation results of this study focus on the analytics and decision support system implementation that provides a reliable, valid, and robust clustering method for modernizing the legacy system. © 2023 John Wiley & Sons Ltd.
format Article
author Aslam, M.
Rahim, L.A.B.
Watada, J.
Rubab, S.
Khan, M.A.
AlQahtani, S.A.
Gadekallu, T.R.
spellingShingle Aslam, M.
Rahim, L.A.B.
Watada, J.
Rubab, S.
Khan, M.A.
AlQahtani, S.A.
Gadekallu, T.R.
Cloud migration framework clustering method for social decision support in modernizing the legacy system
author_facet Aslam, M.
Rahim, L.A.B.
Watada, J.
Rubab, S.
Khan, M.A.
AlQahtani, S.A.
Gadekallu, T.R.
author_sort Aslam, M.
title Cloud migration framework clustering method for social decision support in modernizing the legacy system
title_short Cloud migration framework clustering method for social decision support in modernizing the legacy system
title_full Cloud migration framework clustering method for social decision support in modernizing the legacy system
title_fullStr Cloud migration framework clustering method for social decision support in modernizing the legacy system
title_full_unstemmed Cloud migration framework clustering method for social decision support in modernizing the legacy system
title_sort cloud migration framework clustering method for social decision support in modernizing the legacy system
publishDate 2023
url http://scholars.utp.edu.my/id/eprint/38076/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173429435&doi=10.1002%2fett.4863&partnerID=40&md5=3808171081faa08303c9411265a57d5f
_version_ 1787138263761289216
score 13.223943

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