research-article

An auto-scaling mechanism for cloud-based multimedia storage systems: a fuzzy-based elastic controller

Authors:

Mostafa Ghobaei-Arani,

Alireza SouriAuthors Info & Claims

Multimedia Tools and Applications, Volume 81, Issue 24

Pages 34501 - 34523

https://doi.org/10.1007/s11042-021-11021-9

Published: 01 October 2022 Publication History

Abstract

Cloud computing is a new technology that is increasing in popularity day-by-day. One of the reasons for its popularity can be its elasticity feature. In other words, cloud computing considers the consumer’s resource capacity to be infinite, where the consumer can obtain the resources on-demand and increase or decrease the number of resources. Although various solutions for elasticity management have been developed so far, more work is needed to manage the elasticity of the cloud-based multimedia storage systems more effectively. Accordingly, this paper presents the Observe–Orient–Decide–Act (OODA) loop to improve the resource elasticity in cloud-based multimedia storage systems. In the proposed solution, elasticity management is performed using the OODA loop and fuzzy logic theory. Our simulation results demonstrate that the proposed solution reduces the read time, write time, response time by 7.2%, 6.9%, and 8.4%, respectively, compared with existing elastic cloud-based storage mechanisms.

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Cited By

Dogani JKhunjush FMahmoudi MSeydali M(2023)Multivariate workload and resource prediction in cloud computing using CNN and GRU by attention mechanismThe Journal of Supercomputing10.1007/s11227-022-04782-z79:3(3437-3470)Online publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1007/s11227-022-04782-z

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Information & Contributors

Information

Published In

cover image Multimedia Tools and Applications

Multimedia Tools and Applications Volume 81, Issue 24

Oct 2022

1337 pages

ISSN:1380-7501

Issue’s Table of Contents

© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2021.

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 October 2022

Accepted: 05 May 2021

Revision received: 31 March 2021

Received: 24 October 2020

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Cited By

Dogani JKhunjush FMahmoudi MSeydali M(2023)Multivariate workload and resource prediction in cloud computing using CNN and GRU by attention mechanismThe Journal of Supercomputing10.1007/s11227-022-04782-z79:3(3437-3470)Online publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1007/s11227-022-04782-z

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