A methodology for optimized VM scheduling in small and medium Fog Environments

Alkhalaf, Asma Abdullah

A methodology for optimized VM scheduling in small and medium Fog Environments

Alkhalaf, Asma Abdullah

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Publication Type:: Thesis
Issue Date:: 2024

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Field	Value	Language
dc.contributor.author	Alkhalaf, Asma Abdullah
dc.date.accessioned	2025-03-20T03:57:59Z
dc.date.available	2025-03-20T03:57:59Z
dc.date.issued	2024
dc.identifier.uri	http://hdl.handle.net/10453/186042
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_US.UTF-8
dc.description.abstract	The surge in network traffic due to the increased use of Internet of Things (IoT) devices has degraded Quality of Service (QoS) for edge users. Fog computing, an emerging paradigm, addresses this by processing tasks closer to users, reducing reliance on distant cloud servers. However, small fog datacentres, managed by Small Fog Service Providers (SFSPs), struggle with resource limitations, leading to virtual machine (VM) starvation and reduced competitiveness with larger cloud providers. This thesis proposes an innovative approach to address these issues by horizontally scaling SFSPs using nearby physical devices. As part of our approach, these external devices voluntarily offer computing resources and are integrated into the SFSP's datacentre through a recruitment process that ensures they meet specific performance and reliability standards. The selection of volunteer nodes for VM hosting is governed by trust-based ranking using a multi-criteria decision-making (MCDM) process. Our evaluations demonstrate the effectiveness of this horizontal scaling approach, showing a significant reduction in VM starvation by employing volunteer nodes within an SFSP.	en_US.UTF-8
dc.format	Thesis (PhD)
dc.language.iso	en_US	en_US.UTF-8
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/186042/1/thesis.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	© 2024 Asma Abdullah Alkhalaf
dc.rights	au.edu.uts.lib/cph
dc.title	A methodology for optimized VM scheduling in small and medium Fog Environments	en_US.UTF-8
dc.type	Thesis
utslib.copyright.status	open_access	*

Abstract:

The surge in network traffic due to the increased use of Internet of Things (IoT) devices has degraded Quality of Service (QoS) for edge users. Fog computing, an emerging paradigm, addresses this by processing tasks closer to users, reducing reliance on distant cloud servers. However, small fog datacentres, managed by Small Fog Service Providers (SFSPs), struggle with resource limitations, leading to virtual machine (VM) starvation and reduced competitiveness with larger cloud providers. This thesis proposes an innovative approach to address these issues by horizontally scaling SFSPs using nearby physical devices. As part of our approach, these external devices voluntarily offer computing resources and are integrated into the SFSP's datacentre through a recruitment process that ensures they meet specific performance and reliability standards. The selection of volunteer nodes for VM hosting is governed by trust-based ranking using a multi-criteria decision-making (MCDM) process. Our evaluations demonstrate the effectiveness of this horizontal scaling approach, showing a significant reduction in VM starvation by employing volunteer nodes within an SFSP.

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http://hdl.handle.net/10453/186042