About: PACO-VMP: Parallel Ant Colony Optimization for Virtual Machine Placement

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type	http://eprints.org/ontology/ArticleEPrint http://eprints.org/ontology/EPrint Article Academic Article
seeAlso	HTML Summary of #93038 PACO-VMP: Parallel Ant Colony Optimization for Virtual Machine Placement
sameAs	PACO-VMP: Parallel Ant Colony Optimization for Virtual Machine Placement
http://eprints.org/ontology/hasAccepted	PACO-VMP: Parallel Ant Colony Optimization for Virtual Machine Placement (PDF)
http://eprints.org/ontology/hasDocument	PACO-VMP: Parallel Ant Colony Optimization for Virtual Machine Placement (PDF) PACO-VMP: Parallel Ant Colony Optimization for Virtual Machine Placement (Other) PACO-VMP: Parallel Ant Colony Optimization for Virtual Machine Placement (Other) PACO-VMP: Parallel Ant Colony Optimization for Virtual Machine Placement (Other) PACO-VMP: Parallel Ant Colony Optimization for Virtual Machine Placement (Other) PACO-VMP: Parallel Ant Colony Optimization for Virtual Machine Placement (Other)
dc:hasVersion	PACO-VMP: Parallel Ant Colony Optimization for Virtual Machine Placement (PDF)
Title	PACO-VMP: Parallel Ant Colony Optimization for Virtual Machine Placement
described by	https://demo.openlinksw.com/about/id/entity/https/raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
Date	2022-04
Creator	Joshua Peake Nicholas Costen Martyn Amos Huw Lloyd G.L. Masala
status	peer reviewed published
Publisher	Elsevier
abstract	The Virtual Machine Placement (VMP) problem is a challenging optimization task that involves the assignment of virtual machines to physical machines in a cloud computing environment. The placement of virtual machines can significantly affect the use of resources in a cluster, with a subsequent impact on operational costs and the environment. In this paper, we present an improved algorithm for VMP, based on Parallel Ant Colony Optimization (PACO), which makes effective use of parallelization techniques and modern processor technologies. We achieve solution qualities that are comparable with or superior to those obtained by other nature-inspired methods, with our parallel implementation obtaining a speed-up of up to 2002x over recent serial algorithms in the literature. This allows us to rapidly find high-quality solutions that are close to the theoretical minimum number of Virtual Machines.
Is Part Of	Future Generation Computer Systems https://kar.kent.ac.uk/id/repository
Subject	QA 75 Electronic computers. Computer science
list of authors	https://kar.kent.ac.uk/id/eprint/93038#authors
volume	129
is topic of	https://raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #93038 PACO-VMP: Parallel Ant Colony Optimization for Virtual Machine Placement

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