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

Joshua Peake, Martyn Amos, Nicholas Costen, Giovanni Masala, Huw Lloyd*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish
JournalFuture Generation Computer Systems
Publication statusAccepted/In press - 23 Nov 2021

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