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

Peake, Joshua, Amos, Martyn, Costen, Nicholas, Masala, Giovanni and Lloyd, Huw (2021) PACO-VMP: Parallel Ant Colony Optimization for Virtual Machine Placement. Future Generation Computer Systems. ISSN 0167-739X (In Press)

[img] Text
PACO_VMP.pdf - Accepted Version
Restricted to Repository staff only until 23 November 2022.
Available under License Creative Commons Attribution Non-commercial No Derivatives 4.0.

Download (2MB) | Request a copy

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.

Item Type: Article
Uncontrolled Keywords: Virtual Machine Placement, Ant Colony Optimization, Swarm Intelligence, Parallel MAX-MIN Ant System, Parallel Ant Colony Optimization
Subjects: G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Rachel Branson
Date Deposited: 24 Nov 2021 10:15
Last Modified: 24 Nov 2021 10:15
URI: http://nrl.northumbria.ac.uk/id/eprint/47834

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics