Multi-objective dynamic virtual machine consolidation in the cloud using ant colony system. Issue 1 (2nd January 2018)
- Record Type:
- Journal Article
- Title:
- Multi-objective dynamic virtual machine consolidation in the cloud using ant colony system. Issue 1 (2nd January 2018)
- Main Title:
- Multi-objective dynamic virtual machine consolidation in the cloud using ant colony system
- Authors:
- Ashraf, Adnan
Porres, Ivan - Abstract:
- Abstract: In this paper, we present a novel multi-objective ant colony system algorithm for virtual machine (VM) consolidation in cloud data centres. The proposed algorithm builds VM migration plans, which are then used to minimise over-provisioning of physical machines (PMs) by consolidating VMs on under-utilised PMs. It optimises two objectives that are ordered by their importance. The first and foremost objective in the proposed algorithm is to maximise the number of released PMs. Moreover, since VM migration is a resource-intensive operation, it also tries to minimise the number of VM migrations. The proposed algorithm is empirically evaluated in a series of experiments. The experimental results show that the proposed algorithm provides an efficient solution for VM consolidation in cloud data centres. Moreover, it outperforms two existing ant colony optimization-based VM consolidation algorithms in terms of number of released PMs and number of VM migrations. Graphical Abstract: MOACS advances the state of the art on ACO-based VM consolidation by implementing a multi-objective, multi-colony ACS algorithm. It extends our previous single-objective, single-colony ACO algorithm for VM consolidation and similar works by other researchers that implement single-objective, single-colony ACO algorithms. The proposed multi-objective, multi-colony approach eliminates the need for an aggregate objective function (AOF) and allows to combine the optimisation objectives in anAbstract: In this paper, we present a novel multi-objective ant colony system algorithm for virtual machine (VM) consolidation in cloud data centres. The proposed algorithm builds VM migration plans, which are then used to minimise over-provisioning of physical machines (PMs) by consolidating VMs on under-utilised PMs. It optimises two objectives that are ordered by their importance. The first and foremost objective in the proposed algorithm is to maximise the number of released PMs. Moreover, since VM migration is a resource-intensive operation, it also tries to minimise the number of VM migrations. The proposed algorithm is empirically evaluated in a series of experiments. The experimental results show that the proposed algorithm provides an efficient solution for VM consolidation in cloud data centres. Moreover, it outperforms two existing ant colony optimization-based VM consolidation algorithms in terms of number of released PMs and number of VM migrations. Graphical Abstract: MOACS advances the state of the art on ACO-based VM consolidation by implementing a multi-objective, multi-colony ACS algorithm. It extends our previous single-objective, single-colony ACO algorithm for VM consolidation and similar works by other researchers that implement single-objective, single-colony ACO algorithms. The proposed multi-objective, multi-colony approach eliminates the need for an aggregate objective function (AOF) and allows to combine the optimisation objectives in an appropriate manner. … (more)
- Is Part Of:
- International journal of parallel, emergent and distributed systems. Volume 33:Issue 1(2018)
- Journal:
- International journal of parallel, emergent and distributed systems
- Issue:
- Volume 33:Issue 1(2018)
- Issue Display:
- Volume 33, Issue 1 (2018)
- Year:
- 2018
- Volume:
- 33
- Issue:
- 1
- Issue Sort Value:
- 2018-0033-0001-0000
- Page Start:
- 103
- Page End:
- 120
- Publication Date:
- 2018-01-02
- Subjects:
- Virtual machines -- consolidation -- metaheuristic -- ant colony system -- cloud computing
Parallel computers -- Periodicals
Electronic data processing -- Distributed processing -- Periodicals
Computer algorithms -- Periodicals
004.35 - Journal URLs:
- http://www.tandfonline.com/toc/gpaa20/current ↗
http://www.tandfonline.com/ ↗ - DOI:
- 10.1080/17445760.2017.1278601 ↗
- Languages:
- English
- ISSNs:
- 1744-5760
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4542.441300
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 5416.xml