DocumentCode
111242
Title
Using Ant Colony System to Consolidate VMs for Green Cloud Computing
Author
Farahnakian, Fahimeh ; Ashraf, Adnan ; Pahikkala, Tapio ; Liljeberg, Pasi ; Plosila, Juha ; Porres, Ivan ; Tenhunen, Hannu
Author_Institution
Dept. of Inf. Technol., Univ. of Turku, Turku, Finland
Volume
8
Issue
2
fYear
2015
fDate
March-April 1 2015
Firstpage
187
Lastpage
198
Abstract
High energy consumption of cloud data centers is a matter of great concern. Dynamic consolidation of Virtual Machines (VMs) presents a significant opportunity to save energy in data centers. A VM consolidation approach uses live migration of VMs so that some of the under-loaded Physical Machines (PMs) can be switched-off or put into a low-power mode. On the other hand, achieving the desired level of Quality of Service (QoS) between cloud providers and their users is critical. Therefore, the main challenge is to reduce energy consumption of data centers while satisfying QoS requirements. In this paper, we present a distributed system architecture to perform dynamic VM consolidation to reduce energy consumption of cloud data centers while maintaining the desired QoS. Since the VM consolidation problem is strictly NP-hard, we use an online optimization metaheuristic algorithm called Ant Colony System (ACS). The proposed ACS-based VM Consolidation (ACS-VMC) approach finds a near-optimal solution based on a specified objective function. Experimental results on real workload traces show that ACS-VMC reduces energy consumption while maintaining the required performance levels in a cloud data center. It outperforms existing VM consolidation approaches in terms of energy consumption, number of VM migrations, and QoS requirements concerning performance.
Keywords
ant colony optimisation; cloud computing; computer centres; green computing; power aware computing; quality of service; virtual machines; ACS-VMC approach; ACS-based VM consolidation approach; QoS requirements; VM consolidation approach; ant colony system; cloud data centers; cloud providers; distributed system architecture; energy consumption; green cloud computing; live VM migrations; online optimization metaheuristic algorithm; quality of service; under-loaded physical machines; virtual machines; Cloud computing; Energy consumption; Heuristic algorithms; Optimization; Quality of service; Resource management; Servers; Dynamic VM consolidation; SLA; ant colony system; cloud computing; energy-efficiency; green computing;
fLanguage
English
Journal_Title
Services Computing, IEEE Transactions on
Publisher
ieee
ISSN
1939-1374
Type
jour
DOI
10.1109/TSC.2014.2382555
Filename
6998956
Link To Document