Title :
Virtual Machine Placement for Improving Energy Efficiency and Network Performance in IaaS Cloud
Author :
Jiankang Dong ; Hongbo Wang ; Xing Jin ; Yangyang Li ; Peng Zhang ; Shiduan Cheng
Author_Institution :
State Key Lab. of Networking & Switching Technol., Beijing Univ. of Posts & Telecommun., Beijing, China
Abstract :
Under the premise of ensuring application performance, how to place virtual machines (VMs) on physical machines (PMs) to improve resource utilization and reduce energy consumption is one of the major concerns for cloud providers in IaaS cloud. The existing VM placement schemes are mostly to reduce energy consumption by optimizing utilization of physical server or network elements, but the issue of aggressive consolidation of VM is ignored, which may lead to network performance degradation. To address the issue, this paper proposes a VM placement scheme based on a new two-stage heuristic algorithm to optimize network performance and to reduce energy consumption of physical servers and network elements, so as to finally achieve the tradeoff between energy efficiency and network performance. The simulations show that our solution achieves good results.
Keywords :
cloud computing; power aware computing; virtual machines; IaaS cloud; PM; VM placement schemes; cloud providers; energy consumption reduction; energy efficiency; network performance; physical machines; physical servers; resource utilization; two-stage heuristic algorithm; virtual machine placement; Clustering algorithms; Energy consumption; Optimization; Resource management; Servers; Telecommunication traffic; Vectors; Energy Optimization; IaaS Cloud; Network Performance; Virtual Machine Placement;
Conference_Titel :
Distributed Computing Systems Workshops (ICDCSW), 2013 IEEE 33rd International Conference on
Conference_Location :
Philadelphia, PA
Print_ISBN :
978-1-4799-3247-4
DOI :
10.1109/ICDCSW.2013.48