Managing Performance Overhead of Virtual Machines in Cloud Computing: A Survey, State of the Art, and Future Directions

Infrastructure-as-a-Service (IaaS) cloud computing offers customers (tenants) a scalable and economical way to provision virtual machines (VMs) on demand while charging them only for the leased computing resources by time. However, due to the VM contention on shared computing resources in datacenter...

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Vydané v:	Proceedings of the IEEE Ročník 102; číslo 1; s. 11 - 31
Hlavní autori:	Xu, Fei, Liu, Fangming, Jin, Hai, Vasilakos, Athanasios V.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York, NY IEEE 01.01.2014 Institute of Electrical and Electronics Engineers
Predmet:	Applied sciences Cloud computing Computer science; control theory; systems Computer systems and distributed systems. User interface Data centers Exact sciences and technology Language processing and microprogramming Performance evaluation predictable performance Servers Software virtual machine (VM) performance overhead Virtual machining Virtualization Wide area networks Performance evaluation On demand Cloud computing virtual machine (VM) performance overhead virtualization Virtual machine Web service Data center Resource sharing Review Modeling Process virtualization predictable performance Software infrastructure Computer server
ISSN:	0018-9219, 1558-2256
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Abstract	Infrastructure-as-a-Service (IaaS) cloud computing offers customers (tenants) a scalable and economical way to provision virtual machines (VMs) on demand while charging them only for the leased computing resources by time. However, due to the VM contention on shared computing resources in datacenters, this new computing paradigm inevitably brings noticeable performance overhead (i.e., unpredictable performance) of VMs to tenants, which has become one of the primary issues of the IaaS cloud. Consequently, increasing efforts have recently been devoted to guaranteeing VM performance for tenants. In this survey, we review the state-of-the-art research on managing the performance overhead of VMs, and summarize them under diverse scenarios of the IaaS cloud, ranging from the single-server virtualization, a single mega datacenter, to multiple geodistributed datacenters. Specifically, we unveil the causes of VM performance overhead by illustrating representative scenarios, discuss the performance modeling methods with a particular focus on their accuracy and cost, and compare the overhead mitigation techniques by identifying their effectiveness and implementation complexity. With the obtained insights into the pros and cons of each existing solution, we further bring forth future research challenges pertinent to the modeling methods and mitigation techniques of VM performance overhead in the IaaS cloud.
AbstractList	Infrastructure-as-a-Service (IaaS) cloud computing offers customers (tenants) a scalable and economical way to provision virtual machines (VMs) on demand while charging them only for the leased computing resources by time. However, due to the VM contention on shared computing resources in datacenters, this new computing paradigm inevitably brings noticeable performance overhead (i.e., unpredictable performance) of VMs to tenants, which has become one of the primary issues of the IaaS cloud. Consequently, increasing efforts have recently been devoted to guaranteeing VM performance for tenants. In this survey, we review the state-of-the-art research on managing the performance overhead of VMs, and summarize them under diverse scenarios of the IaaS cloud, ranging from the single-server virtualization, a single mega datacenter, to multiple geodistributed datacenters. Specifically, we unveil the causes of VM performance overhead by illustrating representative scenarios, discuss the performance modeling methods with a particular focus on their accuracy and cost, and compare the overhead mitigation techniques by identifying their effectiveness and implementation complexity. With the obtained insights into the pros and cons of each existing solution, we further bring forth future research challenges pertinent to the modeling methods and mitigation techniques of VM performance overhead in the IaaS cloud.
Author	Vasilakos, Athanasios V. Jin, Hai Liu, Fangming Xu, Fei
Author_xml	– sequence: 1 givenname: Fei surname: Xu fullname: Xu, Fei email: xufei@hust.edu.cn organization: Services Computing Technology and System Lab, Cluster and Grid Computing Lab in the School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan , China – sequence: 2 givenname: Fangming surname: Liu fullname: Liu, Fangming email: fmliu@hust.edu.cn organization: Services Computing Technology and System Lab, Cluster and Grid Computing Lab in the School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan , China – sequence: 3 givenname: Hai surname: Jin fullname: Jin, Hai email: hjin@hust.edu.cn organization: Services Computing Technology and System Lab, Cluster and Grid Computing Lab in the School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan , China – sequence: 4 givenname: Athanasios V. surname: Vasilakos fullname: Vasilakos, Athanasios V. email: vasilako@sci.kuniv.edu.kw organization: Department of Computer Science, Kuwait University, Safat, Kuwait
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Snippet	Infrastructure-as-a-Service (IaaS) cloud computing offers customers (tenants) a scalable and economical way to provision virtual machines (VMs) on demand while...
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SubjectTerms	Applied sciences Cloud computing Computer science; control theory; systems Computer systems and distributed systems. User interface Data centers Exact sciences and technology Language processing and microprogramming Performance evaluation predictable performance Servers Software virtual machine (VM) performance overhead Virtual machining Virtualization Wide area networks
Title	Managing Performance Overhead of Virtual Machines in Cloud Computing: A Survey, State of the Art, and Future Directions
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Volume	102
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