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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Vydáno v:Proceedings of the IEEE Ročník 102; číslo 1; s. 11 - 31
Hlavní autoři: Xu, Fei, Liu, Fangming, Jin, Hai, Vasilakos, Athanasios V.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York, NY IEEE 01.01.2014
Institute of Electrical and Electronics Engineers
Témata:
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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Popis
Shrnutí: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.
ISSN:0018-9219
1558-2256
DOI:10.1109/JPROC.2013.2287711