DocumentCode :
251838
Title :
Adaptive Downtime for Live Migration of Virtual Machines
Author :
Clemente-Castello, Francisco J. ; Fernandez, Juan Carlos ; Mayo, Rafael ; Quintana-Orti, Enrique S.
Author_Institution :
Depto. de Ing. y Cienc. de Comput., Univ. Jaume I, Castellόn, Spain
fYear :
2014
fDate :
8-11 Dec. 2014
Firstpage :
457
Lastpage :
464
Abstract :
Live migration of virtual machines is a pivotal mechanism to offer consolidation services in virtualized and cloud computing environments. In general, the standard live migration process favors short downtime periods, to avoid affecting on-line services provided by virtual machines. In particular, live migration can only be applied in scenarios where the dirty page rate is low compared to the communication network bandwidth. Furthermore, while setting a short downtime is convenient for on-line services, this may not be necessary, e.g., For long time-consuming high performance applications as, in this sort of computations, a relative large of downtime period, (say, in the order of minutes) due to a live migration, only introduces a small overhead on the total execution time. In this paper we enhance the live migration process in a variety of scenarios where the standard live migration configuration does not permit live migration. For these situations, we propose, analyse, and validate a modification of the KVM hyper visor that accommodates live migration with short downtime, independently of the type of application and services in execution on the virtual machine.
Keywords :
cloud computing; resource allocation; virtual machines; virtualisation; KVM hypervisor; adaptive downtime; cloud computing; kernel-based virtual machine; live migration; resource use; virtualization; Algorithm design and analysis; Bandwidth; Benchmark testing; Cloud computing; Random access memory; Virtual machine monitors; Virtual machining; HPC; KVM; Virtualization; energy consumption; live migration; performance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Utility and Cloud Computing (UCC), 2014 IEEE/ACM 7th International Conference on
Conference_Location :
London
Type :
conf
DOI :
10.1109/UCC.2014.58
Filename :
7027525
Link To Document :
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