DocumentCode
113563
Title
Performance analysis of Hadoop MapReduce on an OpenNebula cloud with KVM and OpenVZ virtualizations
Author
Magalhaes Vasconcelos, Pedro Roger ; Azevedo de Araujo Freitas, Gisele
Author_Institution
Fed. Univ. of Ceara, Ceará, Brazil
fYear
2014
fDate
8-10 Dec. 2014
Firstpage
471
Lastpage
476
Abstract
Cloud computing provides access to a set of resources such as virtual machines, storage and network as services. In this context, virtualization has been used as an platform for resource-intensive applications, like Hadoop, as it has brought features like server consolidation, scalability and better resources usage. OpenVZ and KVM are very popular and widely used virtualization platforms with distinct virtualization modes: containet-based and full-virtualization. In this work, we conducted benchmarks to measure the performance of a Hadoop cluster deployed on OpenNebula clouds with KVM and OpenVZ. Our results show that OpenVZ performs better than KVM in the CPU and I/O reading benchmarks. KVM achieves better performance in the I/O writing benchmarks.
Keywords
cloud computing; data handling; operating system kernels; resource allocation; virtual machines; virtualisation; CPU; Hadoop MapReduce; Hadoop cluster; I/O reading benchmarks; I/O writing benchmarks; KVM; OpenNebula cloud computing; OpenVZ virtualizations; containet-based virtualization; kernel-based virtual machine; performance analysis; resource-intensive applications; Benchmark testing; Cloud computing; Hardware; Servers; Virtual machine monitors; Virtual machining; Virtualization; Big Data; KVM; MapReduce; OpenVZ; cloud computing; virtualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Internet Technology and Secured Transactions (ICITST), 2014 9th International Conference for
Conference_Location
London
Type
conf
DOI
10.1109/ICITST.2014.7038858
Filename
7038858
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