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Resource Virtualization for Real-time Industrial Clouds
Mälardalen University, School of Innovation, Design and Engineering.
2016 (English)Independent thesis Advanced level (degree of Master (One Year)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Cloud computing is emerging very fast as it has potential in transforming IT industry by replacing local systems as well as in reshaping the design of IT hardware. It helps companies to share their infrastructure resources over internet ensuring better utilization of them. Nowadays developers do not need to deploy expensive hardware or human resource to maintain them because of cloud computing. Such elasticity of resources is new in the IT world. With the help of virtualization, clouds meet different types of customer demand as well as ensure better utilization of resources. There are two types of virtualization technique (dominant): (i) hardware level or system level virtualization, and (ii) operating system (OS) level virtualization. In the industry system level virtualization is commonly used. However it introduces some performance overhead because of its heavy weight nature. OS level virtualization replacing system level virtualization as it is of light weight nature and has lower performance overhead. Nevertheless, more research is necessary to compare these two technologies in case of performance overhead. In this thesis, a comparison is made in between these two technologies to find  the suitable one for real time industrial cloud. XEN is chosen to represent system level virtualization and Docker and OpenVZ for OS level virtualization. To compare them the considered performance criteria are: migration time, downtime, CPU consumption during migration, execution time. The evaluation showed that OS level virtualization technique OpenVZ is more suitable for industrial real time cloud as it has better migration utility, shorter downtime and lower CPU consumption during migration.

Place, publisher, year, edition, pages
2016. , 56 p.
National Category
Computer Systems
URN: urn:nbn:se:mdh:diva-32244OAI: diva2:943739
Subject / course
Computer Science
Available from: 2016-06-29 Created: 2016-06-28 Last updated: 2016-06-29Bibliographically approved

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