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Comparing Automatic Load Balancing using VMware DRS with a Human Expert
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Ericsson AB, SWE.
2016 (English)In: 2016 IEEE INTERNATIONAL CONFERENCE ON CLOUD ENGINEERING WORKSHOP (IC2EW), IEEE, 2016, p. 239-246Conference paper, Published paper (Refereed)
Abstract [en]

In recent years, there has been a rapid growth of interest in dynamic management of resources in virtualized systems. Virtualization provides great flexibility in terms of resource sharing but at the same time it also brings new challenges for load balancing using automatic migrations of virtual machines. In this paper, we have evaluated VMware's Distributed Resource Scheduler (DRS) in a number of realistic scenarios using multiple instances of a large industrial telecommunication application. We have measured the performance on the hosts before and after the migration in terms of CPU utilization, and compared DRS migrations with human expert migrations. According to our results, DRS with the most aggressive threshold gave us the best results. It could balance the load in 40% of cases while in other cases it could not balance the load properly. DRS did completely unnecessary migrations back and forth in some cases.

Place, publisher, year, edition, pages
IEEE, 2016. p. 239-246
Keywords [en]
Cloud Computing, Distributed Resource Scheduler (DRS), Virtual Machine Migration, Virtualization, VMware
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-13923DOI: 10.1109/IC2EW.2016.14ISI: 000392269400047ISBN: 978-1-5090-3684-4 (electronic)OAI: oai:DiVA.org:bth-13923DiVA, id: diva2:1076295
Conference
IEEE International Conference on Cloud Engineering (IC2E), APR 04-08, 2016, TU Berlin, Berlin, GERMANY
Part of project
Bigdata@BTH- Scalable resource-efficient systems for big data analytics, Knowledge FoundationAvailable from: 2017-02-22 Created: 2017-02-22 Last updated: 2021-05-05Bibliographically approved
In thesis
1. Performance Implications of Virtualization
Open this publication in new window or tab >>Performance Implications of Virtualization
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Virtualization is a component of cloud computing. Virtualization transforms traditional inflexible, complex infrastructure of individual servers, storage, and network hardware into a flexible virtual resource pool and increases IT agility, flexibility, and scalability while creating significant cost savings. Additional benefits of virtualization include, greater work mobility, increased performance and availability of resources, and automated operations. Many virtualization solutions have been implemented. There are plenty of cloud providers using different virtualization solutions to provide virtual machines (VMs) and containers, respectively. Various virtualization solutions have different performance overheads due to their various implementations of virtualization and supported features. A cloud user should understand performance overheads of different virtualization solutions and the impact on the performance caused by different virtualization features, so that it can choose appropriate virtualization solution, for the services to avoid degrading their quality of services (QoSs). In this research, we investigate the impacts of different virtualization technologies such as, container-based, and hypervisor-based virtualization as well as various virtualization features such as, over-allocation of resources, live migration, scalability, and distributed resource scheduling on the performance of various applications for instance, Cassandra NoSQL database, and a large telecommunication application. According to our results, hypervisor-based virtualization has many advantages and is more mature compare to the recently introduced container-based virtualization. However, impacts of the hypervisorbased virtualization on the performance of the applications is much higher than the container-based virtualization as well as the non-virtualized solution. The findings of this research should be of benefit to the ones who provide planning, designing, and implementing of the IT infrastructure.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2019. p. 211
Series
Blekinge Institute of Technology Doctoral Dissertation Series, ISSN 1653-2090 ; 1
Keywords
Cloud computing, Virtualization
National Category
Computer Systems
Identifiers
urn:nbn:se:bth-17217 (URN)978-91-7295-361-1 (ISBN)
Public defence
2019-01-16, J1650, Campus Gräsvik, Karlskrona, 13:00 (English)
Opponent
Supervisors
Available from: 2018-11-05 Created: 2018-11-02 Last updated: 2019-01-22Bibliographically approved

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Shirinbab, SogandLundberg, Lars

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