Identificação de gargalos de desempenho em ambientes virtuais para uso em computação em nuvem
Abstract
Cloud computing uses virtualization to manage and handle with resources with no interaction to users raising the performance of servers and/or physical resources. Virtualization allows many users have independent machines in a same server, bringing benefits as resource isolation. However, depending on a workload in a virtual machine, this one can put down the performance of another virtual machines. Thus, is essential to identify when these interferences occur and how to avoid them. Our proposal is to use three basic types of workload (memory, CPU and I/O) to verify among the KVM or Xen what is the most suitable for the activities of the cloud. We find that there is no good virtualizer but rather a virtualizer suitable for each type of workload.
References
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VMware (2014). What is virtualization? https://www.vmware.com/br/virtualization/virtualization-basics/what-is-virtualization. Accessed: 2014-01-30.
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Benevenuto, F., Ismael Jr, J., and Almeida, J. (2004). Quantitative evaluation of unstructured peer-to-peer architectures. In Proceedings of the 2004 International Workshop on Hot Topics in Peer-to-Peer Systems, HOT-P2P '04, pages 56–65, Washington, DC, USA. IEEE Computer Society.
Daniels, J. (2009). Server virtualization architecture and implementation. Crossroads, 16(1):8–12.
Head, M., Kochut, A., Schulz, C., and Shaikh, H. (2010). Virtual hypervisor: Enabling fair and economical resource partitioning in cloud environments. In Network Operations and Management Symposium (NOMS), 2010 IEEE, pages 104–111.
Jain, R. (1991). The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling. Wiley Professional Computing. Wiley.
Jiang, W., Zhou, Y., Cui, Y., Feng, W., Chen, Y., Shi, Y., and Wu, Q. (2009). Cfs optimizations to kvm threads on multi-core environment. In Parallel and Distributed Systems (ICPADS), 2009 15th International Conference on, pages 348–354.
Khan, A., Othman, M., Madani, S., and Khan, S. (2014). A survey of mobile cloud computing application models. Communications Surveys Tutorials, IEEE, 16(1):393– 413.
Koh, Y., Knauerhase, R., Brett, P., Bowman, M., Wen, Z., and Pu, C. (2007). An analysis of performance interference effects in virtual environments. In Performance Analysis of Systems Software, 2007. ISPASS 2007. IEEE International Symposium on, pages 200–209.
Lee, M., Krishnakumar, A. S., Krishnan, P., Singh, N., and Yajnik, S. (2010). Supporting soft real-time tasks in the xen hypervisor. SIGPLAN Not., 45(7):97–108.
Matthews, J. N., Hu, W., Hapuarachchi, M., Deshane, T., Dimatos, D., Hamilton, G., and McCabe, M. (2007). Quantifying the performance isolation properties of virtualization systems. In Experimental Computer Science on Experimental Computer Science, ecs'07, pages 5–5, Berkeley, CA, USA. USENIX Association.
Niyato, D. (2011). Optimization-based virtual machine manager for private cloud computing. In Cloud Computing Technology and Science (CloudCom), 2011 IEEE Third International Conference on, pages 99–106.
Santos, R. and Charão, A. S. (2008). Análise comparativa de desempenho do hipervisor xen: Paravirtualização versus virtualização total. Universidade Federal de Santa Maria. Brasil.
Somani, G. and Chaudhary, S. (2010). Performance isolation and scheduler behavior. In Parallel Distributed and Grid Computing (PDGC), 2010 1st International Conference on, pages 272–277.
Srinivasan, S., Raja, K., and Muthuselvan, S. (2012). Futuristic assimilation of cloud computing platforms and its services. In Emerging Trends in Electrical Engineering and Energy Management (ICETEEEM), 2012 International Conference on, pages 178– 180.
VMware (2014). What is virtualization? https://www.vmware.com/br/virtualization/virtualization-basics/what-is-virtualization. Accessed: 2014-01-30.
White, J. and Pilbeam, A. (2010). A survey of virtualization technologies with perfor mance testing. CoRR, abs/1010.3233.
Zaghloul, S. (2013). The mutual effect of virtualization and parallelism in a cloud envi ronment. In AFRICON, 2013, pages 1–5.
Zhang, Q., Cheng, L., and Boutaba, R. (2010). Cloud computing: state-of-the-art and research challenges. Journal of internet services and applications, 1(1):7–18.
Published
2014-07-28
How to Cite
FERREIRA, Carlos; RIBEIRO, João; B. JÚNIOR, Wellington; ESTRELLA, Júlio; L. FILHO, Dionísio; PEIXOTO, Maycon.
Identificação de gargalos de desempenho em ambientes virtuais para uso em computação em nuvem. In: WORKSHOP ON PERFORMANCE OF COMPUTER AND COMMUNICATION SYSTEMS (WPERFORMANCE), 13. , 2014, Brasília.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2014
.
p. 164-177.
ISSN 2595-6167.
