Um Monitor de Consumo Energético para Computação em Nuvem na Ferramenta OpenNebula
Resumo
Nuvens computacionais consomem grandes quantidades de energia elétrica, sendo responsáveis pela emissão de pelo menos 2% do dióxido de carbono mundial. Por outro lado, as ferramentas de gerenciamento de nuvens atuais não dispõem de recursos para monitorar o consumo energético de suas infraestruturas, bem como não oferecem informações sobre a demanda de energia elétrica, sendo este uma parte integrante do custo de manutenção da nuvem. Portanto, este artigo propõe um modelo de monitoramento energético para nuvens computacionais. Foi criado um addon denominado Monitor Energético (ME) para monitorar o consumo energético em data centers virtualizados, através de Kernel-based Virtual Machine e geridos por OpenNebula. Os experimentos foram realizados com a ferramenta Sysbench para o estresse proposital do ambiente de testes, aonde os resultados comprovaram o bom funcionamento da nossa ferramenta e que ela possui uma visualização intuitiva do monitoramento.Referências
Alexey Kopytov (2016). Sysbench in Launchpad. https://launchpad.net/
Bertran, R., Becerra, Y., Carrera, D., Beltran, V., Gonzílez, M., Martorell, X., Navarro, N., Torres, J., and Ayguadé, E. (2012). Energy accounting for shared virtualized en- vironments under dvfs using pmc-based power models. Future Gener. Comput. Syst., 28(2):457–468.
Bourdon, A., Noureddine, A., Rouvoy, R., and Seinturier, L. (2011). Linux: Understan- ding Process-Level Power Consumption. Green Computing Middleware (GCM'2011).
Fenopix (2016). CanvasJS: Beautiful HTML5 JavaScript Charts. http://canvasjs.com.
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Kansal, A., Zhao, F., Liu, J., Kothari, N., and Bhattacharya, A. A. (2010). Virtual machine power metering and provisioning. In Proceedings of the 1st ACM Symposium on Cloud Computing, SoCC '10, pages 39–50, New York, NY, USA. ACM.
Marcu, M., Tudor, D., and Fuicu, S. (2011). Power consumption and temperature me- asurement of virtualization solutions. In Thermal Investigations of ICs and Systems (THERMINIC), 2011 17th International Workshop on, pages 1–6.
OpenNebula Community (2016). OpenNebula, Flexible Enterprise Cloud Made Simple. http://opennebula.org/.
Roveda, D., Vogel, A., and Griebler, D. (2015). Understanding, Discussing and Analy- zing the OpenNebula and OpenStack's IaaS Management Layers. Revista Eletronica Argentina-Brasil de Tecnologias da Informacao e da Comunicacao, 3(1):15.
Spirals Research Group (2016). PowerAPI. http://www.powerapi.org.
The Apache Software Foundation (2016). Welcome! - The Apache HTTP Server Project. https://httpd.apache.org/.
The PHP Group (2016). PHP: Hypertext Preprocessor. http://php.net/.
VMWare Inc. (2015). VMware Virtualization for Desktop and Server. http://www.vmware.com/.
Vogel, A., Griebler, D., Maron, C. A. F., Schepke, C., and Fernandes, L. G. (2016). Private IaaS Clouds: A Comparative Analysis of OpenNebula, CloudStack and OpenStack. In 24rd Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pages 672–679, Heraklion Crete, Greece. IEEE.
Watts up? (2015). Watts up? Pro. http://www.wattsupmeters.com.
Wen, C., Long, X., Yang, Y., Ni, F., and Mu, Y. (2013). System power model and virtual machine power metering for cloud computing pricing. In Intelligent System Design and Engineering Applications (ISDEA), 2013 Third International Conference on, pages 1379–1382.
Bertran, R., Becerra, Y., Carrera, D., Beltran, V., Gonzílez, M., Martorell, X., Navarro, N., Torres, J., and Ayguadé, E. (2012). Energy accounting for shared virtualized en- vironments under dvfs using pmc-based power models. Future Gener. Comput. Syst., 28(2):457–468.
Bourdon, A., Noureddine, A., Rouvoy, R., and Seinturier, L. (2011). Linux: Understan- ding Process-Level Power Consumption. Green Computing Middleware (GCM'2011).
Fenopix (2016). CanvasJS: Beautiful HTML5 JavaScript Charts. http://canvasjs.com.
Fiasco (2015). L4Re – L4 Runtime Environment. http://l4re.org/.
jQuery Foundation (2016). jQuery Foundation. https://jquery.org/.
Kansal, A., Zhao, F., Liu, J., Kothari, N., and Bhattacharya, A. A. (2010). Virtual machine power metering and provisioning. In Proceedings of the 1st ACM Symposium on Cloud Computing, SoCC '10, pages 39–50, New York, NY, USA. ACM.
Marcu, M., Tudor, D., and Fuicu, S. (2011). Power consumption and temperature me- asurement of virtualization solutions. In Thermal Investigations of ICs and Systems (THERMINIC), 2011 17th International Workshop on, pages 1–6.
OpenNebula Community (2016). OpenNebula, Flexible Enterprise Cloud Made Simple. http://opennebula.org/.
Roveda, D., Vogel, A., and Griebler, D. (2015). Understanding, Discussing and Analy- zing the OpenNebula and OpenStack's IaaS Management Layers. Revista Eletronica Argentina-Brasil de Tecnologias da Informacao e da Comunicacao, 3(1):15.
Spirals Research Group (2016). PowerAPI. http://www.powerapi.org.
The Apache Software Foundation (2016). Welcome! - The Apache HTTP Server Project. https://httpd.apache.org/.
The PHP Group (2016). PHP: Hypertext Preprocessor. http://php.net/.
VMWare Inc. (2015). VMware Virtualization for Desktop and Server. http://www.vmware.com/.
Vogel, A., Griebler, D., Maron, C. A. F., Schepke, C., and Fernandes, L. G. (2016). Private IaaS Clouds: A Comparative Analysis of OpenNebula, CloudStack and OpenStack. In 24rd Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pages 672–679, Heraklion Crete, Greece. IEEE.
Watts up? (2015). Watts up? Pro. http://www.wattsupmeters.com.
Wen, C., Long, X., Yang, Y., Ni, F., and Mu, Y. (2013). System power model and virtual machine power metering for cloud computing pricing. In Intelligent System Design and Engineering Applications (ISDEA), 2013 Third International Conference on, pages 1379–1382.
Publicado
05/10/2016
Como Citar
LEIRIA, Raul; SCHEPKE, Claudio; DE MELLO, Aline; GRIEBLER, Daivan.
Um Monitor de Consumo Energético para Computação em Nuvem na Ferramenta OpenNebula. In: SIMPÓSIO EM SISTEMAS COMPUTACIONAIS DE ALTO DESEMPENHO (SSCAD), 17. , 2016, Aracajú.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2016
.
p. 169-178.
DOI: https://doi.org/10.5753/wscad.2016.14257.
