Escalonamento orientado por qualidade de serviço em infraestruturas de computação na nuvem
Resumo
Provedores de computação na nuvem oferecem múltiplas classes de serviço para lidar com a heterogeneidade da carga de trabalho. Essas classes são diferenciadas pela Qualidade de Serviço (QoS) esperada, que é definida em termos de Objetivos de Níveis de Serviço (SLO). Uma política de escalonamento baseada em prioridades é uma forma comum de permitir que requisições de diferentes classes alcancem a QoS desejada. No entanto, em períodos de contenção de recursos, a QoS oferecida pode ser injusta para certos usuários. Este trabalho propõe o escalonamento orientado por QoS, que usa uma política baseada no SLO e na QoS de cada requisição em um dado momento. Experimentos de simulação usando dados de um sistema real em produção foram executados para comparar as diferentes políticas e mostrar os benefícios do escalonador proposto.Referências
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Carvalho, M., Cirne, W., Brasileiro, F., and Wilkes, J. (2014). Long-term slos for reclaimed cloud computing resources. In Proceedings of the ACM Symposium on Cloud Computing, SOCC ’14, pages 20:1–20:13, New York, NY, USA. ACM.
Carvalho, M., Menascé, D., and Brasileiro, F. (2015). Prediction-based admission control for iaas clouds with multiple service classes. In Cloud Computing Technology and Science (CloudCom), 2015 IEEE 7th International Conference on, pages 82–90. IEEE.
Cirne,W. and Frachtenberg, E. (2012).Web-scale job scheduling. InWorkshop on Job Scheduling Strategies for Parallel Processing, pages 1–15. Springer.
Curino, C., Difallah, D. E., Douglas, C., Krishnan, S., Ramakrishnan, R., and Rao, S. (2014). Reservationbased scheduling: If you’re late don’t blame us! In Proceedings of the ACM Symposium on Cloud Computing, SOCC ’14, pages 2:1–2:14, New York, NY, USA. ACM.
da Silva, G. F., Brasileiro, F., Lopes, R., Carvalho, M., and Turull, D. (2017). Method and resource manager for scheduling of instances in a data centre.
da Silva, G. F., Brasileiro, F. V., Lopes, R. V., Morais, F. J. A., Carvalho, M., and Turull, D. (2020). Qosdriven scheduling in the cloud. J. Internet Serv. Appl., 11(1):9.
da Silva, G. F., Lopes, R., Brasileiro, F., Carvalho, M., Morais, F., Mafra, J., and Turull, D. (2019). Escalonamento justo em infraestruturas de nuvem com múltiplas classes de serviço. In Anais do XXXVII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, pages 636–649, Porto Alegre, RS, Brasil. SBC.
Delimitrou, C., Sanchez, D., and Kozyrakis, C. (2015). Tarcil: reconciling scheduling speed and quality in large shared clusters. In Proceedings of the Sixth ACM Symposium on Cloud Computing, pages 97–110. ACM.
Dubey, S. and Agrawal, S. (2013). Qos driven task scheduling in cloud computing. Int. J. Comput. Appl. Technol. Res, 2(5):595–600.
Karanasos, K., Rao, S., Curino, C., Douglas, C., Chaliparambil, K., Fumarola, G. M., Heddaya, S., Ramakrishnan, R., and Sakalanaga, S. (2015). Mercury: Hybrid centralized and distributed scheduling in large shared clusters. In USENIX Annual Technical Conference, pages 485–497.
Marshall, P., Keahey, K., and Freeman, T. (2011). Improving utilization of infrastructure clouds. In Proceedings of the 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID ’11, pages 205–214, Washington, DC, USA. IEEE Computer Society.
Schwarzkopf, M., Konwinski, A., Abd-El-Malek, M., and Wilkes, J. (2013). Omega: Flexible, scalable schedulers for large compute clusters. In Proceedings of the 8th ACM European Conference on Computer Systems, EuroSys ’13, pages 351–364, New York, NY, USA. ACM.
Vavilapalli, V. K., Murthy, A. C., Douglas, C., Agarwal, S., Konar, M., Evans, R., Graves, T., Lowe, J., Shah, H., Seth, S., et al. (2013). Apache hadoop yarn: Yet another resource negotiator. In Proceedings of the 4th annual Symposium on Cloud Computing, page 5. ACM.
Verma, A., Korupolu, M., and Wilkes, J. (2014). Evaluating job packing in warehouse-scale computing. In 2014 IEEE Int’l Conf. on Cluster Computing, CLUSTER 2014, Madrid, Spain, pages 48–56.
Verma, A., Pedrosa, L., Korupolu, M., Oppenheimer, D., Tune, E., and Wilkes, J. (2015). Large-scale cluster management at google with borg. In Proceedings of the Tenth European Conference on Computer Systems, EuroSys ’15, pages 18:1–18:17, New York, NY, USA. ACM.
Xu, J. and Zhu, C. (2015). Optimal pricing and capacity planning of a new economy cloud computing service class. In 2015 International Conference on Cloud and Autonomic Computing, pages 149–157. IEEE.
Burns, B., Grant, B., Oppenheimer, D., Brewer, E., and Wilkes, J. (2016). Borg, omega, and kubernetes. Commun. ACM, 59(5):50–57.
Carvalho, M., Cirne, W., Brasileiro, F., and Wilkes, J. (2014). Long-term slos for reclaimed cloud computing resources. In Proceedings of the ACM Symposium on Cloud Computing, SOCC ’14, pages 20:1–20:13, New York, NY, USA. ACM.
Carvalho, M., Menascé, D., and Brasileiro, F. (2015). Prediction-based admission control for iaas clouds with multiple service classes. In Cloud Computing Technology and Science (CloudCom), 2015 IEEE 7th International Conference on, pages 82–90. IEEE.
Cirne,W. and Frachtenberg, E. (2012).Web-scale job scheduling. InWorkshop on Job Scheduling Strategies for Parallel Processing, pages 1–15. Springer.
Curino, C., Difallah, D. E., Douglas, C., Krishnan, S., Ramakrishnan, R., and Rao, S. (2014). Reservationbased scheduling: If you’re late don’t blame us! In Proceedings of the ACM Symposium on Cloud Computing, SOCC ’14, pages 2:1–2:14, New York, NY, USA. ACM.
da Silva, G. F., Brasileiro, F., Lopes, R., Carvalho, M., and Turull, D. (2017). Method and resource manager for scheduling of instances in a data centre.
da Silva, G. F., Brasileiro, F. V., Lopes, R. V., Morais, F. J. A., Carvalho, M., and Turull, D. (2020). Qosdriven scheduling in the cloud. J. Internet Serv. Appl., 11(1):9.
da Silva, G. F., Lopes, R., Brasileiro, F., Carvalho, M., Morais, F., Mafra, J., and Turull, D. (2019). Escalonamento justo em infraestruturas de nuvem com múltiplas classes de serviço. In Anais do XXXVII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, pages 636–649, Porto Alegre, RS, Brasil. SBC.
Delimitrou, C., Sanchez, D., and Kozyrakis, C. (2015). Tarcil: reconciling scheduling speed and quality in large shared clusters. In Proceedings of the Sixth ACM Symposium on Cloud Computing, pages 97–110. ACM.
Dubey, S. and Agrawal, S. (2013). Qos driven task scheduling in cloud computing. Int. J. Comput. Appl. Technol. Res, 2(5):595–600.
Karanasos, K., Rao, S., Curino, C., Douglas, C., Chaliparambil, K., Fumarola, G. M., Heddaya, S., Ramakrishnan, R., and Sakalanaga, S. (2015). Mercury: Hybrid centralized and distributed scheduling in large shared clusters. In USENIX Annual Technical Conference, pages 485–497.
Marshall, P., Keahey, K., and Freeman, T. (2011). Improving utilization of infrastructure clouds. In Proceedings of the 2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGRID ’11, pages 205–214, Washington, DC, USA. IEEE Computer Society.
Schwarzkopf, M., Konwinski, A., Abd-El-Malek, M., and Wilkes, J. (2013). Omega: Flexible, scalable schedulers for large compute clusters. In Proceedings of the 8th ACM European Conference on Computer Systems, EuroSys ’13, pages 351–364, New York, NY, USA. ACM.
Vavilapalli, V. K., Murthy, A. C., Douglas, C., Agarwal, S., Konar, M., Evans, R., Graves, T., Lowe, J., Shah, H., Seth, S., et al. (2013). Apache hadoop yarn: Yet another resource negotiator. In Proceedings of the 4th annual Symposium on Cloud Computing, page 5. ACM.
Verma, A., Korupolu, M., and Wilkes, J. (2014). Evaluating job packing in warehouse-scale computing. In 2014 IEEE Int’l Conf. on Cluster Computing, CLUSTER 2014, Madrid, Spain, pages 48–56.
Verma, A., Pedrosa, L., Korupolu, M., Oppenheimer, D., Tune, E., and Wilkes, J. (2015). Large-scale cluster management at google with borg. In Proceedings of the Tenth European Conference on Computer Systems, EuroSys ’15, pages 18:1–18:17, New York, NY, USA. ACM.
Xu, J. and Zhu, C. (2015). Optimal pricing and capacity planning of a new economy cloud computing service class. In 2015 International Conference on Cloud and Autonomic Computing, pages 149–157. IEEE.
Publicado
16/08/2021
Como Citar
SILVA, Giovanni Farias da; BRASILEIRO, Francisco; LOPES, Raquel.
Escalonamento orientado por qualidade de serviço em infraestruturas de computação na nuvem. In: CONCURSO DE TESES E DISSERTAÇÕES - SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 39. , 2021, Uberlândia.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 137-144.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc_estendido.2021.17164.
