Arcabouço para Orquestração Osmótica de Cloud Slices
Resumo
Essa pesquisa baseia-se no paradigma slice-as-a-service proposto no projeto Novel Enablers for Cloud Slicing (NECOS). Assumindo o fornecimento de slices fim-a-fim, as quais são compostas por recursos vindos de multiplos provedores de infraestrutura, esse trabalho explora uma abordagem de orquestração osmótica, em um contexto de cloud slice, visando preservar o SLA durante o tempo de execução. O objetivo é desenvolver um mecanismo para orquestrar o rearranjo de recursos excedentes contidos em uma parte do slice pouco utilizada para uma parte que esteja mais sobrecarregada. Este artigo traz um experimento inicial para validar a operação do ambiente de testes construído.
Palavras-chave:
Gerenciamento de Redes, Slice como Serviço, Gerenciamento de Redes
Referências
Amazon Web Services (2018). Amazon elastic container service. https://aws. amazon.com/pt/ecs/. Online; acessado em 12-12-2018.
Apache Software Foundation (2018). Apache mesos. http://mesos.apache. org/. Online; acessado em 12-12-2018.
Carnevale, L., Celesti, A., Galletta, A., Dustdar, S., and Villari, M. (2018). From the cloud to edge and iot: a smart orchestration architecture for enabling osmotic com-puting. In 2018 32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA), pages 419-424. IEEE.
Casalicchio, E. (2019). Container orchestration: A survey. In Systems Modeling: Metho-dologies and Tools, pages 221-235. Springer.
Casalicchio, E. and Perciballi, V. (2017). Auto-scaling of containers: The impact of relative and absolute metrics. In Foundations and Applications of Self* Systems (FAS* W), 2017 IEEE 2nd International Workshops on, pages 207-214. IEEE.
Docker (2018). Swarm mode overview. https://docs.docker.com/engine/ swarm/. Online; acessado em 12-12-2018.
Freitas, L. A., Braga, V. G., Corrêa, S. L., Mamatas, L., Rothenberg, C. E., Clayman, S., and Cardoso, K. V. (2018). Slicing and allocation of transformable resources for the deployment of multiple virtualized infrastructure managers (vims). In 4th IEEE Con-ference on Network Softwarization and Workshops (NetSoft), pages 424-432. IEEE.
Kephart, J. O. and Chess, D. M. (2003). The vision of autonomic computing. Computer, 36(1):41-50.
Kubernetes (2018a). Horizontal pod autoscaler. https://kubernetes.io/docs/ tasks/run-application/horizontal-pod-autoscale/. Online; acessado em 21-11-2018.
Kubernetes (2018b). Pod overview. https://kubernetes.io/docs/ concepts/workloads/pods/pod-overview/. Online; acessado em 21-12-2018.
Kubernetes (2018c). Production-grade container orchestration. https:// kubernetes.io/. Online; acessado em 12-12-2018.
LeCun, Y., Bengio, Y., and Hinton, G. (2015). Deep learning. nature, 521(7553):436.
Merkel, D. (2014). Docker: lightweight linux containers for consistent development and deployment. Linux Journal, 2014(239):2.
Mesosphere (2018). Marathon: A container orchestration platform for mesos and dc/os. https://mesosphere.github.io/marathon/. Online; acessado em 12-12-2018.
Morshed, A., Jayaraman, P. P., Sellis, T., Georgakopoulos, D., Villari, M., and Ranjan, R. (2017). Deep osmosis: Holistic distributed deep learning in osmotic computing. IEEE Cloud Computing, 4(6):22-32.
Murphy, E. (2018). Welcome to openstack documentation. https://docs. openstack.org. Online; acessado em 16-03-2019.
NECOS (2018a). D3.1: Necos system architecture and platform specification. v1. http: //www.maps.upc.edu/public/NECOS\%20D3.1\%20final.pdf. On-line; acessado em 12-03-2019.
NECOS (2018b). Novel enablers for cloud slicing. http://www.h2020-necos. eu/. Online; acessado em 12-12-2018.
Netto, M. A., Cardonha, C., Cunha, R. L., and Assunçao, M. D. (2014). Evaluating auto-scaling strategies for cloud computing environments. In Modelling, Analysis & Si-mulation of Computer and Telecommunication Systems (MASCOTS), 2014 IEEE 22nd International Symposium on, pages 187-196. IEEE.
Pasquini, R. and Stadler, R. (2017). Learning end-to-end application qos from openflow switch statistics. In IEEE Network Softwarization (NetSoft), pages 1-9. IEEE.
Prometheus (2019). Overview prometheus. https://prometheus.io/docs/ introduction/overview/. Online; acessado em 16-03-2019.
Qu, C., Calheiros, R. N., and Buyya, R. (2018). Auto-scaling web applications in clouds: A taxonomy and survey. ACM Computing Surveys (CSUR), 51(4):73.
Sandvine (2018). The global internet phenomena report. https://www.sandvine.
com/hubfs/downloads/phenomena/2018-phenomena-report.pdf. Online; acessado em 18-03-2019.
Sciancalepore, V., Cirillo, F., and Costa-Perez, X. (2017). Slice as a service (slaas) optimal iot slice resources orchestration. In GLOBECOM 2017-2017 IEEE Global Communi-cations Conference, pages 1-7. IEEE.
Sharma, V., Srinivasan, K., Jayakody, D. N. K., Rana, O., and Kumar, R. (2017). Managing service-heterogeneity using osmotic computing. arXiv preprint ar-Xiv:1704.04213.
Silva, F. S. D., Lemos, M. O., Medeiros, A., Neto, A. V., Pasquini, R., Moura, D., Rothen-berg, C., Mamatas, L., Correa, S. L., Cardoso, K. V., et al. (2018). Necos project: Towards lightweight slicing of cloud federated infrastructures. In 2018 4th IEEE Con-ference on Network Softwarization and Workshops (NetSoft), pages 406-414. IEEE.
Sodagar, I. (2011). The mpeg-dash standard for multimedia streaming over the internet. IEEE MultiMedia, 18(4):62-67.
Villari, M., Fazio, M., Dustdar, S., Rana, O., and Ranjan, R. (2016). Osmotic computing: A new paradigm for edge/cloud integration. IEEE Cloud Computing, 3(6):76-83.
VLC (2019). Vlc media player. https://www.videolan.org/vlc/. Online; acessado em 16-03-2019.
Apache Software Foundation (2018). Apache mesos. http://mesos.apache. org/. Online; acessado em 12-12-2018.
Carnevale, L., Celesti, A., Galletta, A., Dustdar, S., and Villari, M. (2018). From the cloud to edge and iot: a smart orchestration architecture for enabling osmotic com-puting. In 2018 32nd International Conference on Advanced Information Networking and Applications Workshops (WAINA), pages 419-424. IEEE.
Casalicchio, E. (2019). Container orchestration: A survey. In Systems Modeling: Metho-dologies and Tools, pages 221-235. Springer.
Casalicchio, E. and Perciballi, V. (2017). Auto-scaling of containers: The impact of relative and absolute metrics. In Foundations and Applications of Self* Systems (FAS* W), 2017 IEEE 2nd International Workshops on, pages 207-214. IEEE.
Docker (2018). Swarm mode overview. https://docs.docker.com/engine/ swarm/. Online; acessado em 12-12-2018.
Freitas, L. A., Braga, V. G., Corrêa, S. L., Mamatas, L., Rothenberg, C. E., Clayman, S., and Cardoso, K. V. (2018). Slicing and allocation of transformable resources for the deployment of multiple virtualized infrastructure managers (vims). In 4th IEEE Con-ference on Network Softwarization and Workshops (NetSoft), pages 424-432. IEEE.
Kephart, J. O. and Chess, D. M. (2003). The vision of autonomic computing. Computer, 36(1):41-50.
Kubernetes (2018a). Horizontal pod autoscaler. https://kubernetes.io/docs/ tasks/run-application/horizontal-pod-autoscale/. Online; acessado em 21-11-2018.
Kubernetes (2018b). Pod overview. https://kubernetes.io/docs/ concepts/workloads/pods/pod-overview/. Online; acessado em 21-12-2018.
Kubernetes (2018c). Production-grade container orchestration. https:// kubernetes.io/. Online; acessado em 12-12-2018.
LeCun, Y., Bengio, Y., and Hinton, G. (2015). Deep learning. nature, 521(7553):436.
Merkel, D. (2014). Docker: lightweight linux containers for consistent development and deployment. Linux Journal, 2014(239):2.
Mesosphere (2018). Marathon: A container orchestration platform for mesos and dc/os. https://mesosphere.github.io/marathon/. Online; acessado em 12-12-2018.
Morshed, A., Jayaraman, P. P., Sellis, T., Georgakopoulos, D., Villari, M., and Ranjan, R. (2017). Deep osmosis: Holistic distributed deep learning in osmotic computing. IEEE Cloud Computing, 4(6):22-32.
Murphy, E. (2018). Welcome to openstack documentation. https://docs. openstack.org. Online; acessado em 16-03-2019.
NECOS (2018a). D3.1: Necos system architecture and platform specification. v1. http: //www.maps.upc.edu/public/NECOS\%20D3.1\%20final.pdf. On-line; acessado em 12-03-2019.
NECOS (2018b). Novel enablers for cloud slicing. http://www.h2020-necos. eu/. Online; acessado em 12-12-2018.
Netto, M. A., Cardonha, C., Cunha, R. L., and Assunçao, M. D. (2014). Evaluating auto-scaling strategies for cloud computing environments. In Modelling, Analysis & Si-mulation of Computer and Telecommunication Systems (MASCOTS), 2014 IEEE 22nd International Symposium on, pages 187-196. IEEE.
Pasquini, R. and Stadler, R. (2017). Learning end-to-end application qos from openflow switch statistics. In IEEE Network Softwarization (NetSoft), pages 1-9. IEEE.
Prometheus (2019). Overview prometheus. https://prometheus.io/docs/ introduction/overview/. Online; acessado em 16-03-2019.
Qu, C., Calheiros, R. N., and Buyya, R. (2018). Auto-scaling web applications in clouds: A taxonomy and survey. ACM Computing Surveys (CSUR), 51(4):73.
Sandvine (2018). The global internet phenomena report. https://www.sandvine.
com/hubfs/downloads/phenomena/2018-phenomena-report.pdf. Online; acessado em 18-03-2019.
Sciancalepore, V., Cirillo, F., and Costa-Perez, X. (2017). Slice as a service (slaas) optimal iot slice resources orchestration. In GLOBECOM 2017-2017 IEEE Global Communi-cations Conference, pages 1-7. IEEE.
Sharma, V., Srinivasan, K., Jayakody, D. N. K., Rana, O., and Kumar, R. (2017). Managing service-heterogeneity using osmotic computing. arXiv preprint ar-Xiv:1704.04213.
Silva, F. S. D., Lemos, M. O., Medeiros, A., Neto, A. V., Pasquini, R., Moura, D., Rothen-berg, C., Mamatas, L., Correa, S. L., Cardoso, K. V., et al. (2018). Necos project: Towards lightweight slicing of cloud federated infrastructures. In 2018 4th IEEE Con-ference on Network Softwarization and Workshops (NetSoft), pages 406-414. IEEE.
Sodagar, I. (2011). The mpeg-dash standard for multimedia streaming over the internet. IEEE MultiMedia, 18(4):62-67.
Villari, M., Fazio, M., Dustdar, S., Rana, O., and Ranjan, R. (2016). Osmotic computing: A new paradigm for edge/cloud integration. IEEE Cloud Computing, 3(6):76-83.
VLC (2019). Vlc media player. https://www.videolan.org/vlc/. Online; acessado em 16-03-2019.
Publicado
25/09/2019
Como Citar
GUARDIEIRO PEREIRA REZENDE, Aryadne ; MARQUES, Gustavo Silveira; FIALHO, Raquel ; PASQUINI, Rafael .
Arcabouço para Orquestração Osmótica de Cloud Slices. In: WORKSHOP DE TEORIA, TECNOLOGIAS E APLICAÇÕES DE SLICING PARA INFRAESTRUTURAS SOFTWARIZADAS (WSLICE), 1. , 2019, Gramado.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 28-41.
DOI: https://doi.org/10.5753/wslice.2019.7720.
