Migração proativa de máquinas virtuais para aplicações móveis na computação em névoa
Resumo
Aplicações frequentemente utilizam nuvens como suporte ao processamento e armazenamento. A diversidade de aplicações móveis traz também uma diversidade de requisitos de qualidade de serviço, tais como requisitos estritos de atraso e disponibilidade de acesso. A computação em névoa inclui recursos computacionais na borda da rede para que o atraso no tempo de resposta possa ser reduzido. Neste artigo, apresentamos uma política de migração proativa de máquinas virtuais em ambientes de névoa a fim de melhorar o gerenciamento dos recursos computacionais utilizados pelos véıculos conectados a essa infraestrutura. Simulações sugerem que a utilização de predições sobre o trajeto futuro do véıculo pode melhorar o gerenciamento de recursos da névoa, mantendo a máquina virtual do usuário em dispositivos de névoa tão próximos quanto possível do trajeto do automóvel. A solução apresentada reduz o número de migrações realizadas durante o trajeto do usuário sem prejudicar o tempo de resposta da máquina virtual alocada na névoa.
Referências
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Codeca, L., Frank, R., and Engel, T. (2015). Luxembourg sumo trafc (lust) scenario: 24 hours of mobility for vehicular networking research. In Vehicular Networking Conference (VNC), 2015 IEEE, pages 1–8. IEEE.
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Kim, O. T. T., Tri, N. D., Nguyen, V., and Hong, C. S. (2015). Addressing virtual machine migration problems in cloud based vehicular networks.
Lopes, M. M., Higashino, W. A., Capretz, M. A., and Bittencourt, L. F. (2017). Myifogsim: A simulator for virtual machine migration in fog computing. In Companion Proceedings of the10th International Conference on Utility and Cloud Computing, UCC ’17 Companion, pages 47–52, New York, NY, USA. ACM.
Malandrino, F., Casetti, C., Chiasserini, C.-F., and Fiore, M. (2014). Content download in vehicular networks in presence of noisy mobility prediction. IEEE Transactions on Mobile Computing, 13(5):1007–1021.
Mell, P. M. and Grance, T. (2011). SP 800-145. The NIST Denition of Cloud Computing. Technical report, Gaithersburg, MD, United States.
Mustafa, A. M., Abubakr, O. M., Ahmadien, O., Ahmedin, A., and Mokhtar, B. (2017). Mobility prediction for efcient resources management in vehicular cloud computing. In Mobile Cloud Computing, Services, and Engineering, 5th IEEE International Conference on, pages 53–59. IEEE.
Nabi, T., Mittal, P., Azimi, P., Dig, D., and Tilevich, E. (2015). Assessing the benets of computational ofoading in mobile-cloud applications. In Proceedings of the 3rd International Workshop on Mobile Development Lifecycle, pages 17–24. ACM.
Puliato, C., Mingozzi, E., and Anastasi, G. (2017). Fog computing for the internet of In Smart Computing (SMARTCOMP), 2017 mobile things: issues and challenges. IEEE International Conference on, pages 1–6. IEEE.
Refaat, T. K., Kantarci, B., and Mouftah, H. T. (2014). Dynamic virtual machine migration in a vehicular cloud. In 2014 IEEE Symposium on Computers and Communications (ISCC), pages 1–6. IEEE.
Roman, R., Lopez, J., and Mambo, M. (2016). Mobile edge computing, fog et al.: A survey and analysis of security threats and challenges. Future Generation Computer Systems.
Satyanarayanan, M., Bahl, P., Caceres, R., and Davies, N. (2009). The case for vm-based cloudlets in mobile computing. IEEE pervasive Computing, 8(4):14–23.
Shin, W., Min, B.-Y., and Kim, D. K. (2015). Vehicaching: Embracing user request on vehicle route with proactive data transportation. In 2015 IEEE 81st Vehicular Technology Conference (VTC Spring), pages 1–5. IEEE.
Taleb, T. and Ksentini, A. (2013). Follow me cloud: interworking federated clouds and distributed mobile networks. IEEE Network, 27(5):12–19.
Yan, H., Wan, J., Wang, Y., Wang, Z., and Song, Z. (2013). Vehicular cyber-physical systems with mobile cloud computing support. In International Conference on Cloud Computing, pages 27–35. Springer.
Yao, H., Bai, C., Zeng, D., Liang, Q., and Fan, Y. (2015). Migrate or not? exploring virtual machine migration in roadside cloudlet-based vehicular cloud. Concurrency and Computation: Practice and Experience, 27(18):5780–5792.
Yu, R., Zhang, Y., Gjessing, S., Xia, W., and Yang, K. (2013a). Toward cloud-based vehicular networks with efcient resource management. IEEE Network, 27(5):48–55.
Yu, R., Zhang, Y., Wu, H., Chatzimisios, P., and Xie, S. (2013b). Virtual machine live migration for pervasive services in cloud-assisted vehicular networks. In Communications and Networking in China (CHINACOM), 2013 8th International ICST Conference on, pages 540–545. IEEE.
Batista, D. M., Goldman, A., Hirata, R., Kon, F., Costa, F. M., and Endler, M. (2016). Interscity: Addressing future internet research challenges for smart cities. In Network of the Future (NOF), 2016 7th International Conference on the, pages 1–6. IEEE.
Bittencourt, L. F., Lopes, M. M., Petri, I., and Rana, O. F. (2015). Towards virtual machine migration in fog computing. In P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2015 10th International Conference on, pages 1–8. IEEE.
Bonomi, F., Milito, R., Zhu, J., and Addepalli, S. (2012). Fog computing and its role in the internet of things. In Proceedings of the rst edition of the MCC workshop on Mobile cloud computing, pages 13–16. ACM.
Codeca, L., Frank, R., and Engel, T. (2015). Luxembourg sumo trafc (lust) scenario: 24 hours of mobility for vehicular networking research. In Vehicular Networking Conference (VNC), 2015 IEEE, pages 1–8. IEEE.
Gomes, A. S., Braun, T., and Monteiro, E. (2016a). Enhanced caching strategies at the edge of lte mobile networks. In 2016 IFIP Networking Conference (IFIP Networking) and Workshops, pages 341–349. IEEE.
Gomes, A. S., Fonseca, V., Sousa, B., Palma, D., Simoes, P., Monteiro, E., and Cordeiro, L. (2016b). A mobile follow-me cloud content caching model. In NOMS 2016-2016 IEEE/IFIP Network Operations and Management Symposium, pages 763–766. IEEE.
Gupta, H., Vahid Dastjerdi, A., Ghosh, S. K., and Buyya, R. (2017). ifogsim: A toolkit for modeling and simulation of resource management techniques in the internet of things, edge and fog computing environments. Software: Practice and Experience, 47(9):1275–1296.
Júnior, W., Henrique, A., and Lopes, K. (2016). Avaliação de desempenho da técnica de ofoading computacional em nuvens móveis. wperformance.
Kim, O. T. T., Tri, N. D., Nguyen, V., and Hong, C. S. (2015). Addressing virtual machine migration problems in cloud based vehicular networks.
Lopes, M. M., Higashino, W. A., Capretz, M. A., and Bittencourt, L. F. (2017). Myifogsim: A simulator for virtual machine migration in fog computing. In Companion Proceedings of the10th International Conference on Utility and Cloud Computing, UCC ’17 Companion, pages 47–52, New York, NY, USA. ACM.
Malandrino, F., Casetti, C., Chiasserini, C.-F., and Fiore, M. (2014). Content download in vehicular networks in presence of noisy mobility prediction. IEEE Transactions on Mobile Computing, 13(5):1007–1021.
Mell, P. M. and Grance, T. (2011). SP 800-145. The NIST Denition of Cloud Computing. Technical report, Gaithersburg, MD, United States.
Mustafa, A. M., Abubakr, O. M., Ahmadien, O., Ahmedin, A., and Mokhtar, B. (2017). Mobility prediction for efcient resources management in vehicular cloud computing. In Mobile Cloud Computing, Services, and Engineering, 5th IEEE International Conference on, pages 53–59. IEEE.
Nabi, T., Mittal, P., Azimi, P., Dig, D., and Tilevich, E. (2015). Assessing the benets of computational ofoading in mobile-cloud applications. In Proceedings of the 3rd International Workshop on Mobile Development Lifecycle, pages 17–24. ACM.
Puliato, C., Mingozzi, E., and Anastasi, G. (2017). Fog computing for the internet of In Smart Computing (SMARTCOMP), 2017 mobile things: issues and challenges. IEEE International Conference on, pages 1–6. IEEE.
Refaat, T. K., Kantarci, B., and Mouftah, H. T. (2014). Dynamic virtual machine migration in a vehicular cloud. In 2014 IEEE Symposium on Computers and Communications (ISCC), pages 1–6. IEEE.
Roman, R., Lopez, J., and Mambo, M. (2016). Mobile edge computing, fog et al.: A survey and analysis of security threats and challenges. Future Generation Computer Systems.
Satyanarayanan, M., Bahl, P., Caceres, R., and Davies, N. (2009). The case for vm-based cloudlets in mobile computing. IEEE pervasive Computing, 8(4):14–23.
Shin, W., Min, B.-Y., and Kim, D. K. (2015). Vehicaching: Embracing user request on vehicle route with proactive data transportation. In 2015 IEEE 81st Vehicular Technology Conference (VTC Spring), pages 1–5. IEEE.
Taleb, T. and Ksentini, A. (2013). Follow me cloud: interworking federated clouds and distributed mobile networks. IEEE Network, 27(5):12–19.
Yan, H., Wan, J., Wang, Y., Wang, Z., and Song, Z. (2013). Vehicular cyber-physical systems with mobile cloud computing support. In International Conference on Cloud Computing, pages 27–35. Springer.
Yao, H., Bai, C., Zeng, D., Liang, Q., and Fan, Y. (2015). Migrate or not? exploring virtual machine migration in roadside cloudlet-based vehicular cloud. Concurrency and Computation: Practice and Experience, 27(18):5780–5792.
Yu, R., Zhang, Y., Gjessing, S., Xia, W., and Yang, K. (2013a). Toward cloud-based vehicular networks with efcient resource management. IEEE Network, 27(5):48–55.
Yu, R., Zhang, Y., Wu, H., Chatzimisios, P., and Xie, S. (2013b). Virtual machine live migration for pervasive services in cloud-assisted vehicular networks. In Communications and Networking in China (CHINACOM), 2013 8th International ICST Conference on, pages 540–545. IEEE.
Publicado
10/05/2018
Como Citar
GONÇALVES, Diogo M.; BITTENCOURT, Luiz F.; MADEIRA, Edmundo M. R..
Migração proativa de máquinas virtuais para aplicações móveis na computação em névoa. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 36. , 2018, Campos do Jordão.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2018
.
p. 1229-1242.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2018.2490.
