MORFEU: Mecanismo baseado em Otimização Combinatória para Alocação de Tarefas em Nuvens Veiculares
Resumo
Os sistemas de transporte inteligentes (ITS) compõem um arcabouço de serviços que busca mitigar problemas no setor rodoviário. Os serviços de ITS são facilitados pela criação de nuvens veiculares por meio do uso dos recursos de comunicação de outros veículos para fornecer serviços em nuvem mais próximos das aplicações veiculares. No entanto, frequentemente os recursos computacionais presentes nos veículos são subutilizados. Para mitigar essa limitação, este trabalho propõe um mecanismo baseado em otimização combinatória para alocação de tarefas em nuvens veiculares, denominado de MORFEU. O mecanismo considera otimização combinatória para alocar com eficiência tarefas computacionais a serem executadas em nuvens veiculares. Resultados de simulação mostram que o MORFEU consegue alocar mais tarefas, com um ganho superior, e menor desperdício de recursos computacionais em comparação com outras abordagens de alocação avaliadas.
Palavras-chave:
Nuvens veiculares, Alocação de tarefas, Otimização combinatória
Referências
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Hagenauer, F., Higuchi, T., Altintas, O., and Dressler, F. (2019). Efficient data handling in vehicular micro clouds. Ad Hoc Networks, 91:101871.
Hattab, G., Ucar, S., Higuchi, T., Altintas, O., Dressler, F., and Cabric, D. (2019). Optimized assignment of computational tasks in vehicular micro clouds. In 2nd International Workshop on Edge Systems, Analytics and Networking, pages 1–6. ACM.
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Meneguette, R. I., Boukerche, A., and Pimenta, A. H. (2018). Avarac: An availabilitybased resource allocation scheme for vehicular cloud. IEEE Transactions on Intelligent Transportation Systems.
Meneguette, R. I., Rodrigues, D. O., da Costa, J. B. D., Rosario, D., and Villas, L. A. (2019). A virtual machine migration policy based on multiple attribute decision in vehicular cloud scenario. In IEEE International Conference on Communications (ICC), pages 1–6. IEEE.
Nabi, M., Benkoczi, R., Abdelhamid, S., and Hassanein, H. S. (2017). Resource assignment in vehicular clouds. In IEEE International Conference on Communications (ICC), pages 1–6. Ieee.
Pereira, R., Lieira, D., da Silva, M., Pimenta, A., da Costa, J. B. D., Rosario, D. L., and Meneguette, R. I. (2019). A novel fog-based resource allocation policy for vehicular clouds in the highway environment. In IEEE 11th Latin-American Conference on Communications (LATINCOM), pages 1–6. IEEE.
Qualcomm (2018). Connecting vehicles to everything.
Sorkhoh, I., Ebrahimi, D., Atallah, R., and Assi, C. (2019). Workload scheduling in vehicular networks with edge cloud capabilities. IEEE Transactions on Vehicular Technology.
Thakur, A. and Malekian, R. (2019). Fog computing for detecting vehicular congestion, an internet of vehicles based approach: A review. IEEE Intelligent Transportation Systems Magazine, 11(2):8–16.
Wang, J., Liu, T., Liu, K., Kim, B., Xie, J., and Han, Z. (2018). Computation offloading over fog and cloud using multi-dimensional multiple knapsack problem. In IEEE Global Communications Conference (GLOBECOM), pages 1–7. IEEE.
Yang, C., Liu, Y., Chen, X., Zhong, W., and Xie, S. (2019). Efficient mobility-aware task offloading for vehicular edge computing networks. IEEE Access, 7:26652–26664.
Yu, R., Zhang, Y., Gjessing, S., Xia, W., and Yang, K. (2013). Toward cloud-based vehicular networks with efficient resource management. IEEE Network, 27(5):48–55.
CISCO (2019). Driving Profits from Connected Vehicles. Technical report, CISCO.
Codeca, L., Frank, R., Faye, S., and Engel, T. (2017). Luxembourg sumo traffic (lust) scenario: Traffic demand evaluation. IEEE Intelligent Transportation Systems Magazine, 9(2):52–63.
Costa, J., Rosário, D., de Souza, A. M., Villas, L. A., and Cerqueira, E. (2018). Protocolo para disseminação de dados em vanets baseado em métricas de redes complexas: Um estudo de caso com sistema de gerenciamento de trânsito. In XXXVI Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuı́dos. SBC.
Coutinho, R. W. and Boukerche, A. (2019). Guidelines for the design of vehicular cloud infrastructures for connected autonomous vehicles. IEEE Wireless Communications, 26(4):6–11.
Ester, M., Kriegel, H.-P., Sander, J., Xu, X., et al. (1996). A density-based algorithm for discovering clusters in large spatial databases with noise. In Kdd, pages 226–231.
Hagenauer, F., Higuchi, T., Altintas, O., and Dressler, F. (2019). Efficient data handling in vehicular micro clouds. Ad Hoc Networks, 91:101871.
Hattab, G., Ucar, S., Higuchi, T., Altintas, O., Dressler, F., and Cabric, D. (2019). Optimized assignment of computational tasks in vehicular micro clouds. In 2nd International Workshop on Edge Systems, Analytics and Networking, pages 1–6. ACM.
Higuchi, T., Dressler, F., and Altintas, O. (2018). How to keep a vehicular micro cloud intact. In IEEE 87th Vehicular Technology Conference (VTC Spring), pages 1–5. IEEE.
Kadhim, A. J. and Seno, S. A. H. (2019). Maximizing the utilization of fog computing in internet of vehicle using sdn. IEEE Communications Letters, 23(1):140–143.
Martello, S. and Toth, P. (1990). Knapsack problems: algorithms and computer implementations. John Wiley & Sons Ltd.
Meneguette, R. I., Boukerche, A., and Pimenta, A. H. (2018). Avarac: An availabilitybased resource allocation scheme for vehicular cloud. IEEE Transactions on Intelligent Transportation Systems.
Meneguette, R. I., Rodrigues, D. O., da Costa, J. B. D., Rosario, D., and Villas, L. A. (2019). A virtual machine migration policy based on multiple attribute decision in vehicular cloud scenario. In IEEE International Conference on Communications (ICC), pages 1–6. IEEE.
Nabi, M., Benkoczi, R., Abdelhamid, S., and Hassanein, H. S. (2017). Resource assignment in vehicular clouds. In IEEE International Conference on Communications (ICC), pages 1–6. Ieee.
Pereira, R., Lieira, D., da Silva, M., Pimenta, A., da Costa, J. B. D., Rosario, D. L., and Meneguette, R. I. (2019). A novel fog-based resource allocation policy for vehicular clouds in the highway environment. In IEEE 11th Latin-American Conference on Communications (LATINCOM), pages 1–6. IEEE.
Qualcomm (2018). Connecting vehicles to everything.
Sorkhoh, I., Ebrahimi, D., Atallah, R., and Assi, C. (2019). Workload scheduling in vehicular networks with edge cloud capabilities. IEEE Transactions on Vehicular Technology.
Thakur, A. and Malekian, R. (2019). Fog computing for detecting vehicular congestion, an internet of vehicles based approach: A review. IEEE Intelligent Transportation Systems Magazine, 11(2):8–16.
Wang, J., Liu, T., Liu, K., Kim, B., Xie, J., and Han, Z. (2018). Computation offloading over fog and cloud using multi-dimensional multiple knapsack problem. In IEEE Global Communications Conference (GLOBECOM), pages 1–7. IEEE.
Yang, C., Liu, Y., Chen, X., Zhong, W., and Xie, S. (2019). Efficient mobility-aware task offloading for vehicular edge computing networks. IEEE Access, 7:26652–26664.
Yu, R., Zhang, Y., Gjessing, S., Xia, W., and Yang, K. (2013). Toward cloud-based vehicular networks with efficient resource management. IEEE Network, 27(5):48–55.
Publicado
07/12/2020
Como Citar
DA COSTA, Joahannes Bruno Dias; PEIXOTO, Maycon Leone Maciel; MENEGUETTE, Rodolfo Ipolito; ROSÁRIO, Denis Lima; VILLAS, Leandro Aparecido.
MORFEU: Mecanismo baseado em Otimização Combinatória para Alocação de Tarefas em Nuvens Veiculares. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 38. , 2020, Rio de Janeiro.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 505-518.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2020.12305.
