Algoritmo de Decisão para Offloading Computacional em Vehicular Fog Computing com Pedestres
Resumo
Com um maior número de dispositivos integrados e conectados em uma VANET (Veicular Ad Hoc Networks), há uma maior disponibilidade e variedade de recursos computacionais para executar aplicações. No campo das redes veiculares, a tecnologia VFC (Vehicular Fog Computing) estabelece veículos, borda e nuvem como infraestruturas provedoras de recursos. No entanto, o uso do VFC como infraestrutura para pedestres ainda é limitado, com poucos trabalhos abordando o offloading computacional nesse cenário. Nesse contexto, um algoritmo de decisão para o processo de offloading foi implementado com base em recursos disponibilizados pela VFC, de modo a garantir melhores taxas de offloading e latência. Os resultados demonstraram que o algoritmo proposto obteve taxas de eficiência na escolha acima de 90% nos cenários testados, além de uma redução de até 40% no tempo de execução do offloading quando comparado à abordagem aleatória testada.
Referências
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Hou, X., Li, Y., Chen, M., Wu, D., Jin, D., and Chen, S. (2016). Vehicular fog computing: A viewpoint of vehicles as the infrastructures. IEEE Transactions on Vehicular Technology, 65(6):3860-3873.
Ibrahim, K. and Weigle, M. C. (2008). Cascade: Cluster-based accurate syntactic compression of aggregated data in vanets. In 2008 IEEE Globecom Workshops, pages 1-10. IEEE.
Khan, M. J., Khan, M. A., Beg, A., Malik, S., and El-Sayed, H. (2022). An overview of the 3gpp identified use cases for v2x services. Procedia Computer Science, 198:750-756.
Li, F., Chen, W., Shui, Y., Wang, J., Yang, K., Xu, L., Yu, J., and Li, C. (2019). Connectivity probability analysis of vanets at different traffic densities using measured data at 5.9 ghz. Physical Communication, 35:100709.
Lin, Y.-D., Hu, J.-C., Kar, B., and Yen, L.-H. (2019). Cost minimization with offloading to vehicles in two-tier federated edge and vehicular-fog systems. In 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), pages 1-6. IEEE.
Mezzavilla, M., Zhang, M., Polese, M., Ford, R., Dutta, S., Rangan, S., and Zorzi, M. (2018). End-to-end simulation of 5g mmwave networks. IEEE Communications Surveys & Tutorials, 20(3):2237-2263.
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Nguyen, Q.-H., Morold, M., David, K., and Dressler, F. (2020). Car-to-pedestrian communication with mec-support for adaptive safety of vulnerable road users. Computer Communications, 150:83-93.
Sewalkar, P. and Seitz, J. (2019). Vehicle-to-pedestrian communication for vulnerable road users: Survey, design considerations, and challenges. Sensors, 19(2):358.
Shi, J., Du, J., Wang, J., Wang, J., and Yuan, J. (2020). Priority-aware task offloading in vehicular fog computing based on deep reinforcement learning. IEEE Transactions on Vehicular Technology, 69(12):16067-16081.
Souza, A. B., Celestino, J., Xavier, F. A., Oliveira, F. D., Patel, A., and Latifi, M. (2013). Stable multicast trees based on ant colony optimization for vehicular ad hoc networks. In The International Conference on Information Networking 2013 (ICOIN), pages 101-106. IEEE.
Wang, Z., Zhong, Z., Zhao, D., and Ni, M. (2018). Vehicle-based cloudlet relaying for mobile computation offloading. IEEE Transactions on Vehicular Technology, 67(11):11181-11191.
Xiao, L., Zhuang, W., Zhou, S., and Chen, C. (2019). Learning while offloading: Task offloading in vehicular edge computing network. In Learning-based VANET Communication and Security Techniques, pages 49-77. Springer.
Yoo, S. K., Cotton, S. L., Zhang, L., Doone, M. G., Song, J. S., and Rajbhandari, S. (2021). Evaluation of a switched combining based distributed antenna system (das) for pedestrian-to-vehicle communications. IEEE Transactions on Vehicular Technology, 70(10):11005-11010.
Chen, S., Hu, J., Shi, Y., Peng, Y., Fang, J., Zhao, R., and Zhao, L. (2017). Vehicle-to-everything (v2x) services supported by lte-based systems and 5g. IEEE Communications Standards Magazine, 1(2):70-76.
de Almeida, T. T., Júnior, J. G. R., Campista, M. E. M., and Costa, L. H. M. K. (2020). Uma análise de desempenho do wi-fi direct para comunicações veículo-pedestre. In Anais do XXXVIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, pages 253-266. SBC.
De Souza, A. B., Rego, P. A., Carneiro, T., Rodrigues, J. D. C., Rebouças Filho, P. P., De Souza, J. N., Chamola, V., De Albuquerque, V. H. C., and Sikdar, B. (2020). Computation offloading for vehicular environments: A survey. IEEE Access, 8:198214-198243.
de Souza, A. B., Rego, P. A. L., Rocha, P. H. G., Carneiro, T., and de Souza, J. N. (2020). A task offloading scheme for wave vehicular clouds and 5g mobile edge computing. In GLOBECOM 2020-2020 IEEE Global Communications Conference, pages 1-6. IEEE.
Eckermann, F., Kahlert, M., and Wietfeld, C. (2019). Performance analysis of c-v2x mode 4 communication introducing an open-source c-v2x simulator. In 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), pages 1-5. IEEE.
Gonçalves, D. M., Bittencourt, L. F., and Madeira, E. M. (2019). Análise da predição de mobilidade na migração de aplicações em computação em névoa. In Anais do XXXVII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos, pages 580-593. SBC.
Hou, X., Li, Y., Chen, M., Wu, D., Jin, D., and Chen, S. (2016). Vehicular fog computing: A viewpoint of vehicles as the infrastructures. IEEE Transactions on Vehicular Technology, 65(6):3860-3873.
Ibrahim, K. and Weigle, M. C. (2008). Cascade: Cluster-based accurate syntactic compression of aggregated data in vanets. In 2008 IEEE Globecom Workshops, pages 1-10. IEEE.
Khan, M. J., Khan, M. A., Beg, A., Malik, S., and El-Sayed, H. (2022). An overview of the 3gpp identified use cases for v2x services. Procedia Computer Science, 198:750-756.
Li, F., Chen, W., Shui, Y., Wang, J., Yang, K., Xu, L., Yu, J., and Li, C. (2019). Connectivity probability analysis of vanets at different traffic densities using measured data at 5.9 ghz. Physical Communication, 35:100709.
Lin, Y.-D., Hu, J.-C., Kar, B., and Yen, L.-H. (2019). Cost minimization with offloading to vehicles in two-tier federated edge and vehicular-fog systems. In 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), pages 1-6. IEEE.
Mezzavilla, M., Zhang, M., Polese, M., Ford, R., Dutta, S., Rangan, S., and Zorzi, M. (2018). End-to-end simulation of 5g mmwave networks. IEEE Communications Surveys & Tutorials, 20(3):2237-2263.
Nguyen, Q.-H., Morold, M., David, K., and Dressler, F. (2019). Adaptive safety context information for vulnerable road users with mec support. In 2019 15th Annual Conference on Wireless On-demand Network Systems and Services (WONS), pages 28-35. IEEE.
Nguyen, Q.-H., Morold, M., David, K., and Dressler, F. (2020). Car-to-pedestrian communication with mec-support for adaptive safety of vulnerable road users. Computer Communications, 150:83-93.
Sewalkar, P. and Seitz, J. (2019). Vehicle-to-pedestrian communication for vulnerable road users: Survey, design considerations, and challenges. Sensors, 19(2):358.
Shi, J., Du, J., Wang, J., Wang, J., and Yuan, J. (2020). Priority-aware task offloading in vehicular fog computing based on deep reinforcement learning. IEEE Transactions on Vehicular Technology, 69(12):16067-16081.
Souza, A. B., Celestino, J., Xavier, F. A., Oliveira, F. D., Patel, A., and Latifi, M. (2013). Stable multicast trees based on ant colony optimization for vehicular ad hoc networks. In The International Conference on Information Networking 2013 (ICOIN), pages 101-106. IEEE.
Wang, Z., Zhong, Z., Zhao, D., and Ni, M. (2018). Vehicle-based cloudlet relaying for mobile computation offloading. IEEE Transactions on Vehicular Technology, 67(11):11181-11191.
Xiao, L., Zhuang, W., Zhou, S., and Chen, C. (2019). Learning while offloading: Task offloading in vehicular edge computing network. In Learning-based VANET Communication and Security Techniques, pages 49-77. Springer.
Yoo, S. K., Cotton, S. L., Zhang, L., Doone, M. G., Song, J. S., and Rajbhandari, S. (2021). Evaluation of a switched combining based distributed antenna system (das) for pedestrian-to-vehicle communications. IEEE Transactions on Vehicular Technology, 70(10):11005-11010.
Publicado
23/05/2022
Como Citar
ROCHA, Paulo H. G.; SOUZA, Alisson B. de; SILVA, Francisco A.; REGO, Paulo A. L..
Algoritmo de Decisão para Offloading Computacional em Vehicular Fog Computing com Pedestres. In: WORKSHOP DE COMPUTAÇÃO URBANA (COURB), 6. , 2022, Fortaleza.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 224-237.
ISSN 2595-2706.
DOI: https://doi.org/10.5753/courb.2022.223566.
