Desvendando a Elasticidade de Máquinas Virtuais em VANETs: Uma Estratégia para Aperfeiçoar o Planejamento de Capacidade em RSUs
Resumo
Este artigo apresenta um modelo de desempenho projetado para avaliar a eficácia de um sistema de auto-escalonamento de máquinas virtuais aplicado ao monitoramento em rodovias sujeitas a elevada variabilidade de tráfego com VANETs. Para isso, foi utilizada uma abordagem baseada em redes de Petri estocásticas, capaz de capturar uma variedade de comportamentos distintos associados ao sistema de auto-escalonamento. Os resultados obtidos revelam a importância da quantidade já alocada de máquinas virtuais no sistema inicialmente. Ainda, constatou-se que a aplicação efetiva da estratégia de auto-escalonamento e reinstanciação desempenhou um papel significativo na otimização do desempenho global do sistema.Referências
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Bobbio, A., Puliafito, A., Telek, M., and Trivedi, K. S. (1998). Recent developments in non-markovian stochastic petri nets. Journal of Circuits, Systems, and Computers, 8(01):119–158.
Carvalho, D., Rodrigues, L., Endo, P. T., Kosta, S., and Silva, F. A. (2020). Edge servers placement in mobile edge computing using stochastic petri nets. International Journal of Computational Science and Engineering, 23(4):352–366.
Cumbal, R., Gutiérrez, S., Guerrero, C., Hincapié, R., and Arévalo, G. (2019). Optimal resources allocation from vanet infrastructures in dynamic mobile environments. In 2019 IEEE Latin-American Conference on Communications (LATINCOM), pages 1–5. IEEE.
Fé, I., Matos, R., Dantas, J., Melo, C., Nguyen, T. A., Min, D., Choi, E., Silva, F. A., and Maciel, P. R. M. (2022a). Performance-cost trade-off in auto-scaling mechanisms for cloud computing. Sensors, 22(3):1221.
Fé, I., Matos, R., Dantas, J., Melo, C., Nguyen, T. A., Min, D., Choi, E., Silva, F. A., and Maciel, P. R. M. (2022b). Performance-cost trade-off in auto-scaling mechanisms for cloud computing. Sensors, 22(3):1221.
Jain, R. (1990). The art of computer systems performance analysis: techniques for experimental design, measurement, simulation, and modeling. John Wiley & Sons.
Karabulut, M. A., Shah, A. S., Ilhan, H., Pathan, A.-S. K., and Atiquzzaman, M. (2023). Inspecting vanet with various critical aspects–a systematic review. Ad Hoc Networks, page 103281.
Macêdo, J., Carvalho, V., Andrade, E., and Silva, F. (2022). Modeling and analysis of communication in vanets using rsus. In Proceedings of the 21st Workshop on Performance of Computer and Communication Systems, pages 96–107, Porto Alegre, RS, Brasil. SBC.
Martin-Faus, I. V., Urquiza-Aguiar, L., Aguilar Igartua, M., and Guérin-Lassous, I. (2018). Transient analysis of idle time in vanets using markov-reward models. IEEE Transactions on Vehicular Technology, 67(4):2833–2847.
Naresh, R., Narayanan, K. L., Kumar, C. V., and Senthilkumar, S. (2024). A routing in vanet towards smart business cities using optimization techniques. In Digital Twin Technology and AI Implementations in Future-Focused Businesses, pages 1–13. IGI Global.
Ouhmidou, H., Nabou, A., Ikidid, A., Bouassaba, W., Ouzzif, M., and El Kiram, M. A. (2023). Traffic control, congestion management and smart parking through vanet, ml, and iot: A review. In 2023 10th International Conference on Wireless Networks and Mobile Communications (WINCOM), pages 1–6. IEEE.
Parashar, S. and Tiwari, R. (2023). Traffic control and qos improvement analysis in v-to-v and v-to-rsu communication in vanet. In 2023 World Conference on Communication & Computing (WCONF), pages 1–5. IEEE.
Rodrigues, L., Neto, F., Gonçalves, G., Soares, A., and Silva, F. A. (2021). Performance evaluation of smart cooperative traffic lights in vanets. International Journal of Computational Science and Engineering, 24(3):276–289.
Siddiqi, M. H., Alruwaili, M., Ali, A., Haider, S. F., Ali, F., and Iqbal, M. (2020). Dynamic priority-based efficient resource allocation and computing framework for vehicular multimedia cloud computing. IEEE access, 8:81080–81089.
Silva, B., Matos, R., Callou, G., Figueiredo, J., Oliveira, D., Ferreira, J., Dantas, J., Lobo, A., Alves, V., and Maciel, P. (2015). Mercury: An integrated environment for performance and dependability evaluation of general systems. In Proceedings of the Industrial Track at 45th Dependable Systems and Networks Conference, DSN, pages 1–4.
Silva, L. G., Cardoso, I., Brito, C., Barbosa, V., Nogueira, B., Choi, E., Nguyen, T. A., Min, D., Lee, J. W., and Silva, F. A. (2023). Urban advanced mobility dependability: A model-based quantification on vehicular ad hoc networks with virtual machine migration. Sensors, 23(23):9485.
Tang, Y., Cheng, N., Wu, W., Wang, M., Dai, Y., and Shen, X. (2019). Delay-minimization routing for heterogeneous vanets with machine learning based mobility prediction. IEEE Transactions on Vehicular Technology, 68(4):3967–3979.
Wu, X., Zhao, S., Zhang, R., and Yang, L. (2020). Mobility prediction-based joint task assignment and resource allocation in vehicular fog computing. In 2020 IEEE Wireless Communications and Networking Conference (WCNC), pages 1–6. IEEE.
Bobbio, A., Puliafito, A., Telek, M., and Trivedi, K. S. (1998). Recent developments in non-markovian stochastic petri nets. Journal of Circuits, Systems, and Computers, 8(01):119–158.
Carvalho, D., Rodrigues, L., Endo, P. T., Kosta, S., and Silva, F. A. (2020). Edge servers placement in mobile edge computing using stochastic petri nets. International Journal of Computational Science and Engineering, 23(4):352–366.
Cumbal, R., Gutiérrez, S., Guerrero, C., Hincapié, R., and Arévalo, G. (2019). Optimal resources allocation from vanet infrastructures in dynamic mobile environments. In 2019 IEEE Latin-American Conference on Communications (LATINCOM), pages 1–5. IEEE.
Fé, I., Matos, R., Dantas, J., Melo, C., Nguyen, T. A., Min, D., Choi, E., Silva, F. A., and Maciel, P. R. M. (2022a). Performance-cost trade-off in auto-scaling mechanisms for cloud computing. Sensors, 22(3):1221.
Fé, I., Matos, R., Dantas, J., Melo, C., Nguyen, T. A., Min, D., Choi, E., Silva, F. A., and Maciel, P. R. M. (2022b). Performance-cost trade-off in auto-scaling mechanisms for cloud computing. Sensors, 22(3):1221.
Jain, R. (1990). The art of computer systems performance analysis: techniques for experimental design, measurement, simulation, and modeling. John Wiley & Sons.
Karabulut, M. A., Shah, A. S., Ilhan, H., Pathan, A.-S. K., and Atiquzzaman, M. (2023). Inspecting vanet with various critical aspects–a systematic review. Ad Hoc Networks, page 103281.
Macêdo, J., Carvalho, V., Andrade, E., and Silva, F. (2022). Modeling and analysis of communication in vanets using rsus. In Proceedings of the 21st Workshop on Performance of Computer and Communication Systems, pages 96–107, Porto Alegre, RS, Brasil. SBC.
Martin-Faus, I. V., Urquiza-Aguiar, L., Aguilar Igartua, M., and Guérin-Lassous, I. (2018). Transient analysis of idle time in vanets using markov-reward models. IEEE Transactions on Vehicular Technology, 67(4):2833–2847.
Naresh, R., Narayanan, K. L., Kumar, C. V., and Senthilkumar, S. (2024). A routing in vanet towards smart business cities using optimization techniques. In Digital Twin Technology and AI Implementations in Future-Focused Businesses, pages 1–13. IGI Global.
Ouhmidou, H., Nabou, A., Ikidid, A., Bouassaba, W., Ouzzif, M., and El Kiram, M. A. (2023). Traffic control, congestion management and smart parking through vanet, ml, and iot: A review. In 2023 10th International Conference on Wireless Networks and Mobile Communications (WINCOM), pages 1–6. IEEE.
Parashar, S. and Tiwari, R. (2023). Traffic control and qos improvement analysis in v-to-v and v-to-rsu communication in vanet. In 2023 World Conference on Communication & Computing (WCONF), pages 1–5. IEEE.
Rodrigues, L., Neto, F., Gonçalves, G., Soares, A., and Silva, F. A. (2021). Performance evaluation of smart cooperative traffic lights in vanets. International Journal of Computational Science and Engineering, 24(3):276–289.
Siddiqi, M. H., Alruwaili, M., Ali, A., Haider, S. F., Ali, F., and Iqbal, M. (2020). Dynamic priority-based efficient resource allocation and computing framework for vehicular multimedia cloud computing. IEEE access, 8:81080–81089.
Silva, B., Matos, R., Callou, G., Figueiredo, J., Oliveira, D., Ferreira, J., Dantas, J., Lobo, A., Alves, V., and Maciel, P. (2015). Mercury: An integrated environment for performance and dependability evaluation of general systems. In Proceedings of the Industrial Track at 45th Dependable Systems and Networks Conference, DSN, pages 1–4.
Silva, L. G., Cardoso, I., Brito, C., Barbosa, V., Nogueira, B., Choi, E., Nguyen, T. A., Min, D., Lee, J. W., and Silva, F. A. (2023). Urban advanced mobility dependability: A model-based quantification on vehicular ad hoc networks with virtual machine migration. Sensors, 23(23):9485.
Tang, Y., Cheng, N., Wu, W., Wang, M., Dai, Y., and Shen, X. (2019). Delay-minimization routing for heterogeneous vanets with machine learning based mobility prediction. IEEE Transactions on Vehicular Technology, 68(4):3967–3979.
Wu, X., Zhao, S., Zhang, R., and Yang, L. (2020). Mobility prediction-based joint task assignment and resource allocation in vehicular fog computing. In 2020 IEEE Wireless Communications and Networking Conference (WCNC), pages 1–6. IEEE.
Publicado
20/05/2024
Como Citar
SILVA, Luis Guilherme et al.
Desvendando a Elasticidade de Máquinas Virtuais em VANETs: Uma Estratégia para Aperfeiçoar o Planejamento de Capacidade em RSUs. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 42. , 2024, Niterói/RJ.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 169-182.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2024.1291.
