Entregas Aéreas por Drones Cooperativos: Uma Avaliação de Desempenho Considerando Pontos de Recarga de Bateria
Resumo
Em algumas cidades mais desenvolvidas do mundo já existem iniciativas de entregas por drones em diversos tipos de serviços. Em termos tecnológicos, há um grande desafio relacionado ao tempo limitado de vôo de tais dispositivos, causado principalmente pela limitação de bateria. Neste contexto, duas ações podem mitigar este problema: usar pontos de recarga estratégicos na cidade e adotar entregas cooperativas de múltiplos drones. Ambas as ações são custosas. Este artigo propõe um modelo de redes de Petri estocástico (SPN, do inglês Stochastic Petri Nets) capaz de predizer o nível de utilização de drones cooperativos, bem como o tempo médio e taxas de entrega. Tal predição considera fatores importantes como uso de drones redundantes e inclusão do tempo de recarga em pontos estratégicos.Referências
Beigi, P., Khoueiry, M., Rajabi, M. S., and Hamdar, S. (2022). Station reallocation and rebalancing strategy for bike-sharing systems: A case study of washington dc. arXiv preprint arXiv:2204.07875.
Bobbio, A. (1990). System modelling with petri nets. In Systems Reliability Assessment: Proceedings of the Ispra Course held at the Escuela Tecnica Superior de Ingenieros Navales, Madrid, Spain, September 19–23, 1988 in collaboration with Universidad Politecnica de Madrid, pages 103–143. Springer.
Correia, L. F., Dantas, J. R., and Silva, F. A. (2023). Blockchain as a service environment: a dependability evaluation. The Journal of Supercomputing, pages 1–25.
de Oliveira, F. M., Bittencourt, L. F., Bianchi, R. A., and Kamienski, C. A. (2023). Drones in the big city: Autonomous collision avoidance for aerial delivery services. IEEE Transactions on Intelligent Transportation Systems.
Devos, A., Ebeid, E., and Manoonpong, P. (2018). Development of autonomous drones for adaptive obstacle avoidance in real world environments. In 2018 21st Euromicro conference on digital system design (DSD), pages 707–710. IEEE.
Dhote, J. and Limbourg, S. (2020). Designing unmanned aerial vehicle networks for biological material transportation–the case of brussels. Computers & Industrial Engineering, 148:106652.
Du, L., Li, X., Gan, Y., and Leng, K. (2022). Optimal model and algorithm of medical materials delivery drone routing problem under major public health emergencies. Sustainability, 14(8):4651.
Fé, I., Nguyen, T. A., Soares, A., Son, S., Choi, E., Min, D., Lee, J.-W., and Silva, F. A. (2023). Model-driven dependability and power consumption quantification of kubernetes based cloud-fog continuum. IEEE Access.
Flyzipline (2024). American company that designs, manufactures, and operates delivery drones. [link] Acessado em: 04/01/2024.
Gemikonakli, O., Ever, E., and Kocyigit, A. (2009). Approximate solution for two stage open networks with markov-modulated queues minimizing the state space explosion problem. Journal of Computational and Applied Mathematics, 223(1):519–533.
Girault, C. and Valk, R. (2013). Petri nets for systems engineering: a guide to modeling, verification, and applications. Springer Science & Business Media.
Iqbal, D. and Buhnova, B. (2022). Model-based approach for building trust in autonomous drones through digital twins. In 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages 656–662. IEEE.
Jain, R. (1990). The art of computer systems performance analysis: techniques for experimental design, measurement, simulation, and modeling. John Wiley & Sons.
JOUAV (2024). How much does a drone cost in 2024? here’s a price breakdown. [link]. Acessado em: 04/01/2024.
Maciel, P., Matos, R., Silva, B., Figueiredo, J., Oliveira, D., Fé, I., Maciel, R., and Dantas, J. (2017). Mercury: Performance and dependability evaluation of systems with exponential, expolynomial, and general distributions. In 2017 IEEE 22nd Pacific Rim international symposium on dependable computing (PRDC), pages 50–57. IEEE.
Mahulea, C., Recalde, L., and Silva, M. (2010). Observability of continuous petri nets with infinite server semantics. Nonlinear Analysis: Hybrid Systems, 4(2):219–232.
Mateen, F. J., Leung, K. B., Vogel, A. C., Cissé, A. F., and Chan, T. C. (2020). A drone delivery network for antiepileptic drugs: a framework and modelling case study in a low-income country. Transactions of The Royal Society of Tropical Medicine and Hygiene, 114(4):308–314.
Namiki (2022). Modeling and simulation for optimizing drone operation rate by combining hybrid policies. In 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech), pages 162–166. IEEE.
Shi, Y., Lin, Y., Li, B., and Li, R. Y. M. (2022). A bi-objective optimization model for the medical supplies’ simultaneous pickup and delivery with drones. Computers & Industrial Engineering, 171:108389.
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.
Sousa, R. d., Cristian, L., Feitosa, L., Choi, E., Nguyen, T. A., Min, D., and Silva, F. A. (2023). Performability evaluation and sensitivity analysis of a video streaming on demand architecture. Applied Sciences, 13(2):998.
Bobbio, A. (1990). System modelling with petri nets. In Systems Reliability Assessment: Proceedings of the Ispra Course held at the Escuela Tecnica Superior de Ingenieros Navales, Madrid, Spain, September 19–23, 1988 in collaboration with Universidad Politecnica de Madrid, pages 103–143. Springer.
Correia, L. F., Dantas, J. R., and Silva, F. A. (2023). Blockchain as a service environment: a dependability evaluation. The Journal of Supercomputing, pages 1–25.
de Oliveira, F. M., Bittencourt, L. F., Bianchi, R. A., and Kamienski, C. A. (2023). Drones in the big city: Autonomous collision avoidance for aerial delivery services. IEEE Transactions on Intelligent Transportation Systems.
Devos, A., Ebeid, E., and Manoonpong, P. (2018). Development of autonomous drones for adaptive obstacle avoidance in real world environments. In 2018 21st Euromicro conference on digital system design (DSD), pages 707–710. IEEE.
Dhote, J. and Limbourg, S. (2020). Designing unmanned aerial vehicle networks for biological material transportation–the case of brussels. Computers & Industrial Engineering, 148:106652.
Du, L., Li, X., Gan, Y., and Leng, K. (2022). Optimal model and algorithm of medical materials delivery drone routing problem under major public health emergencies. Sustainability, 14(8):4651.
Fé, I., Nguyen, T. A., Soares, A., Son, S., Choi, E., Min, D., Lee, J.-W., and Silva, F. A. (2023). Model-driven dependability and power consumption quantification of kubernetes based cloud-fog continuum. IEEE Access.
Flyzipline (2024). American company that designs, manufactures, and operates delivery drones. [link] Acessado em: 04/01/2024.
Gemikonakli, O., Ever, E., and Kocyigit, A. (2009). Approximate solution for two stage open networks with markov-modulated queues minimizing the state space explosion problem. Journal of Computational and Applied Mathematics, 223(1):519–533.
Girault, C. and Valk, R. (2013). Petri nets for systems engineering: a guide to modeling, verification, and applications. Springer Science & Business Media.
Iqbal, D. and Buhnova, B. (2022). Model-based approach for building trust in autonomous drones through digital twins. In 2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages 656–662. IEEE.
Jain, R. (1990). The art of computer systems performance analysis: techniques for experimental design, measurement, simulation, and modeling. John Wiley & Sons.
JOUAV (2024). How much does a drone cost in 2024? here’s a price breakdown. [link]. Acessado em: 04/01/2024.
Maciel, P., Matos, R., Silva, B., Figueiredo, J., Oliveira, D., Fé, I., Maciel, R., and Dantas, J. (2017). Mercury: Performance and dependability evaluation of systems with exponential, expolynomial, and general distributions. In 2017 IEEE 22nd Pacific Rim international symposium on dependable computing (PRDC), pages 50–57. IEEE.
Mahulea, C., Recalde, L., and Silva, M. (2010). Observability of continuous petri nets with infinite server semantics. Nonlinear Analysis: Hybrid Systems, 4(2):219–232.
Mateen, F. J., Leung, K. B., Vogel, A. C., Cissé, A. F., and Chan, T. C. (2020). A drone delivery network for antiepileptic drugs: a framework and modelling case study in a low-income country. Transactions of The Royal Society of Tropical Medicine and Hygiene, 114(4):308–314.
Namiki (2022). Modeling and simulation for optimizing drone operation rate by combining hybrid policies. In 2022 IEEE 4th Global Conference on Life Sciences and Technologies (LifeTech), pages 162–166. IEEE.
Shi, Y., Lin, Y., Li, B., and Li, R. Y. M. (2022). A bi-objective optimization model for the medical supplies’ simultaneous pickup and delivery with drones. Computers & Industrial Engineering, 171:108389.
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.
Sousa, R. d., Cristian, L., Feitosa, L., Choi, E., Nguyen, T. A., Min, D., and Silva, F. A. (2023). Performability evaluation and sensitivity analysis of a video streaming on demand architecture. Applied Sciences, 13(2):998.
Publicado
21/07/2024
Como Citar
SILVA, Francisco Airton; BARBOSA, Vandirleya; SABINO, Arthur; LIMA, Luiz Nelson; FÉ, Iure; REGO, Paulo; BITTENCOURT, Luiz F..
Entregas Aéreas por Drones Cooperativos: Uma Avaliação de Desempenho Considerando Pontos de Recarga de Bateria. In: SEMINÁRIO INTEGRADO DE SOFTWARE E HARDWARE (SEMISH), 51. , 2024, Brasília/DF.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 205-216.
ISSN 2595-6205.
DOI: https://doi.org/10.5753/semish.2024.2991.
