STEER: Redes IoT Dirigidas por Intenções e Baseadas em SDN
Resumo
As infraestruturas de IoT estão ficando cada vez mais difíceis de gerenciar. Um dos principais problemas é a alta volatilidade presente na infraestrutura, que demanda, cada vez mais, soluções auto-adaptativas. Como resposta, este trabalho apresenta STEER (Sdn-based inTEnt drivEn iot netwoRks), uma nova abordagem para adaptação dinâmica de redes IoT, baseada na união dos conceitos de Redes Dirigidas por Intenções (IDN) e Redes Definidas por Software (SDNs). Especificamente, exploramos a capacidade de IDNs para interpretar a intenção de uma aplicação, usando um Mediador de IDN em conjunto com controladores SDN para modificar o comportamento da rede, em tempo de execução e de forma autonômica, permitindo realizar a intenção de acordo com o contexto operacional atual da rede.
Palavras-chave:
Internet das Coisas, Redes Definidas por Software, Redes Dirigidas por Intenção, Adaptação dinâmica
Referências
Aschenbruck, N., Bauer, J., Bieling, J., Bothe, A., and Schwamborn, M. (2012). Selective and secure over-the-air programming for wireless sensor networks. In 2012 21st International Conference on Computer Communications and Networks (ICCCN), pages 1–6. IEEE.
Azzara, A., Alessandrelli, D., Bocchino, S., Petracca, M., and Pagano, P. (2014). Pyot, a macroprogramming framework for the internet of things. In Proceedings of the 9th IEEE international symposium on industrial embedded systems (SIES 2014), pages 96–103. IEEE.
Bera, S., Misra, S., and Vasilakos, A. V. (2017). Software-defined networking for internet of things: A survey. IEEE Internet of Things Journal, 4(6):1994–2008.
Blair, G. (2018). Complex distributed systems: The need for fresh perspectives. In 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), pages 1410–1421.
Cerroni, W., Buratti, C., Cerboni, S., Davoli, G., Contoli, C., Foresta, F., Callegati, F., and Verdone, R. (2017). Intent-based management and orchestration of heterogeneous openflow/iot sdn domains. In 2017 IEEE Conference on Network Softwarization (NetSoft), pages 1–9.
Cordeiro, Bruna M. O., S., Junior, M. B. R., and Junior, I. G. S. (2019). Air-pure: Uma solução iot da qualidade do ar interior. Monografia (Bacharel em Engenharia de Computação), UFG (Universidade Federal de Goiás), Goiânia, Brazil.
Davoli, G., Cerroni, W., Tomovic, S., Buratti, C., Contoli, C., and Callegati, F. (2019). Intent-based service management for heterogeneous software-defined infrastructure domains. International Journal of Network Management, 29(1):e2051.
Elkhatib, Y., Coulson, G., and Tyson, G. (2017). Charting an intent driven network. In 2017 13th International Conference on Network and Service Management (CNSM), pages 1–5. IEEE.
Galluccio, L., Milardo, S., Morabito, G., and Palazzo, S. (2015). Sdn-wise: Design, prototyping and experimentation of a stateful sdn solution for wireless sensor networks. In 2015 IEEE Conference on Computer Communications (INFOCOM), pages 513–521. IEEE.
Jacobs, A. S., Pfitscher, R. J., Ferreira, R. A., and Granville, L. Z. (2018). Refining network intents for self-driving networks. In Proceedings of the Afternoon Workshop on Self-Driving Networks, pages 15–21.
Júnior, J. C., da Cunha, D. C., and Ferraz, C. A. (2021). Integrating context awareness and sdn for a lightweight approach to adaptive networking. In Anais do XIII Simpósio Brasileiro de Computação Ubíqua e Pervasiva, pages 91–101. SBC.
Junior, S., Riker, A., Silvestre, B., Moreira, W., Oliveira-Jr, A., and Borges, V. (2020). Dynasti—dynamic multiple rpl instances for multiple iot applications in smart city. Sensors, 20(11):3130.
Mai, T., Garg, S., Yao, H., Nie, J., Kaddoum, G., and Xiong, Z. (2021). In-network intelligence control: Toward a self-driving networking architecture. IEEE Network, 35(2):53–59.
Noor, J., Tseng, H.-Y., Garcia, L., and Srivastava, M. (2019). Ddflow: visualized declarative programming for heterogeneous iot networks. In Proceedings of the International Conference on Internet of Things Design and Implementation, pages 172–177.
Osman, M., He, J., Mokbal, F. M. M., Zhu, N., and Qureshi, S. (2021). Ml-lgbm: A machine learning model based on light gradient boosting machine for the detection of version number attacks in rpl-based networks. IEEE Access, 9:83654–83665.
Pang, L., Yang, C., Chen, D., Song, Y., and Guizani, M. (2020). A survey on intent-driven networks. IEEE Access, 8:22862–22873.
Rodrigues-Filho, R. and Porter, B. (2017). Defining emergent software using continuous selfassembly, perception, and learning. ACM Transactions on Autonomous and Adaptive Systems (TAAS), 12(3):1–25.
Rodriguez-Zurrunero, R., Tirado-Andrés, F., and Araujo, A. (2018). Yetios: An adaptive operating system for wireless sensor networks. In 2018 IEEE 43rd Conference on Local Computer Networks Workshops (LCN Workshops), pages 16–22. IEEE.
Shafi, N. B., Ali, K., and Hassanein, H. S. (2012). No-reboot and zero-flash over-the-air programming for wireless sensor networks. In 2012 9th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), pages 371–379. IEEE.
Azzara, A., Alessandrelli, D., Bocchino, S., Petracca, M., and Pagano, P. (2014). Pyot, a macroprogramming framework for the internet of things. In Proceedings of the 9th IEEE international symposium on industrial embedded systems (SIES 2014), pages 96–103. IEEE.
Bera, S., Misra, S., and Vasilakos, A. V. (2017). Software-defined networking for internet of things: A survey. IEEE Internet of Things Journal, 4(6):1994–2008.
Blair, G. (2018). Complex distributed systems: The need for fresh perspectives. In 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS), pages 1410–1421.
Cerroni, W., Buratti, C., Cerboni, S., Davoli, G., Contoli, C., Foresta, F., Callegati, F., and Verdone, R. (2017). Intent-based management and orchestration of heterogeneous openflow/iot sdn domains. In 2017 IEEE Conference on Network Softwarization (NetSoft), pages 1–9.
Cordeiro, Bruna M. O., S., Junior, M. B. R., and Junior, I. G. S. (2019). Air-pure: Uma solução iot da qualidade do ar interior. Monografia (Bacharel em Engenharia de Computação), UFG (Universidade Federal de Goiás), Goiânia, Brazil.
Davoli, G., Cerroni, W., Tomovic, S., Buratti, C., Contoli, C., and Callegati, F. (2019). Intent-based service management for heterogeneous software-defined infrastructure domains. International Journal of Network Management, 29(1):e2051.
Elkhatib, Y., Coulson, G., and Tyson, G. (2017). Charting an intent driven network. In 2017 13th International Conference on Network and Service Management (CNSM), pages 1–5. IEEE.
Galluccio, L., Milardo, S., Morabito, G., and Palazzo, S. (2015). Sdn-wise: Design, prototyping and experimentation of a stateful sdn solution for wireless sensor networks. In 2015 IEEE Conference on Computer Communications (INFOCOM), pages 513–521. IEEE.
Jacobs, A. S., Pfitscher, R. J., Ferreira, R. A., and Granville, L. Z. (2018). Refining network intents for self-driving networks. In Proceedings of the Afternoon Workshop on Self-Driving Networks, pages 15–21.
Júnior, J. C., da Cunha, D. C., and Ferraz, C. A. (2021). Integrating context awareness and sdn for a lightweight approach to adaptive networking. In Anais do XIII Simpósio Brasileiro de Computação Ubíqua e Pervasiva, pages 91–101. SBC.
Junior, S., Riker, A., Silvestre, B., Moreira, W., Oliveira-Jr, A., and Borges, V. (2020). Dynasti—dynamic multiple rpl instances for multiple iot applications in smart city. Sensors, 20(11):3130.
Mai, T., Garg, S., Yao, H., Nie, J., Kaddoum, G., and Xiong, Z. (2021). In-network intelligence control: Toward a self-driving networking architecture. IEEE Network, 35(2):53–59.
Noor, J., Tseng, H.-Y., Garcia, L., and Srivastava, M. (2019). Ddflow: visualized declarative programming for heterogeneous iot networks. In Proceedings of the International Conference on Internet of Things Design and Implementation, pages 172–177.
Osman, M., He, J., Mokbal, F. M. M., Zhu, N., and Qureshi, S. (2021). Ml-lgbm: A machine learning model based on light gradient boosting machine for the detection of version number attacks in rpl-based networks. IEEE Access, 9:83654–83665.
Pang, L., Yang, C., Chen, D., Song, Y., and Guizani, M. (2020). A survey on intent-driven networks. IEEE Access, 8:22862–22873.
Rodrigues-Filho, R. and Porter, B. (2017). Defining emergent software using continuous selfassembly, perception, and learning. ACM Transactions on Autonomous and Adaptive Systems (TAAS), 12(3):1–25.
Rodriguez-Zurrunero, R., Tirado-Andrés, F., and Araujo, A. (2018). Yetios: An adaptive operating system for wireless sensor networks. In 2018 IEEE 43rd Conference on Local Computer Networks Workshops (LCN Workshops), pages 16–22. IEEE.
Shafi, N. B., Ali, K., and Hassanein, H. S. (2012). No-reboot and zero-flash over-the-air programming for wireless sensor networks. In 2012 9th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), pages 371–379. IEEE.
Publicado
31/07/2022
Como Citar
CORDEIRO, Bruna M. O. S.; RODRIGUES FILHO, Roberto; S. JÚNIOR, Iwens G.; COSTA, Fábio M..
STEER: Redes IoT Dirigidas por Intenções e Baseadas em SDN. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO UBÍQUA E PERVASIVA (SBCUP), 14. , 2022, Niterói.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 71-80.
ISSN 2595-6183.
DOI: https://doi.org/10.5753/sbcup.2022.222943.
