O impacto dos algoritmos de controle de congestionamento em aplicações Edge-Cloud Continuum
Resumo
Edge-Cloud Continuum é uma arquitetura que combina os conceitos de Cloud e Edge Computing, de forma transparente ao usuário final. A combinação é necessária para melhorar a qualidade dos serviços, em termos de latência de acesso, tempo de processamento e consumo energético. Embora revolucionária, a arquitetura proposta é dependente das redes de interconexão, herdando seus desafios de pesquisa relacionados ao gerenciamento e compartilhamento de recursos. Assim, o presente trabalho investiga o impacto ocasionado pelos algoritmos de controle de congestionamento Cubic e Reno, tradicionalmente usados pelas aplicações Edge-Cloud Continuum. O ensaio experimental resume uma aplicação, demonstrando as mudança de desempenho ao mudar o algoritmo de controle de congestionamento na arquitetura.Referências
Bittencourt, L. et al. (2018). The internet of things, fog and cloud continuum: Integration and challenges. Internet of Things, 3:134–155.
Ha, S., Rhee, I., and Xu, L. (2008). Cubic: A new tcp-friendly high-speed tcp variant. SIGOPS Oper. Syst. Rev., 42(5):64–74.
Jacobson, V. (1988). Congestion avoidance and control. ACM SIGCOMM computer communication review, 18(4):314–329.
Lantz et al. (2010). A network in a laptop: rapid prototyping for software-defined networks. In Proceedings of the 9th ACM SIGCOMM Workshop on Hot Topics in Networks, pages 1–6.
Lopez, G. et al. (2015). Edge-centric computing: Vision and challenges.
Lorincz et al. (2021). A comprehensive overview of tcp congestion control in 5g networks: Research challenges and future perspectives. Sensors, 21(13):4510.
Mell, P., Grance, T., et al. (2011). The nist definition of cloud computing.
Roberts, J., Skandalakis, J., Foard, R., and Choi, J. (2016). A comparison of sdn based tcp congestion control with tcp reno and cubic. Technical report, Technical Report.
Rodrigues et al. (2023). Service provisioning in edge-cloud continuum: Emerging applications for mobile devices. Journal of Internet Services and Applications, 14(1):47–83.
Verma et al. (2020). An iot based congestion control algorithm. Internet of Things, 9:100157.
Yousefpour et al. (2019). All one needs to know about fog computing and related edge computing paradigms: A complete survey. J. of Systems Architecture, 98:289–330.
Ha, S., Rhee, I., and Xu, L. (2008). Cubic: A new tcp-friendly high-speed tcp variant. SIGOPS Oper. Syst. Rev., 42(5):64–74.
Jacobson, V. (1988). Congestion avoidance and control. ACM SIGCOMM computer communication review, 18(4):314–329.
Lantz et al. (2010). A network in a laptop: rapid prototyping for software-defined networks. In Proceedings of the 9th ACM SIGCOMM Workshop on Hot Topics in Networks, pages 1–6.
Lopez, G. et al. (2015). Edge-centric computing: Vision and challenges.
Lorincz et al. (2021). A comprehensive overview of tcp congestion control in 5g networks: Research challenges and future perspectives. Sensors, 21(13):4510.
Mell, P., Grance, T., et al. (2011). The nist definition of cloud computing.
Roberts, J., Skandalakis, J., Foard, R., and Choi, J. (2016). A comparison of sdn based tcp congestion control with tcp reno and cubic. Technical report, Technical Report.
Rodrigues et al. (2023). Service provisioning in edge-cloud continuum: Emerging applications for mobile devices. Journal of Internet Services and Applications, 14(1):47–83.
Verma et al. (2020). An iot based congestion control algorithm. Internet of Things, 9:100157.
Yousefpour et al. (2019). All one needs to know about fog computing and related edge computing paradigms: A complete survey. J. of Systems Architecture, 98:289–330.
Publicado
23/10/2023
Como Citar
SAKASHITA, Nicolas K. C.; ALBUQUERQUE, Paulo Roberto; KOSLOVSKI, Guilherme P..
O impacto dos algoritmos de controle de congestionamento em aplicações Edge-Cloud Continuum. In: ESCOLA REGIONAL DE REDES DE COMPUTADORES (ERRC), 20. , 2023, Porto Alegre/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 19-24.
DOI: https://doi.org/10.5753/errc.2023.893.