Estratégia de Posicionamento de Aplicações Sensíveis à Privacidade e Latência em Bordas Federadas
Resumo
Sobre ambientes de computação em borda federada, provedores de infraestrutura compartilham recursos com o objetivo de minimizar limitações de escalabilidade, e atender a crescente demanda por recursos das aplicações. No entanto, a heterogeneidade da infraestrutura, gerenciada por diferentes provedores de borda, impõe desafios relacionados ao equilíbrio entre os requisitos de desempenho e privacidade das aplicações. Algumas estratégias existentes tentam resolver essa questão implementando decisões de posicionamento baseadas no nível de confiança do usuário no provedor de borda. No entanto, isso acaba limitando a quantidade de servidores de borda considerados confiáveis. Diante disso, este artigo apresenta ETHOS (Edge-Trusted HOSt), uma estratégia que classifica e seleciona servidores de borda baseado em níveis de confiança individual em cada servidor, independentemente do provedor que o gerencia. Experimentos demonstram que o ETHOS é capaz de reduzir as violações de privacidade e, ao mesmo tempo, minimizar as violações de latência em comparação com outras abordagens da literatura.Referências
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Souza, P., Kayser, C., Roges, L., and Ferreto, T. (2023a). Thea a qos, privacy, and power-aware algorithm for placing applications on federated edges. In 2023 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pages 136–143.
Souza, P., Vieira, Â. N. C., Rubin, F., Ferreto, T., and Rossi, F. D. (2022). Latency-aware privacy-preserving service migration in federated edges. In CLOSER, pages 288–295.
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Wang, S., Zhao, Y., Xu, J., Yuan, J., and Hsu, C.-H. (2019b). Edge server placement in mobile edge computing. Journal of Parallel and Distributed Computing, 127:160–168.
Xia, J., Cheng, G., Guo, D., and Zhou, X. (2020). A qoe-aware service-enhancement strategy for edge artificial intelligence applications. IEEE Internet of Things Journal, 7(10):9494–9506.
Aral, A., De Maio, V., and Brandic, I. (2021). Ares: Reliable and sustainable edge provisioning for wireless sensor networks. IEEE Transactions on Sustainable Computing, 7(4):761–773.
Brik, B., Frangoudis, P. A., and Ksentini, A. (2020). Service-oriented mec applications placement in a federated edge cloud architecture. In ICC 2020 2020 IEEE International Conference on Communications (ICC), pages 1–6.
Buyya, R., Srirama, S. N., Casale, G., Calheiros, R., Simmhan, Y., Varghese, B., Gelenbe, E., Javadi, B., Vaquero, L. M., Netto, M. A. S., Toosi, A. N., Rodriguez, M. A., Llorente, I. M., Vimercati, S. D. C. D., Samarati, P., Milojicic, D., Varela, C., Bahsoon, R., Assuncao, M. D. D., Rana, O., Zhou, W., Jin, H., Gentzsch, W., Zomaya, A. Y., and Shen, H. (2018). A manifesto for future generation cloud computing: Research directions for the next decade. 51(5).
Faticanti, F., Savi, M., Pellegrini, F. D., Kochovski, P., Stankovski, V., and Siracusa, D. (2020). Deployment of application microservices in multi-domain federated fog environments. In 2020 International Conference on Omni-layer Intelligent Systems (COINS), pages 1–6.
Feng, C., Han, P., Zhang, X., Yang, B., Liu, Y., and Guo, L. (2022). Computation offloading in mobile edge computing networks: A survey. Journal of Network and Computer Applications, 202:103366.
He, X., Jin, R., and Dai, H. (2020). Peace: Privacy-preserving and cost-efficient task offloading for mobile-edge computing. IEEE Transactions on Wireless Communications, 19(3):1814–1824.
Institute, E. T. S. (2023). Multi-access edge computing (mec).
Ismail, L. and Materwala, H. (2021). Escove: energy-sla-aware edge–cloud computation offloading in vehicular networks. Sensors, 21(15):5233.
Jeong, Y., Maria, E., and Park, S. (2021). Towards energy-efficient service scheduling in federated edge clouds. Cluster Computing, pages 1–13.
Kaiser, S., Haq, M. S., Tosun, A. , and Korkmaz, T. (2022). Container technologies for arm architecture: A comprehensive survey of the state-of-the-art. IEEE Access, 10:84853–84881.
Kar, B., Yahya, W., Lin, Y.-D., and Ali, A. (2023). Offloading using traditional optimization and machine learning in federated cloud–edge–fog systems: A survey. IEEE Communications Surveys Tutorials, 25(2):1199–1226.
Lin, L., Liao, X., Jin, H., and Li, P. (2019). Computation offloading toward edge computing. Proceedings of the IEEE, 107(8):1584–1607.
Souza, P., Kayser, C., Roges, L., and Ferreto, T. (2023a). Thea a qos, privacy, and power-aware algorithm for placing applications on federated edges. In 2023 31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), pages 136–143.
Souza, P., Vieira, Â. N. C., Rubin, F., Ferreto, T., and Rossi, F. D. (2022). Latency-aware privacy-preserving service migration in federated edges. In CLOSER, pages 288–295.
Souza, P. S., Ferreto, T., and Calheiros, R. N. (2023b). Edgesimpy: Python-based modeling and simulation of edge computing resource management policies. Future Generation Computer Systems, 148:446–459.
Wang, J., Feng, Z., George, S., Iyengar, R., Pillai, P., and Satyanarayanan, M. (2019a). Towards scalable edge-native applications. In Proceedings of the 4th ACM/IEEE Symposium on Edge Computing, pages 152–165.
Wang, S., Zhao, Y., Xu, J., Yuan, J., and Hsu, C.-H. (2019b). Edge server placement in mobile edge computing. Journal of Parallel and Distributed Computing, 127:160–168.
Xia, J., Cheng, G., Guo, D., and Zhou, X. (2020). A qoe-aware service-enhancement strategy for edge artificial intelligence applications. IEEE Internet of Things Journal, 7(10):9494–9506.
Publicado
17/10/2023
Como Citar
KONZEN, Marcos P.; SOUZA, Paulo S. S.; ROSSI, Fábio D.; MATTOS, Júlio C. B..
Estratégia de Posicionamento de Aplicações Sensíveis à Privacidade e Latência em Bordas Federadas. In: SIMPÓSIO EM SISTEMAS COMPUTACIONAIS DE ALTO DESEMPENHO (SSCAD), 24. , 2023, Porto Alegre/RS.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 73-84.
DOI: https://doi.org/10.5753/wscad.2023.235769.
