HealthStack: Providing an IoT Middleware for Malleable QoS Service Stacking for Healthcare 4.0
Resumo
Com a utilização de sensores inteligentes em hospitais, o monitoramento e processamento dos dados é de extrema importância para melhorar serviços médicos. Em particular, esses dispositivos podem auxiliar na tomadas de decisões críticas. Nesse contexto, a qualidade do serviço (QoS) é essencial para garantir a confiabilidade dos dados das aplicações. Dito isso, esse artigo propõem HealthStack, um middleware para salas cirúrgicas com QoS automático e suporte a transmissão de dados em tempo real. O artigo propõe uma estratégia de QoS baseada em neurônios artificiais para seleção dos componentes do middleware com baixa performance. Foi desenvolvido e testado um protótipo do modelo em uma sala de cirurgia real. A avaliação demonstra que a estratégia pode melhorar o jitter médio de aplicações em até 90,3%.Referências
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Samanta, A. and Misra, S. (2018). Dynamic connectivity establishment and cooperative scheduling for qos-aware wireless body area networks. IEEE Transactions on Mobile Comp., 17(12):2775–2788.
Sodhro, A. H., Luo, Z., Sangaiah, A. K., and Baik, S. W. (2019). Mobile edge computing based qos optimization in medical healthcare applications. Int. Journal of Information Management, 45:308 – 318.
Wang, J., Sun, Y., and Ji, Y. (2018). Qos-based adaptive power control scheme for co-located wbans: a cooperative bargaining game theoretic perspective. Wireless Networks, 24(8):3129–3139.
Wang, Q. et al. (2019). Enable advanced qos-aware network slicing in 5g networks for slice-based media use cases. IEEE Transactions on Broadcasting, 65(2):444–453.
Bai, T., Lin, J., Li, G., Wang, H., Ran, P., Li, Z., Pang, Y., Wu, W., and Jeon, G. (2019). An optimized protocol for qos and energy efciency on wireless body area networks. Peer-to-Peer Networking and Applications, 12(2):326–336.
Goyal, R., Patel, R., Bhaduria, H., and Prasad, D. (2020). An energy efcient qos supported optimized transmission rate technique in wbans. Wireless Pers. C., pages 1–26.
Guezguez, M. J., Rekhis, S., and Boudriga, N. (2018). A sensor cloud for the provision of secure and qos-aware healthcare services. Arabian Journal for Science and Eng., 43(12):7059–7082.
Nanda, P. and Fernandes, R. C. (2007). Quality of service in telemedicine. In First Int. Conf. on the Digital Society (ICDS’07), pages 2–2.
Nielsen, M. A. (2015). Neural Networks and Deep Learning, volume 2018. Determination Press San Francisco, CA, USA:.
Samanta, A., Li, Y., and Chen, S. (2018). Qos-aware heuristic scheduling with delayconstraint for wbsns. In 2018 IEEE Int. Conf. on Communications (ICC), pages 1–7.
Samanta, A. and Misra, S. (2018). Dynamic connectivity establishment and cooperative scheduling for qos-aware wireless body area networks. IEEE Transactions on Mobile Comp., 17(12):2775–2788.
Sodhro, A. H., Luo, Z., Sangaiah, A. K., and Baik, S. W. (2019). Mobile edge computing based qos optimization in medical healthcare applications. Int. Journal of Information Management, 45:308 – 318.
Wang, J., Sun, Y., and Ji, Y. (2018). Qos-based adaptive power control scheme for co-located wbans: a cooperative bargaining game theoretic perspective. Wireless Networks, 24(8):3129–3139.
Wang, Q. et al. (2019). Enable advanced qos-aware network slicing in 5g networks for slice-based media use cases. IEEE Transactions on Broadcasting, 65(2):444–453.
Publicado
15/06/2021
Como Citar
RODRIGUES, Vinicius F.; RIGHI, Rodrigo da R.; COSTA, Cristiano A. da.
HealthStack: Providing an IoT Middleware for Malleable QoS Service Stacking for Healthcare 4.0. In: CONCURSO DE TESES E DISSERTAÇÕES - SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO APLICADA À SAÚDE (SBCAS), 21. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 25-30.
ISSN 2763-8987.
DOI: https://doi.org/10.5753/sbcas.2021.16096.