HealthStack: Providing an IoT Middleware for Malleable QoS Service Stacking for Healthcare 4.0
Abstract
With smart sensors in hospitals, monitor and process data is crucial to improve medical services. In particular, these devices can assist in making critical decisions that can save lives. In this context, quality of service (QoS) is essential to ensure application data reliability. That said, this article proposes HealthStack, a middleware for operating rooms with automatic QoS and support for real-time data transmission. We also present a QoS strategy based on artificial neurons to select middleware components with critical performance. We developed a prototype of the model and tested it in an actual operating room. The evaluation shows that the strategy improves the average jitter experienced by the application by 90.3%.References
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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.
Published
2021-06-15
How to Cite
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: THESIS AND DISSERTATION CONTEST - BRAZILIAN SYMPOSIUM ON COMPUTING APPLIED TO HEALTHCARE (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.
