Internet of Medical Things: A Performance Assessment Focusing on Priorities of Claims
Abstract
The Internet of Medical Things (IoHT) is a subarea of the Internet of Things focused on the health context. IoT monitoring devices are equipped with sensors and actuators that can take a certain action and even save lives. However, there are medical situations that require more sophisticated computer systems that generate a large load of data and require real-time response. In this case, it is often necessary to evaluate possible distributed system architectures to support the sensor network. This work presents a queuing network model representing an IoHT architecture with priority requests. The model is highly configurable and can assist technology professionals in the context of IoHT.
Keywords:
Health computing, queuing theory, IoHT
References
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Bertoli, M., Casale, G., and Serazzi, G. (2009). Jmt: performance engineering tools forsystem modeling.SIGMETRICS Perform. Eval. Rev., 36(4):10–15.
de Morais Barroca Filho, I. and de Aquino Junior, G. S. (2017). Iot-based healthcareapplications: a review. InInternational conference on computational science and itsapplications, pages 47–62. Springer.
El Kafhali, S. and Salah, K. (2018). Performance modelling and analysis of internet ofthings enabled healthcare monitoring systems.IET Networks, 8(1):48–58
Haragos, I.-M. and Cernazanu-Glavan, C. (2012). Modelling road traffic using servicecenter.AECE 2012, 2
He, D., Ye, R., Chan, S., Guizani, M., and Xu, Y. (2018). Privacy in the internet of thingsfor smart healthcare.IEEE Communications Magazine, 56(4):38–44.
Iorga, M., Feldman, L., Barton, R., Martin, M. J., Goren, N. S., and Mahmoudi, C. (2018).Fog computing conceptual model.
Islam, M. M., Rahaman, A., and Islam, M. R. (2020). Development of smart healthcaremonitoring system in iot environment.SN computer science, 1:1–11.
Khoa, T. V., Saputra, Y. M., Hoang, D. T., Trung, N. L., Nguyen, D., Ha, N. V., and Dut-kiewicz, E. (2020). Collaborative learning model for cyberattack detection systems iniot industry 4.0. In2020 IEEE Wireless Communications and Networking Conference(WCNC), pages 1–6. IEEE.
Maktoubian, J. and Ansari, K. (2019). An iot architecture for preventive maintenance ofmedical devices in healthcare organizations.Health and Technology, 9(3):233–243.
Mohammadian, H. D., Mohammadian, F. D., and Assante, D. (2020). Iot-education po-licies on national and international level regarding best practices in german smes. In2020 IEEE Global Engineering Education Conf. (EDUCON), pages 1848–1857. IEEE.
Mukherjee, A., Ghosh, S., Behere, A., Ghosh, S. K., and Buyya, R. (2020). Internetof health things (ioht) for personalized health care using integrated edge-fog-cloudnetwork.Journal of Ambient Intelligence and Humanized Computing, pages 1–17.
Rubin, J., Abreu, R., Ganguli, A., Nelaturi, S., Matei, I., and Sricharan, K. (2017). Recog-nizing abnormal heart sounds using deep learning.arXiv preprint arXiv:1707.04642.
Sarmah, S. S. (2020). An efficient iot-based patient monitoring and heart disease predic-tion system using deep learning modified neural network.IEEE Access, 8:135784–135797.
Shafiq, M., Tian, Z., Sun, Y., Du, X., and Guizani, M. (2020). Selection of effective ma-chine learning algorithm and bot-iot attacks traffic identification for internet of thingsin smart city.Future Generation Computer Systems, 107:433–442.
Sztrik, J. et al. (2012). Basic queueing theory.University of Debrecen, Faculty of Infor-matics, 193:60–67.
Uslu, B. ç ., Okay, E., and Dursun, E. (2020). Analysis of factors affecting iot-based smarthospital design.Journal of Cloud Computing, 9(1):1–23.
Yassein, M. B., Hmeidi, I., Al-Harbi, M., Mrayan, L., Mardini, W., and Khamayseh,Y. (2019). Iot-based healthcare systems: a survey. InProceedings of the SecondInternational Conf. on Data Science, E-Learning and Information Systems, pages 1–9
Published
2021-07-18
How to Cite
SANTOS, Lucas; SANTOS, Brena; SILVA, Francisco Airton.
Internet of Medical Things: A Performance Assessment Focusing on Priorities of Claims. In: PROCEEDINGS OF BRAZILIAN SYMPOSIUM ON UBIQUITOUS AND PERVASIVE COMPUTING (SBCUP), 13. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 21-30.
ISSN 2595-6183.
DOI: https://doi.org/10.5753/sbcup.2021.16000.
