Avaliação de Desempenho de uma Arquitetura de Sistema de Monitoramento de Pacientes em Hospitais Inteligentes com Fontes de Dados Interna e Externa
Abstract
The variety of sensors for health monitoring helps in decision making by medical professionals. For certain clinical situations, it is interesting to monitor the patient’s health after discharge. Wearable health monitoring devices (such as smartwatches) can be used to keep sending data to the hospital. However, for monitoring a large number of patients (external and internal), a resilient and high-performance computing infrastructure is required. Such characteristics require high monetary cost equipment. To help plan such an infrastructure, this paper presents an SPN (Stochastic Petri Network) model for evaluating the performance of a multi-tier hospital system architecture (edge-fog-cloud). The model allows evaluating the mean response time (MRT), level of resource utilization (U) and probability of data loss (DP). A very specific characteristic is to consider two data sources (internal and external). As a case study, the impact of varying the number of containers (from 5 to 100) for simultaneous processing in the cloud was analyzed. With capacity 50, 75 and 100 simultaneous containers, the result was similar, with MRT below 25 seconds. For capacity 5 and 25 containers, MRT has reached 150 seconds.
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Araujo, J., Silva, B., Oliveira, D., and Maciel, P. (2014). Dependability evaluation of a mhealth system using a mobile cloud infrastructure. In 2014 IEEE international conference on systems, man, and cybernetics (SMC), pages 1348–1353. IEEE.
Brito, C., Rodrigues, L., Santos, B., Fé, I., Nguyen, T.-A., Min, D., Lee, J.-W., and Silva, F. A. (2021). Stochastic model driven performance and availability planning for a mobile edge computing system. Applied Sciences, 11(9):4088.
Chen, X., Thomas, N., and Harrison, M. (2011). Performance evaluation of scheduling policies in a smart hospital environment. In 2011 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery, pages 585–592. IEEE.
Costa, I., Araujo, J., Dantas, J., Campos, E., Silva, F. A., and Maciel, P. (2016). Availability evaluation and sensitivity analysis of a mobile backend-as-a-service platform. Quality and Reliability Engineering International, 32(7):2191–2205.
Gomez-Sacristan, A., Rodriguez-Hernandez, M. A., and Sempere, V. (2015). Evaluation of quality of service in smart-hospital communications. Journal of Medical Imaging and Health Informatics, 5(8):1864–1869.
Huang, D. Y., Apthorpe, N., Li, F., Acar, G., and Feamster, N. (2020). Iot inspector: Crowdsourcing labeled network traffic from smart home devices at scale. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 4(2):1–21.
Kaur, M., Malhotra, J., and Kaur, P. D. (2020). A vanet-iot based accident detection and management system for the emergency rescue services in a smart city. In 2020 8th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions)(ICRITO), pages 964–968. IEEE.
Khayal, I. S. and Farid, A. M. (2021). A dynamic system model for personalized healthcare delivery and managed individual health outcomes. IEEE Access, 9:138267–138282.
Little, J. D. (1961). A proof for the queuing formula: L= λ w. Operations research, 9(3):383–387.
Maciel, P., Matos, R., Silva, B., Figueiredo, J., Oliveira, D., Fé, I., Maciel, R., and Dantas, J. (2017). Mercury: Performance and dependability evaluation of systems with exponential, expolynomial, and general distributions. In 2017 IEEE 22nd Pacific Rim international symposium on dependable computing (PRDC), pages 50–57. IEEE.
Ndiaye, M., Oyewobi, S. S., Abu-Mahfouz, A. M., Hancke, G. P., Kurien, A. M., and Djouani, K. (2020). Iot in the wake of covid-19: A survey on contributions, challenges and evolution. IEEE Access, 8:186821–186839.
Nguyen, T. A., Fe, I., Brito, C., Kaliappan, V. K., Choi, E., Min, D., Lee, J. W., and Silva, F. A. (2021). Performability evaluation of load balancing and fail-over strategies for medical information systems with edge/fog computing using stochastic reward nets. Sensors, 21(18):6253.
Rajasekaran, M., Yassine, A., Hossain, M. S., Alhamid, M. F., and Guizani, M. (2019). Autonomous monitoring in healthcare environment: Reward-based energy charging mechanism for iomt wireless sensing nodes. Future Generation Computer Systems, 98:565–576.
Rodrigues, L., Gonçalves, I., Fé, I., Endo, P. T., and Silva, F. A. (2021). Performance and availability evaluation of an smart hospital architecture. Computing, 103(10):2401–2435.
Santos, G. L., Gomes, D., Silva, F. A., Endo, P. T., and Lynn, T. (2022). Maximising the availability of an internet of medical things system using surrogate models and nature-inspired approaches. International Journal of Grid and Utility Computing, 13(2-3):291–308.
Santos, L., Cunha, B., Fé, I., Vieira, M., and Silva, F. A. (2021). Data processing on edge and cloud: a performability evaluation and sensitivity analysis. Journal of Network and Systems Management, 29(3):1–24.
Silva, F. A., Brito, C., Araújo, G., Fé, I., Tyan, M., Lee, J.-W., Nguyen, T. A., and Maciel, P. R. M. (2022). Model-driven impact quantification of energy resource redundancy and server rejuvenation on the dependability of medical sensor networks in smart hospitals. Sensors, 22(4):1595.
Silva, F. A., Nguyen, T. A., Fé, I., Brito, C., Min, D., and Lee, J.-W. (2021). Performance evaluation of an internet of healthcare things for medical monitoring using m/m/c/k queuing models. IEEE Access, 9:55271–55283.
Singh, R. P., Javaid, M., Haleem, A., and Suman, R. (2020). Internet of things (iot) applications to fight against covid-19 pandemic. Diabetes & Metabolic Syndrome: Clinical Research & Reviews.
Uslu, B. Ç., Okay, E., and Dursun, E. (2020). Analysis of factors affecting iot-based smart hospital 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. In Proceedings of the Second International Conference on Data Science, E-Learning and Information Systems, pages 1–9.
Published
2023-08-06
How to Cite
ROCHA, Francisco M. S.; SANTOS, Lucas Vinícius S. dos; SILVA, Francisco Airton.
Avaliação de Desempenho de uma Arquitetura de Sistema de Monitoramento de Pacientes em Hospitais Inteligentes com Fontes de Dados Interna e Externa. In: WORKSHOP ON PERFORMANCE OF COMPUTER AND COMMUNICATION SYSTEMS (WPERFORMANCE), 22. , 2023, João Pessoa/PB.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 73-84.
ISSN 2595-6167.
DOI: https://doi.org/10.5753/wperformance.2023.230079.
