Scalability Evaluation of the Sentilo Platform Running on Containerized Resources

• Diogo C. P. Domingos Unioeste
• Marcelo A. C Ismael UTFPR / UFPR
• Guilherme Galante Unioeste
• Eduardo Prasniewski UTFPR
• Wesley K. G. Assunção NCSU
• Marcio S. Oyamada Unioeste
• Luis C. E. de Bona UFPR
• Edson T. de Camargo Unioeste / UTFPR

DOI: https://doi.org/10.5753/wperformance.2025.8105

Resumo

A smart city software platform is an integrated environment that helps developers design, implement, deploy, and manage smart city applications. Sentilo is the platform selected to manage smart city solutions in a medium-sized city (Toledo, PR, Brazil) through a partnership between the local university and city administration. This paper aims to evaluate Sentilo’s scalability under different workloads and hardware configurations for both data receiving and provisioning. Results show that Sentilo offers sufficient performance to support the planned and new applications in the city.

Referências

Araujo, V., Mitra, K., Saguna, S., and Åhlund, C. (2019). Performance evaluation of fiware: A cloud-based iot platform for smart cities. JPDC, 132:250–261.

Camargo, E. T., Spanhol, F. A., and Castro e Souza, A. R. (2021). Deployment of a lorawan network and evaluation of tracking devices in the context of smart cities. JISA, 12(8):1–24.

de Camargo, E. T. et al. (2023). Low-cost water quality sensors for iot: A systematic review. Sensors, 23(9).

de M. Del Esposte et al. (2019). Design and evaluation of a scalable smart city software platform with large-scale simulations. Future Generation Computer Systems, 93:427–441.

Droprinchinski, L., Tavares de Camargo, E., and de Morais, M. V. B. (2023). Low-cost sensors for odor monitoring: the state of the art and challenges. In 2023 IEEE International Smart Cities Conference (ISC2), pages 01–04.

Goumopoulos, C. (2024). Smart city middleware: A survey and a conceptual framework. IEEE Access, 12:4015–4047.

Ismail, A. A., Hamza, H. S., and Kotb, A. M. (2018). Performance evaluation of open source iot platforms. In 2018 IEEE global conference on internet of things (GCIoT), pages 1–5. IEEE.

Lai, C. S., Jia, Y., Dong, Z., Wang, D., Tao, Y., Lai, Q. H., Wong, R. T. K., Zobaa, A. F., Wu, R., and Lai, L. L. (2020). A review of technical standards for smart cities. Clean Technologies, 2(3):290–310.

Pereira, J., Batista, T., Cavalcante, E., Souza, A., Lopes, F., and Cacho, N. (2022). A platform for integrating heterogeneous data and developing smart city applications. Future Generation Computer Systems, 128:552–566.

Roncaglio, M. M. et al. (2023). Development of an air quality station using low-cost sensors. In 2023 XIII Brazilian Symposium on Computing Systems Engineering (SBESC), pages 1–6.

Santana, E. F. Z. et al. (2017). Software platforms for smart cities: Concepts, requirements, challenges, and a unified reference architecture. ACM Comput. Surv., 50(6).

Sentilo (2014). Sentilo - sensor and actuator platform for smart cities. [link]. Accessed on: June 18th. 2024.

Sinaeepourfard, A. and outros (2016). Estimating smart city sensors data generation. In 2016 Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net), pages 1–8.

Sánchez-Corcuera, R. et al. (2019). Smart cities survey: Technologies, application domains and challenges for the cities of the future. Int. JDSN, 15(6).

Tabassum, M., Puryear, N., Kuzlu, M., Jovanovic, V., and Abdelwahed, S. (2023). Performance evaluation of a cloud-based iot platform for smart cities: Opencybercity. In 2023 12th Mediterranean Conference on Embedded Computing (MECO). IEEE.

Xavier, F. et al. (2022). Evaluation of low-cost sensors for real-time water quality monitoring. In Anais Estendidos do XII Simpósio Brasileiro de Engenharia de Sistemas Computacionais, pages 56–61. SBC.