Proposing a Tool to Monitor Smart Contract Execution in Integration Processes

• Mailson Teles-Borges Unijuí http://orcid.org/0000-0001-7674-854X
• Rafael Z. Frantz Unijuí https://orcid.org/0000-0003-3740-7560
• José Bocanegra Universidad Distrital Francisco José de Caldas https://orcid.org/0000-0002-8342-7346
• Sandro Sawicki Unijuí https://orcid.org/0000-0002-7960-0775
• Fabricia Roos-Frantz Unijuí https://orcid.org/0000-0001-9514-6560

DOI: https://doi.org/10.5753/sbsi_estendido.2025.246827

Resumo

Smart cities take advantage of digital services to enhance citizens’ experiences. Integration processes facilitate interactions between these services, providing or improving functionalities. The integration can operate under specific restrictions, which can be represented through smart contracts deployed in a blockchain. Monitoring systems track interactions between integration processes and digital services by recording events from communication ports. In this paper, we argue that current monitoring tools lack the ability to observe these ports or invoke smart contracts. We propose a monitoring system to track integration processes, capture port-reported events, and invoke smart contracts on a blockchain platform.

Referências

Addas, A. (2023). The concept of smart cities: a sustainability aspect for future urban development based on different cities. Frontiers in Environmental Science, pages 1–2.

Bautista, E., Sukhija, N., and Deng, S. (2022). Shasta log aggregation, monitoring and alerting in hpc environments with grafana loki and servicenow. In Int. Conf. on Cluster Computing, pages 602–610.

Datadog (2025). [link]. Accessed: January 2025.

Dornelles, E., Parahyba, F., Frantz, R. Z., Roos-Frantz, F., Reina-Quintero, A., Molina-Jiménez, C., Bocanegra, J., and Sawicki, S. (2022). Advances in a DSL to specify smart contracts for application integration processes. In Ibero-American Conference on Software Engineering, pages 46–60.

Dynatrace (2025). [link]. Accessed: January 2025.

Elastic (2025). [link]. Accessed: January 2025.

Fabolude, G., Knoble, C., Vu, A., and Yu, D. (2025). Smart cities, smart systems: A comprehensive review of system dynamics model applications in urban studies in the big data era. Geography and Sustainability, pages 1–12.

Grafana (2025). [link]. Accessed: January 2025.

Klymash, M., Zablotskyi, S., and Pohranychnyi, V. (2024). Improving alerting in the monitoring system using machine learning algorithms. In Int. Conf. on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering, pages 150–153.

Otero, M., Garcia, J. M., and Fernandez, P. (2024). Towards a lightweight distributed telemetry for microservices. In Int. Conf. on Distributed Computing Systems Workshops, pages 75–82.

Rosa-Sequeira, F., Basto-Fernandes, V., and Frantz, R. Z. (2018). Enterprise application integration: Approaches and platforms to design and implement solutions in the cloud. Advances in Engineering Research, pages 277–303.

Serrano, W. (2018). Digital systems in smart city and infrastructure: Digital as a service. Smart cities, pages 134–154.

Sukhija, N. and Bautista, E. (2019). Towards a framework for monitoring and analyzing high performance computing environments using kubernetes and prometheus. In SmartWord, pages 257–262.

Taheri, J., Gördén, A., and Al-Dulaimy, A. (2024). Using machine learning to predict the exact resource usage of microservice chains. In Int. Conf. on Utility and Cloud Computing, pages 25–34.

Tundo, A., Mobilio, M., Orrù, M., Riganelli, O., Guzmàn, M., and Mariani, L. (2019). Varys: An agnostic model-driven monitoring-as-a-service framework for the cloud. In European Software Engineering Conference and Symposium on the Foundations of Software Engineering, pages 1085–1089.

Zou, W., Lo, D., Kochhar, P. S., Le, X.-B. D., Xia, X., Feng, Y., Chen, Z., and Xu, B. (2019). Smart contract development: Challenges and opportunities. IEEE Transactions on Software Engineering, pages 2084–2106.