Negociação de Contratos Inteligentes em Blockchain Baseado em Agentes para Sistemas de Distribuição de Conteúdos Educacionais
Resumo
Este trabalho explora a viabilidade de uma rede de armazenamento de conteúdo educacional em nuvem descentralizada por meio de um modelo de simulação baseado em agentes. O modelo incorpora dinâmicas realistas como capacidade finita de armazenamento, contratos com duração limitada, latência de rede e múltiplas fontes de falha. A simulação executada em múltiplos cenários de escalabilidade revelou que, mesmo com agentes baseados em regras simples, a arquitetura é funcional e economicamente viável. Os resultados validam o modelo conceitual e estabelecem uma base sólida para o futuro desenvolvimento de um sistema de agentes para negociação de smart contracts em blockchain em um ecossistema de negócios de armazenamento de conteúdo educacional.
Palavras-chave:
Armazenamento Descentralizado, Sistemas Multiagentes, Blockchain
Referências
Canelhas, G. d. S. M. (2022). Educational Videos for Pre-School Children: Challenges in the Creation and Content Distribution in Digital Platforms. PhD thesis, Universidade NOVA de Lisboa (Portugal).
George, A. S. (2023). Silicon valley rising: how big tech may eclipse nation states. Partners Universal Innovative Research Publication, 1(1):102–119.
He, Q. and Wang, K. (2023). Intelligent content distribution system: A machine learning-based teaching content customization method. International Journal of Emerging Technologies in Learning, 18(17).
Huang, H., Lin, J., Zheng, B., Zheng, Z., and Bian, J. (2020). When blockchain meets distributed file systems: An overview, challenges, and open issues. IEEE Access, 8:50574–50586.
Lanchester, J. (2017). You are the product. London Review of Books, 39(16):3–10.
Laszlo, E. (1984). Cybernetics in an evolving social system. Kybernetes, 13(3):141–145.
Muller, M. M. (1982). Vulnerable Sovereignty: A cybernetic essay in political sciences. PhD thesis, Brunel University School of Engineering and Design PhD Theses.
Pimentel, J. and Castro, J. (2018). pistar tool–a pluggable online tool for goal modeling. In 2018 IEEE 26th International Requirements Engineering Conference (RE), pages 498–499. IEEE.
Prokurovsky, A., Toutova, N., and Andreev, I. (2025). Content delivery network for e-learning based on enterprise service bus. In 2025 Systems of Signals Generating and Processing in the Field of on Board Communications, pages 1–4. IEEE.
Russell, S. J. and Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Prentice Hall, 4th edition.
Segato, T. H. F., Ralha, C. G., and Fernandes, S. E. S. (2021). Development process of multiagent system for glycemic control of intensive care unit patients. Artif. Intell. Res., 10(1):43.
Snihur, Y. and Bocken, N. (2022). A call for action: The impact of business model innovation on business ecosystems, society and planet. Long Range Planning, 55(6):102182.
Woods, D. (2024). The illusion of power: Unpacking the vulnerabilities of big tech in the face of sovereign states. Chinese Political Science Review, pages 1–29.
Wooldridge, M. (2009). An Introduction to MultiAgent Systems. John Wiley & Sons, 2nd edition.
George, A. S. (2023). Silicon valley rising: how big tech may eclipse nation states. Partners Universal Innovative Research Publication, 1(1):102–119.
He, Q. and Wang, K. (2023). Intelligent content distribution system: A machine learning-based teaching content customization method. International Journal of Emerging Technologies in Learning, 18(17).
Huang, H., Lin, J., Zheng, B., Zheng, Z., and Bian, J. (2020). When blockchain meets distributed file systems: An overview, challenges, and open issues. IEEE Access, 8:50574–50586.
Lanchester, J. (2017). You are the product. London Review of Books, 39(16):3–10.
Laszlo, E. (1984). Cybernetics in an evolving social system. Kybernetes, 13(3):141–145.
Muller, M. M. (1982). Vulnerable Sovereignty: A cybernetic essay in political sciences. PhD thesis, Brunel University School of Engineering and Design PhD Theses.
Pimentel, J. and Castro, J. (2018). pistar tool–a pluggable online tool for goal modeling. In 2018 IEEE 26th International Requirements Engineering Conference (RE), pages 498–499. IEEE.
Prokurovsky, A., Toutova, N., and Andreev, I. (2025). Content delivery network for e-learning based on enterprise service bus. In 2025 Systems of Signals Generating and Processing in the Field of on Board Communications, pages 1–4. IEEE.
Russell, S. J. and Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Prentice Hall, 4th edition.
Segato, T. H. F., Ralha, C. G., and Fernandes, S. E. S. (2021). Development process of multiagent system for glycemic control of intensive care unit patients. Artif. Intell. Res., 10(1):43.
Snihur, Y. and Bocken, N. (2022). A call for action: The impact of business model innovation on business ecosystems, society and planet. Long Range Planning, 55(6):102182.
Woods, D. (2024). The illusion of power: Unpacking the vulnerabilities of big tech in the face of sovereign states. Chinese Political Science Review, pages 1–29.
Wooldridge, M. (2009). An Introduction to MultiAgent Systems. John Wiley & Sons, 2nd edition.
Publicado
24/11/2025
Como Citar
SOUSA, Gabriel de; LIMA, Gabriel Felix de; MORAES, Victor André de; TOKARSKI, Thiago Masera; DEZAN, Gustavo Lopes; ISHIKAWA, Edison.
Negociação de Contratos Inteligentes em Blockchain Baseado em Agentes para Sistemas de Distribuição de Conteúdos Educacionais. In: WORKSHOP SOBRE DESCENTRALIZAÇÃO EM INFORMÁTICA NA EDUCAÇÃO (WDESCENTRAIE), 1. , 2025, Curitiba/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 22-26.
DOI: https://doi.org/10.5753/wdescentraie.2025.16267.
