Proceedings of the 20th Conference on Computer Science and Intelligence Systems (FedCSIS)

DOI: http://dx.doi.org/10.15439/2025F4345

Citation: Proceedings of the 20th Conference on Computer Science and Intelligence Systems (FedCSIS), M. Bolanowski, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 43, pages 1–2 (2025)

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Abstract. Distributed applications now span sensors, edge nodes, fog clusters, and hyperscale clouds. Meeting service-level objectives across this ``Distributed Computing Continuum'' persistently fails when management is reactive, centralized, and blind to uncertainty. I argue for predictive equilibrium as the control objective and for a concrete diagnostic: the Kullback--Leibler divergence between a system's expected and observed causal behavior under perturbations, each modeled with a Bayesian network. This perspective draws from predictive regulation in neuroscience and the fluctuation--dissipation view of equilibrium in physics, and it sets the stage for antifragility---systems that get better because they were stressed, not despite it.

References

1. S. Dustdar, V. Casamayor Pujol, and P. K. Donta, “On Distributed Computing Continuum Systems,” IEEE Trans. Knowl. Data Eng., vol. 35, no. 4, pp. 4092–4105, Apr. 2023, https://dx.doi.org/10.1109/TKDE.2022.3142856.
2. V. Casamayor Pujol, B. Sedlak, Y. Xu, P. K. Donta, and S. Dustdar, “DeepSLOs for the Computing Continuum,” in Proceedings of the 2024 Workshop on Advanced Tools, Programming Languages, and PLatforms for Implementing and Evaluating algorithms for Distributed systems, in ApPLIED’24. New York, NY, USA: Association for Computing Machinery, Jun. 2024, pp. 1–10. https://dx.doi.org/10.1145/3663338.3663681.
3. B. Sedlak, V. C. Pujol, P. K. Donta, and S. Dustdar, “Equilibrium in the Computing Continuum through Active Inference,” Future Gener. Comput. Syst., May 2024, https://dx.doi.org/10.1016/j.future.2024.05.056.
4. V. Casamayor Pujol, B. Sedlak, P. K. Donta, and S. Dustdar, “On Causality in Distributed Continuum Systems,” IEEE Internet Comput., vol. 28, no. 2, pp. 57–64, Mar. 2024, https://dx.doi.org/10.1109/MIC.2023.3344248.
5. V. C. Pujol, B. Sedlak, T. Salvatori, K. Friston, and S. Dustdar, “Distributed Intelligence in the Computing Continuum with Active Inference,” May 30, 2025, https://arxiv.org/abs/2505.24618. https://dx.doi.org/10.48550/arXiv.2505.24618.