## 4 An Architecture for Edge-Fog-Cloud Offloading
Extending our model with probabilistic or time series-based approaches could capture these dynamics, enabling adaptive task offloading and configuration optimisation, and enhancing the framework's robustness in variable environments. While our experiments used D1 as a representative of modestly resourced edge devices, future work will involve testing the system on smaller and more constrained IoT platforms. This will further validate the scalability and adaptability of our approach across diverse edge environments. Hence, much further work remains. Conceptualisation, N.F. ; methodology, N.F., S.W.L. and K.L. ; software, N.F. and S.S.; validation, N.F. and S.S.; investigation, N.F., S.S., S.W.L. and K.L. ; data curation, N.F. and S.S.; writing--original draft preparation, N.F., S.S., S.W.L. and K.L. ; writing--review and editing, N.F., S.S., S.W.L. and K.L. ; visualisation, N.F. and S.S.; supervision, N.F., S.W.L. and K.L. ; project administration, N.F. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Data are contained within the article. The authors declare no conflicts of interest. ## References

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