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Proceedings of the 21st Conference on Computer Science and Intelligence Systems (FedCSIS)

Annals of Computer Science and Information Systems, Volume 47

Towards Efficient Offloading of Time-Critical Tasks in Autonomous Edge-to-Fog Paradigms

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DOI: http://dx.doi.org/10.15439/2026F4187

Citation: Maryline Chetto,

Full text

Abstract. The uncontrollable and time-varying nature of harvested energy makes it challenging to guarantee timing requirements of the real-time software in Energy-Harvesting (EH) autonomous edge devices. In this paper, we consider that the autonomous edge device supports two kinds of hard deadline tasks: low computational periodic tasks in charge of sensing and high computational aperiodic tasks in charge of AI models. This paper provides an algorithm for online acceptance testing that decides whether to process the aperiodic task locally or offload it to the fog, based on current energy and processing conditions. This research represents a foundational step in the integration of fog resources into the IoT infrastructure, bridging the gap between local autonomy and distributed computing.

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