As smart grids increasingly depend on IoT devices and distributed energy management, they require decentralized, low latency orchestration of energy services. We address this with a unified framework for edge fog cloud infrastructures tailored to smart energy systems. It features a graph based data model that captures infrastructure and workload, enabling efficient topology exploration and task placement. Leveraging this model, a swarm-based heuristic algorithm handles task offloading in a resource-aware, latency sensitive manner. Our framework ensures data interoperability via energy data space compliance and guarantees traceability using blockchain based workload notarization. We validate our approach with a real-world KubeEdge deployment, demonstrating zero downtime service migration under dynamic workloads while maintaining service continuity.
@article{arxiv.2604.04645,
title = {Edge-Oriented Orchestration of Energy Services Using Graph-Driven Swarm Intelligence},
author = {Liana Toderean and Dragos Lazea and Vasile Ofrim and Stefania Dumbrava and Anca Hangan and Tudor Cioara},
journal= {arXiv preprint arXiv:2604.04645},
year = {2026}
}
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2nd Workshop on Enabling Machine Learning Operations for next-Gen Embedded Wireless Networked Devices, Sept 22, Leuven, Belgium