🤖 AI Summary
This work addresses the challenges of decentralized, low-latency service orchestration in smart grids under the integration of IoT and distributed energy management. To this end, the authors propose a unified task orchestration framework tailored for edge–fog–cloud collaborative architectures. The framework combines graph-driven modeling with swarm intelligence–based optimization to enable resource-aware, low-latency task offloading. System interoperability is ensured through adherence to Energy Data Space standards, while blockchain technology guarantees traceability of workloads. Real-world deployment experiments based on KubeEdge demonstrate that the proposed approach achieves zero-downtime service migration and sustained service availability under dynamic workloads, significantly enhancing both system responsiveness and reliability.
📝 Abstract
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.