Edge-Oriented Orchestration of Energy Services Using Graph-Driven Swarm Intelligence

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.

Figures (5)

• Figure 1: Orchestration framework architecture
• Figure 2: Unified graph model
• Figure 3: Structure of a Task Token
• Figure 4: Blockchain task tracking flow
• Figure 5: Overview of pod migration performance: CPU, bandwidth, and latency overhead