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

TL;DR

This paper presents a graph-based, swarm intelligence-driven framework for decentralized energy service orchestration in smart grids, emphasizing low latency, data interoperability, and traceability.

Contribution

It introduces a novel unified framework combining graph models, swarm heuristics, blockchain traceability, and real-world validation for energy service management.

Findings

Achieved zero downtime service migration in a real-world deployment.

Demonstrated efficient task offloading with low latency.

Ensured data interoperability and traceability in energy systems.

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.