Edge-Based Digital Twins for QoS-Aware Orchestration in Heterogeneous UAV Fleets

Abstract

Heterogeneous multi-UAV fleets act as highly dynamic mobile Internet of Things (IoT) nodes, but they often integrate platforms with incompatible telemetry and control semantics, hindering safe and scalable coordination. This paper presents an Asset Administration Shell (AAS)-driven digital twin architecture for the cloud continuum that decouples protocol translation from mission orchestration, pushing compute power closer to the edge. The first contribution of this work is a four-layer communication model mapped across the IoT and edge continuum, spanning physical-digital synchronization at the network edge, inter-digital-twin interaction, digitaltwin/GCS supervision in the fog/cloud layer, and a safety-critical physical/GCS bypass. The second contribution is a UAV AAS submodel that standardizes runtime state, energy, payload, and wireless QoS descriptors. The third contribution is an analytical validation framework based on bounded digital-twin staleness $\left(\Delta S_{\max }=30 ~\text{ms}\right)$ to evaluate semantic task reallocation and QoS-aware telemetry adaptation. At a representative cruise speed of 15 m/s, the worst-case position uncertainty induced by semantic latency is 0.45 m, which is acceptable for highlevel mission handoff. For degraded links, stability conditions are derived for queue-bounded latest-state forwarding and hysteresis-based telemetry control. The analysis indicates that AAS enables protocol-agnostic interoperability while preserving orchestration timeliness.