Minimizing Age of Information in Orbital Edge Computing via Dual Queue Offloading

Kurzfassung

We study the minimization of age of information (AoI) in a dual-queue architecture for satellite-assisted Internet of things systems. We consider multiple source-monitor pairs that generate status updates that can be processed locally or offloaded to a shared common server, introducing a trade-off between queueing delay and propagation latency. The objective is to determine the optimal offloading probability that minimizes the average AoI under shared resource contention. To address the structural complexity of heterogeneous queues, we propose a closed-form, non-iterative heuristic based on the optimal operating points of individual queues. The resulting policy adopts a piecewise workload allocation strategy that proportionally distributes traffic at low load and prioritizes the most AoI-efficient server at high load. The numerical results show that the proposed scheme closely approximates the minimum-AoI performance across different service rates and propagation delay regimes, providing a scalable and practical solution for AoI-aware task offloading in orbital edge computing systems.