STAR-GS: Truthful and Visibility-Aware Resource Scheduling for Ground Station as a Service

2026-08-23

AI Summary

为解决地面站服务中资源调度问题，提出STAR-GS机制，结合拍卖理论与调度分析，实现任务准入、分配及定价，以最大化收益。

Abstract

The rapid growth of Low Earth Orbit satellite constellations has created increasing demand for efficient and scalable downlink services. Ground Station as a Service (GSaaS) provides an on-demand access model for satellite operators, but commercial GSaaS providers must schedule limited ground-station bandwidth among multiple satellites with heterogeneous data demands, overlapping visibility windows, strict deadlines, and strategic bidding behaviors. This paper studies GSaaS resource scheduling from a ground-station-centric perspective, where the provider jointly determines task admission, ground-station assignment, bandwidth allocation, and payments. Under satellite orbital dynamics, bandwidth constraints, and downlink task deadlines, maximizing the provider's revenue is NP-hard. To address this challenge, we propose STAR-GS, a truthful and feasibility-aware scheduling mechanism that combines bid-aware admission control, best-fit ground-station assignment, Earliest Deadline First (EDF)-based bandwidth scheduling, and critical-payment pricing. By integrating auction theory with schedulability analysis, STAR-GS incentivizes task owners to truthfully report their private valuations while ensuring that admitted tasks can be feasibly completed before their deadlines. Simulations using Ansys Systems Tool Kit (STK) show that STAR-GS consistently achieves higher revenue than heuristic baselines, obtains near-MILP performance with substantially lower runtime, and scales smoothly to workloads containing up to 900 tasks.

Problem

• Low Earth Orbit
• Ground Station as a Service
• resource scheduling
• bandwidth allocation
• downlink services

Innovation

• truthful and visibility-aware scheduling
• bid-aware admission control
• best-fit ground-station assignment
• Earliest Deadline First (EDF)
• critical-payment pricing