Matchmaker: Maintaining QoS-aware and Predictable Load Balancing Performance for LEO Mega-Constellations

With millions of users introducing significant traffic loads, maintaining effective load balancing in Low Earth Orbit (LEO) mega-constellations is challenging due to satellites’ limited processing capabilities. While existing studies primarily focus on constellations fully equipped with inter-satellite links, this paper addresses the less-explored yet critical issue of achieving QoS-aware load balancing in existing bent pipe architectures. We identify user-satellite assignment as a key determinant of satellite load and propose MATCHMAKER, a strategy that balances satellite load by optimizing user-satellite assignment while simultaneously minimizing disruptive handovers. Specifically, we formulate the QoS-aware User-Satellite Assignment problem to jointly minimize maximum satellite utilization and user-satellite handovers. Given the NP-hardness of this problem, we propose a heuristic algorithm with a performance guarantee. Evaluation results demonstrate that MATCHMAKER improves load balancing performance by up to 130.22% and reduces handovers by up to 46.88% compared to state-of-the-art methods.