StarPerf: Characterizing Network Performance for Emerging Mega-Constellations

"Newspace" mega-constellations, such as Starlink and OneWeb are gaining tremendous popularity, with the promising potential to provide high-capacity and low-latency communication globally. However, very little is known about the architecture and performance of such emerging systems, the workload they have to face, as well as the impact of topological options on the attainable network performance. This paper presents StarPerf, a mega-constellation performance simulation platform that enables constellation manufacturers and content providers to estimate and understand the achievable performance under a variety of constellation options. The proposed platform integrates two key techniques: (1) performance simulation for mega-constellation, which captures the impact of the inherent high mobility in satellite networks and profiles the area-to-area attainable network performance; (2) constellation scaling, which synthesizes various topological options by scaling the space resource and enables exploration on multiple operating conditions that can not be easily reproduced. To demonstrate the effectiveness of StarPerf on understanding and optimizing satellite networks, we leverage StarPerf to evaluate and compare the performance of several state-of-the-art low earth orbit (LEO) constellations and obtain insights on optimizing the architectural design to improve area-to-area network performance. Finally, to further show how applications can benefit from the proposed simulator, we propose an adaptive relay selection algorithm that can intelligently choose the optimal relay on cloud platforms and LEO satellites to achieve reduced latency. Evaluation results show that by properly selecting a relay in the satellite-cloud integrated infrastructure, end-to-end communication latency can be reduced by up to 62% for typical interactive traffic.