Performance Enhancement Proxies (PEPs) are widely used to improve TCP performance in geostationary orbit (GEO) satellite networks, which experience long RTT (approximately 500 ms). As a split TCP-based solution, PEP divides the end-to-end connection into multiple sub-connections, each independently managing its own rate control, including both congestion and flow control. This independence naturally leads to rate imbalances, manifested as an abnormal on-off traffic pattern-a phenomenon confirmed by our experimental observations in real-world GEO satellite networks. Furthermore, we demonstrate that this on-off traffic pattern not only undermines fairness but also reduces throughput, particularly for small-sized flows. To address this problem, we propose PEP-Policer, an automatic rate limiter for PEP to limit the link with higher rate to the lower one. Unlike traditional rate limiting methods that require manual configuration of the target rate, PEP-Policer employs a finite state machine to automatically determine and enforce the appropriate target rate. Moreover, as an add-on, PEP-Policer is compatible with all PEP-based solutions and can be integrated without modifying existing systems. Extensive evaluations in an emulated GEO satellite network show that PEP-Policer improves TCP's fairness and increases goodput by up to 63.0% for Cubic, 49.6% for BBR, and 88.6% for Hybla.

The Satellite-Terrestrial Integrated Network (STIN) enhances end-to-end transmission by simultaneously utilizing terrestrial and satellite networks, offering significant benefits in scenarios like emergency response and cross-continental communication. Low Earth Orbit (LEO) satellite networks offer reduced Round Trip Time (RTT) for long-distance data transmission and serve as a crucial backup during terrestrial network failures. Meanwhile, terrestrial networks are characterized by ample bandwidth resources and generally more stable link conditions. Therefore, integrating Multipath TCP (MPTCP) into STIN is vital for optimizing resource utilization and ensuring efficient data transfer by exploiting the complementary strengths of both networks. However, the inherent challenges of STIN, such as heterogeneity, instability, and handovers, pose difficulties for traditional multipath schedulers, which are typically designed for terrestrial networks. We propose a novel multipath data scheduling approach for STIN, the Adaptive Latency Compensation Scheduler (ALCS), to address these issues. ALCS refines transmission latency estimates by incorporating RTT, congestion window size, inflight and queuing packets, and satellite trajectory information. It further employs adaptive mechanisms for latency compensation and proactive handover management. Implemented in the MPTCP Linux Kernel and evaluated in a simulated STIN testbed, ALCS outperforms existing multipath schedulers, delivering faster data transmission and achieving throughput gains of 9.8% to 44.0% compared to benchmark algorithms.