Low Earth Orbit (LEO) satellite links are pivotal for ubiquitous vehicle connectivity, yet their performance is impacted by a complex interplay of weather, constellation dynamics, and physical obstructions. While individual models for these impairments exist, protocol and application designers lack a unified tool to evaluate behavior under realistic, composed LEO conditions. We present COSME, a route-aware, real-time mobility emulator that integrates multiple impairment models - including obstruction-based loss, constellation-induced jitter, precipitation-driven bandwidth reduction, and packet loss at handovers - into a single framework. By orchestrating Linux network namespaces via tc and netem, COSME enables the high-fidelity playback of merged impairment traces. We demonstrate COSME through five diverse application showcases, highlighting the impact of different congestion control algorithms and transport protocols on LEO connectivity.

Lately, growing effort has been invested to analyze the Starlink performance under vehicular user terminal mobility. As such measurement campaigns are labor- and time-consuming, existing studies mostly focus on single test drives. In this paper, we demonstrate that repeatability and replicability of mobile Starlink measurements represent serious challenges, mainly due to numerous factors that can be hardly controlled. First, we conduct an extensive measurement campaign of Starlink's latency and packet loss under vehicular mobility. The campaign focuses on repeatability and consists of 35 single test drives of the identical highway route over the span of four months. Then, we demonstrate that replicability remains challenging. For this, we replicate existing findings and find new, seemingly statistically significant correlations by purposefully cherry-picking single test drives. By considering our complete dataset, we show that in reality, these findings are likely statistical variations caused by uncontrollable factors. Based on this, we discuss the challenges and provide guidelines for meaningful future Starlink measurements under vehicular mobility.

Low Earth Orbit (LEO) satellite networks such as Starlink allow global and affordable internet access. This not only connects remote residents, but also enables new potentials such as connecting non-stationary agricultural systems in rural areas for high-precision spot farming. One challenge is that tractors and farming robots need to transmit large amounts of data from cameras and laser scanners in real-time, which easily overwhelms the uplink capabilities of a single LEO connection. In this paper, we examine the Starlink performance of multiple terminals within a single service cell to lay ground for multipath link bundling as a possible approach to increase link capabilities. For this purpose, we present two measurement setups consisting of four and seven Starlink dishes placed in one service cell. We conduct multiple measurements and evaluate UDP and TCP throughput, latency, and packet loss. We find that UDP throughput scales almost linearly with the number of dishes, indicating significant bundling potential up to an expected limit. In contrast, TCP BBRv1’s bundling potential is limited, due to inefficiencies in utilizing the links. Moreover, we find that some packet loss events are synchronized within a service cell. For future and independent research, we make our dataset publicly available.

The automation of the agricultural sector is continuously evolving. Especially communication plays a key role for the future agriculture 4.0 transformation. The coordination of agricultural machinery and the increasing usage of robots demands reliable communication. However, in rural areas a sufficient coverage by mobile networks is often not guaranteed. This paper addresses this issue by development of a portable standalone 5G nomadic network with satellite connectivity, which is optimized for agricultural use cases. The approach includes the use of Real Time Kinematic (RTK) for exact positioning, internet backhauling, and a concept for automatic frequency allocation. The proposed nomadic network architecture has been built and tested in a real-world scenario on an agricultural yard in Germany. It was shown that such a network can empower the agricultural transformation in different ways.

Low Earth Orbit (LEO) satellite networks like Starlink are susceptible to both external factors (e.g., weather and obstruction) and internal factors such as frequency and resource allocation changes. This causes performance instabilities by design. In this demo, we show that such instabilities can have a detrimental impact on the performance of TCP and consequently on large parts of today’s internet, as most traffic uses TCP as transport protocol. Consequently, LEO-specific adaptations to either TCP and/or higher-level applications are necessary.

This demo presents link ’em version 2, an open source modification of the Linux Network Emulator (netem), to enable trace-based loss and delay emulation of pre-recorded real-world network conditions. It is used in an experimental setup to demonstrate and evaluate the impact of Network Coding-based Forward Erasure Correction for TCP (TCPyNC) on the performance of Dynamic Adaptive Streaming over HTTP (DASH). Thus, the proposed demonstration showcases the novel features of link ’em v2 and highlights the capability of network coding-based FEC to improve the overall video quality and reduce stalling of DASH video streams.

In many robotic applications as well as in the area of immersive multimedia, large point clouds need to be transmitted over a network preferably in real-time. Typically, the point cloud is first compressed to a significantly smaller size, before it is transmitted as a simple file transfer. A drawback of this method is that it requires a point cloud to be fully available for the compression process to begin, inducing additional delay. In this paper, we explore the potential of streaming incoming points directly from an ongoing laser scan. Therefore, we propose a compression algorithm that operates on an ongoing point stream. Furthermore, we propose and compare different rate adaptation methods that dynamically adapt the compression rate to the currently available network data rate. Our evaluations show promising results in terms of rate fluctuations around the available network data rate and the achieved quality of our solution.