Low Earth Orbit (LEO) satellite ISPs promise universal Internet connectivity, yet their interaction with content delivery remains poorly understood. We present the first comprehensive measurement study decomposing Starlink's web content delivery performance decomposed across Point of Presence (PoP), DNS, and CDN layers. Through two years of measurements combining 225K Cloudflare AIM tests, M-Lab data, and active probing from 99 RIPE Atlas and controlled Starlink probes, we collect 6.1M traceroutes and 10.8M DNS queries to quantify how satellite architecture disrupts terrestrial CDN assumptions. We identify three distinct performance regimes based on infrastructure density. Regions with local content-rich PoPs achieve near-terrestrial latencies with the satellite segment dominating 80-90% of RTT. Infrastructure-sparse regions suffer cascading penalties: remote PoPs force distant resolver selection, which triggers CDN mis-localization, pushing latencies beyond 200 ms. Dense-infrastructure regions show minimal sensitivity to PoP changes. Leveraging Starlink's infrastructure expansion in early 2025 as a natural experiment, we demonstrate that relocating PoPs closer to user location reduces median page-fetch times by 60%. Our findings reveal that infrastructure proximity, not satellite coverage, influences web performance, requiring fundamental changes to CDN mapping and DNS resolution for satellite ISPs.

Content Delivery Networks (CDNs) have been pivotal in the dramatic evolution of the Internet, handling the majority of data traffic for billions of connected users. Low-Earth-Orbit (LEO) satellite networks, such as Starlink, aim to revolutionize global connectivity by providing high-speed, low-latency Internet to remote regions. However, LEO satellite networks (LSNs) face challenges integrating with traditional CDNs, which rely on geographical proximity for efficient content delivery - a method that clashes with the operational dynamics of LSNs. In this paper, we scrutinize the operation of CDNs in the context of LSNs, using Starlink as a case study. We develop a browser extension NetMet that performs extensive web browsing experiments from controlled nodes using both Starlink and terrestrial Internet access. Additionally, we analyse crowdsourced speed tests from Starlink users to Cloudflare CDN servers globally. Our results indicate significant performance issues for Starlink users, stemming from the misalignment between terrestrial and satellite infrastructures. We then investigate the potential for SpaceCDNs which integrate CDN infrastructure directly within the LSNs, and show that this approach offers a promising alternative that decreases latencies by over 50%, making them comparable with the CDN experience of users behind terrestrial ISPs. Our aim is to stimulate further research and discussion on overcoming the challenges of effective content delivery with growing LSN offerings.

Low-Earth-Orbit satellite networks (LSNs) are enabling low-latency high-bandwidth internet connectivity at a global scale. However, majority of the traffic on the Internet is currently handled by Content Delivery Networks (CDNs), which rely on geographical proximity to deliver content. In this work, we examine CDN performance for the commercial largest LSN, i.e. Starlink, by performing active measurements through our web browser plugin and passive analysis of Cloudflare speed tests globally. Comparing this to terrestrial networks, we highlight significant performance degradation for Starlink users due to the asymmetries between satellite and terrestrial infrastructure.

The emerging nature of low-earth-orbiting satellite constellations has brought forth an era of global connectivity. Star-link has the potential to offer a truly global, high-performant service. An obvious question arising from this is whether Starlink can replace existing terrestrial services. In this work we describe the key findings from a detailed study of the performance of Starlink, investigating both its potential and shortcomings to act as a "global ISP".

The Starlink network from SpaceX stands out as the only commercial LEO network with over 2M+ customers and more than 4000 operational satellites. In this paper, we conduct a first-of-its-kind extensive multi-faceted analysis of Starlink performance leveraging several measurement sources. First, based on 19.2M crowdsourced M-Lab speed tests from 34 countries since 2021, we analyze Starlink global performance relative to terrestrial cellular networks. Second, we examine Starlink's ability to support real-time latency and bandwidth-critical applications by analyzing the performance of (i) Zoom conferencing, and (ii) Luna cloud gaming, comparing it to 5G and fiber. Third, we perform measurements from Starlink-enabled RIPE Atlas probes to shed light on the last-mile access and other factors affecting its performance.Finally, we conduct controlled experiments from Starlink dishes in two countries and analyze the impact of globally synchronized "15-second reconfiguration intervals'' of the satellite links that cause substantial latency and throughput variations. Our unique analysis paints the most comprehensive picture of Starlink's global and last-mile performance to date.

Excessive network packet loss is one of the strongest symptoms of the presence of some hardware or software-related infrastructure anomaly. As such, multiple techniques to rapidly and efficiently measure packet loss in physical network equipment have been developed throughout the years. Yet, most of the proposed techniques fall short in the case of cloud scenarios which combine the presence of physical and virtual network devices. In this paper, we tackle the problem of providing lightweight and fine-grained packet loss monitoring at virtual switches. We achieve our goal by combining packet coloring, with efficient packet loss signal extraction and aggregation entirely within the virtual switch level. To understand its feasibility in a production environment, the proposed system has been implemented and evaluated in a synthetic scenario and for real-world use cases. Our implementation on top of OvS-DPDK shows that the proposed system achieves 95% accurate packet loss measurement while introducing negligible switching throughput degradation.

The growing demand for higher compute and memory capacity driven by artificial intelligence (AI) applications pushes higher core counts in modern systems. Many-core architectures exhibiting spatial interconnects with high on-chip bandwidth are ideal for these workloads due to their data movement flexibility and sheer parallelism. However, the size of such platforms makes them particularly susceptible to manufacturing defects, prompting a need for designs and mechanisms that improve yield. Despite these techniques, nonfunctional cores and links are unavoidable. Although prior works address defective cores by disabling them and only scheduling workload to functional ones, communication latency through spatial interconnects is tightly associated with the locations of defective cores and cores with assigned work. Based on this observation, we present Si-Kintsugi, a defect-aware workload scheduling framework for spatial architectures with mesh topology. First, we design a novel and generalizable workload mapping representation and cost function that integrates defect pattern information. The mapping representation is formed into a 1D vector with simple constraints, making it an ideal candidate for open source heuristic-based optimization algorithms. After a communication latency optimized workload mapping is found, dataflow between the mapped cores is automatically generated to balance communication and computation cost. Si-Kintsugi is extensively evaluated on various workloads (i.e., BERT, ResNet, GEMM) across a wide range of defect patterns and rates. Experiment results show that Si-Kintsugi generates a workload schedule that is on average 1.34 × faster than the industry standard layer-pipelined schedule on defective platforms.