Networking
Explore data center networking, BGP, SDN, and modern network technologies
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Fri, Sep 18
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PyStream: Enhancing Video Streaming Evaluation
As streaming services become more commonplace, analyzing their behavior effectively under different network conditions is crucial. This is normally quite expensive, requiring multiple players with different bandwidth configurations to be emulated by a powerful local machine or a cloud environment. Furthermore, emulating a realistic network behavior or guaranteeing adherence to a real network trace is challenging. This paper presents PyStream, a simple yet powerful way to emulate a video streaming network, allowing multiple simultaneous tests to run locally. By leveraging a network of Docker containers, many of the implementation challenges are abstracted away, keeping the resulting system easily manageable and upgradeable. We demonstrate how PyStream not only reduces the requirements for testing a video streaming system but also improves the accuracy of the emulations with respect to the current state-of-the-art. On average, PyStream reduces the error between the original network trace and the bandwidth emulated by video players by a factor of 2-3 compared to Wondershaper, a common network traffic shaper in many video streaming evaluation environments. Moreover, PyStream decreases the cost of running experiments compared to existing cloud-based video streaming evaluation environments such as CAdViSE.
The Life of a Token: from Words to Bits on the Wire
Large Language Models (LLMs) transform vast collections of unstructured text into semantic patterns used for language generation and reasoning tasks. Behind their ease of use lies a complex process: words become tokens, tokens become vectors, and vectors ultimately give rise to streams of bits that flow through High-Performance Computing (HPC) systems. As modern LLMs grow to billions or trillions of parameters, this path increasingly unfolds across thousands of interconnected accelerators, making the underlying communication fabric a critical and often opaque component of model training. This tutorial aims to walk the reader through the journey from words to network traffic, shedding light on how language is translated into communication flows within HPC training systems. Using concrete examples from Dante's Divine Comedy, we illustrate how model architecture, tokenization, embeddings, and parallelization strategies shape the volume, structure, and timing of data exchanged across the network. We combine architectural analysis with analytical traffic models and numerical examples to characterize the communication requirements of LLM training. We try to demystify how words travel across the network and provide practical insights into the network requirements needed to support the journey from text to trained model.
RUN-O-RAN: An O-RAN-Native Architecture Enabling Cooperative Uplink Localization
Accurate positioning is increasingly required in indoor and dense urban environments; nonetheless, satellite-based systems are not always available, and standardized 5G localization solutions remain difficult to deploy with commercial devices. This paper presents RUN-O-RAN, an O-RAN-native framework that enables network-centric uplink localization using standard Sounding Reference Signal (SRS) transmissions from commercial 5G devices. RUN-O-RAN xApp coordinates serving and neighboring base stations, enabling non-serving base stations to retrieve SRS-based uplink timing measurements that would be unavailable in conventional RAN deployments, without modifying the UE or existing 3GPP signaling procedures. The framework combines cooperative SRS collection, first-path time-of-arrival estimation, timing-advance tracking, clock-drift compensation, and multi-anchor position estimation into a complete network-side localization service. Experimental evaluation over $150,000$ SRS transmissions validates the proposed framework, achieving meter-level localization under diverse propagation conditions while revealing the impact of anchor geometry and multipath on positioning accuracy. These findings demonstrate that cooperative SRS-based localization can be realized within the O-RAN ecosystem without modifying commercial UEs, providing a practical foundation for future network-native ISAC positioning services.
N4N064: A Gentle Introduction to Border Gateway Protocol (BGP)
Border Gateway Protocol (BGP), the routing protocol of the global internet, is finding uses in all sorts of places in 2026 beyond internet routing. It’s a huge topic. Large books have been written about BGP and its related technologies, so Ethan and Holly are here with a gentle introduction to BGP. They break down what... Read more »