7 papers
Lodestar: An Online-Learning LLM Inference Router
Gangmuk Lim, Wanyu Zhao, Brighten Godfrey +3
Efficiently serving large language model (LLM) inference tasks is crucial both for user-perceived latency such as time-to-first-token (TTFT) and for GPU utilization. However, LLM r…
CCLab: Adversarial Testing of Learning- and Non-Learning-Based Congestion Controllers
Zhi Chen, Shehab Sarar Ahmed, Chenkai Wang +2
Congestion controllers (CCs) are critical to network performance, and yet their robustness under adverse conditions remains insufficiently understood. While recent learning-based C…
AdvNet: Revealing Performance Issues in Network Protocols by Generating Adversarial Environments
Shehab Sarar Ahmed, William Sentosa, Yinjie Zhang +6
Infrastructure protocols like Congestion Control (CC) seek to provide reliable performance across a wide range of Internet environments. Currently, protocol designers assess perfor…
GATE: GPU-Accelerated Traffic Engineering for the WAN
Rahul Bothra, Alexander Krentsel, Saptarshi Mandal +4
Traffic engineering (TE) has become a crucial tool for enforcing routing policy and maintaining operational efficiency in large networks. Existing TE solutions pick an objective fu…
Assistants, Not Architects: The Role of LLMs in Networked Systems Design
Pratyush Sahu, Rahul Bothra, Venkat Arun +3
Designing the architecture of modern networked systems requires navigating a large, combinatorial space of hardware, systems, and configuration choices with complex cross-layer int…
SafeTree: Expressive Tree Policies for Microservices
Karuna Grewal, P. Brighten Godfrey, Justin Hsu
A microservice-based application is composed of multiple self-contained components called microservices, and controlling inter-service communication is important for enforcing safe…