Abstract

Abstract: Wireless networks are becoming ever more sophisticated and overcrowded, imposing the most delay, jitter, and throughput damage to end-to-end network flows in today’s internet. We therefore, argue for fine-grained mobile endpoint-based wireless measurements to inform a precise congestion control algorithm through a well-defined API to the mobile’s wireless physical layer. Our proposed congestion control algorithm is based on physical-layer bandwidth measurements taken at the endpoint, and captures the latest 5G New Radio innovations that increase wireless capacity, yet create abrupt rises and falls in available wireless capacity that the sender can react to precisely and very rapidly. We implement a proof-of-concept prototype of the measurement module on software-defined radios and the sender and receiver in C. An extensive performance evaluation compares our system head to head against the leading wireless-aware and wireless-oblivious congestion control protocols proposed in the research community and in deployment, in mobile and static mobile scenarios, and over busy and quiet networks. Results show 6.3% higher average throughput than BBR , while simultaneously reducing the 95th percentile delay by a factor of 1.8×.

Bio: Kyle Jamieson is an Associate Professor in the Department of Computer Science at Princeton University and Honorary Reader at University College London. His research focuses on building mobile and wireless systems for sensing, localization, and communication that cut across the boundaries of digital communications and networking. He received the B.S. (Mathematics, Computer Science), M.Eng. (Computer Science and Engineering), and Ph.D. (Computer Science, 2008) degrees in Computer Science from the Massachusetts Institute of Technology. He then received a Starting Investigator fellowship from the European Research Council, a Google Faculty Research Award, and the ACM SIGMOBILE Early Career Award.

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