This January 2022 issue contains three technical papers and four editorial notes.
The first technical paper, Zeph & Iris Map the Internet – A resilient reinforcement learning approach to distributed IP route tracing, by Matthieu Gouel and colleagues, proposes to improve topology discovery by optimizing the use of existing probing resources. This can be done by intelligently allocating probing directives to vantage points. The system is based on the inter-working of two components: Iris, which takes care of the route tracing, and Zeph, which coordinates Iris’s measurements. The results in the paper show that Zeph, in combination with Iris, are able to facilitate fast topology measurements from geographically distributed vantage points.
The second technical paper, Towards Retina-Quality VR Video Streaming: 15ms Could Save You 80\% of Your Bandwidth, by Luke Hsiao and colleagues, investigates how to provide retina-quality video streaming in virtual reality (VR). The paper studies the impact of the motion-to-photon latency — the time between a change in the viewer’s gaze and the resulting change in the display’s pixels — on a VR system. This metric is paramount for VR systems since it impacts video compression. The paper shows, experimentally, that a client and streaming server system with sub-15 ms end-to-end motion-to-photon latency benefit from 5x better video compression than in presence of larger latencies. The paper also shows how to build such a low latency system both hardware and software-wise.
The third technical paper, Towards client-side active measurements without application control, by Palak Goenka and colleagues, proposes to harness Network Error Logging (NEL) to enable active client-side measurements (RTT and connection availability) by dynamically modifying the HTTPS endpoint where NEL reports should be uploaded. Network Error Logging (NEL) is a W3C standard which defines how web servers can receive from a browser reports about performance and failures of web requests. The techniques used in the paper enable active client-side measurements in the browser without requiring Javascript code injection, which is the current and more invasive state of the art solution.
Finally, we have four editorial notes. Roadmap for Edge AI: A Dagstuhl Perspective, by Aaron Yi Ding and his colleagues, based on the collective input of Dagstuhl Seminar (21342), presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI. Then, M-Lab: User initiated Internet data for the research community, by Phillipa Gill and her colleagues, presents Measurement Lab (M-Lab), an open, distributed server platform on which researchers have deployed measurement tools. Important Concepts in Data Communications, by Craig Partridge, presents one perspective about which concepts or ideas in data communications have proven to be enduring in the evolution of data communications. Finally, Answering Three Questions About Networking Research, by Jennifer Rexford and Scott Shenker, presents the first of a series of answers to three questions that were asked to panelists during HotNets’21, about how they pick their own research topics, what areas they would like to see more research on, and how they evaluate conference papers.
I hope that you will enjoy reading this new issue and welcome comments and suggestions on CCR Online (https://ccronline.sigcomm.org) or by email at ccr-editor at sigcomm.org.