{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/optimizing-congestion-control-through-fair","title":"Detecting Fair Queuing for Better Congestion Control","arxiv_id":"2010.08362","date":"2020-10-16","proceeding":null,"authors":["Maximilian Bachl","Joachim Fabini","Tanja Zseby"],"abstract":"Low delay is an explicit requirement for applications such as cloud gaming and video conferencing. Delay-based congestion control can achieve the same throughput but significantly smaller delay than loss-based one and is thus ideal for these applications. However, when a delay- and a loss-based flow compete for a bottleneck, the loss-based one can monopolize all the bandwidth and starve the delay-based one. Fair queuing at the bottleneck link solves this problem by assigning an equal share of the available bandwidth to each flow. However, so far no end host based algorithm to detect fair queuing exists. Our contribution is the development of an algorithm that detects fair queuing at flow startup and chooses delay-based congestion control if there is fair queuing. Otherwise, loss-based congestion control can be used as a backup option. Results show that our algorithm reliably detects fair queuing and can achieve low delay and high throughput in case fair queuing is detected.","url_abs":"https://arxiv.org/abs/2010.08362v3","url_pdf":"https://arxiv.org/pdf/2010.08362v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"optimizing-congestion-control-through-fair","repo_url":"https://github.com/CN-TU/PCC-Uspace","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}