{"title":"Exploring the BBRv2 Congestion Control Algorithm for use on Data Transfer Nodes","authors":"Brendan Tierney, E. Dart, E. Kissel","doi":"10.1109/indis54524.2021.00008","DOIUrl":null,"url":null,"abstract":"It is well known that loss-based TCP congestion control algorithms are problematic for high-speed high-latency flows that are common in Big Science. In 2016 Google released a new congestion control algorithm called ‘BBR’ (Bottleneck Bandwidth and Round-trip time) that uses a model-based approach, and the design has since been refined in an alpha release of BBRv2. In this paper, we describe and perform a set of experiments that assess the suitability of BBRv2 for use on Data Transfer Nodes (DTNs). The experiments were run on both production R&E networks as well as within a controlled testbed environment. Our analysis of the results show that BBRv2 improves upon BBRvl for common Big Science transfer scenarios and is a promising option in high-speed short-queue networking environments.","PeriodicalId":351712,"journal":{"name":"2021 IEEE Workshop on Innovating the Network for Data-Intensive Science (INDIS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Workshop on Innovating the Network for Data-Intensive Science (INDIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/indis54524.2021.00008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
It is well known that loss-based TCP congestion control algorithms are problematic for high-speed high-latency flows that are common in Big Science. In 2016 Google released a new congestion control algorithm called ‘BBR’ (Bottleneck Bandwidth and Round-trip time) that uses a model-based approach, and the design has since been refined in an alpha release of BBRv2. In this paper, we describe and perform a set of experiments that assess the suitability of BBRv2 for use on Data Transfer Nodes (DTNs). The experiments were run on both production R&E networks as well as within a controlled testbed environment. Our analysis of the results show that BBRv2 improves upon BBRvl for common Big Science transfer scenarios and is a promising option in high-speed short-queue networking environments.