{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T17:32:45Z","timestamp":1780421565758,"version":"3.54.1"},"reference-count":33,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T00:00:00Z","timestamp":1745280000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Information and Communication Business Cost Project of JSCMC","award":["SXJD-XXTXF-202303"],"award-info":[{"award-number":["SXJD-XXTXF-202303"]}]},{"name":"Information and Communication Business Cost Project of JSCMC","award":["23-JSLLKY011"],"award-info":[{"award-number":["23-JSLLKY011"]}]},{"name":"Scientific Research Plan of JSLLKYJH","award":["SXJD-XXTXF-202303"],"award-info":[{"award-number":["SXJD-XXTXF-202303"]}]},{"name":"Scientific Research Plan of JSLLKYJH","award":["23-JSLLKY011"],"award-info":[{"award-number":["23-JSLLKY011"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>The rapid development of wireless network technology and the continuous evolution of network service demands have raised higher requirements for congestion control algorithms. In 2016, Google proposed the Bottleneck Bandwidth and Round-trip propagation time (BBR) congestion control algorithm based on the Transmission Control Protocol (TCP) protocol. While BBR offers lower latency and higher throughput compared to traditional congestion control algorithms, it still faces challenges. These include the periodic triggering of the ProbeRTT phase, which impairs data transmission efficiency, data over-injection caused by the congestion window (CWND) value-setting policy, and the difficulty of coordinating resource allocation across multiple concurrent flows. These limitations make BBR less effective in multi-stream competition scenarios in high-speed wireless networks. This paper analyzes the design limitations of the BBR algorithm from a theoretical perspective and proposes the Adaptive-BBR (Ad-BBR) algorithm. The Ad-BBR algorithm incorporates real-time RTT and link queue-state information, introduces a new RTprop determination mechanism, and implements a finer-grained, RTT-based adaptive transmission rate adjustment mechanism to reduce data over-injection and improve RTT fairness. Additionally, the ProbeRTT phase-triggering mechanism is updated to ensure more stable and smoother data transmission. In the NS3, 5G, and Wi-Fi simulation experiments, Ad-BBR outperformed all comparison algorithms by effectively mitigating data over-injection and minimizing unnecessary entries into the ProbeRTT phase. Compared to the BBRv1 algorithm, Ad-BBR achieved a 17% increase in throughput and a 30% improvement in RTT fairness, along with a 13% reduction in the retransmission rate and an approximate 20% decrease in latency.<\/jats:p>","DOI":"10.3390\/fi17050189","type":"journal-article","created":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T20:11:48Z","timestamp":1745352708000},"page":"189","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Ad-BBR: Enhancing Round-Trip Time Fairness and Transmission Stability in TCP-BBR"],"prefix":"10.3390","volume":"17","author":[{"given":"Mingjun","family":"Wang","sequence":"first","affiliation":[{"name":"School of Automation and Information Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"},{"name":"Shaanxi Key Laboratory of Intelligence Coordination Networks, Xi\u2019an 710106, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xuezhi","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Automation and Information Engineering, Xi\u2019an University of Technology, Xi\u2019an 710048, China"},{"name":"Shaanxi Key Laboratory of Intelligence Coordination Networks, Xi\u2019an 710106, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Feng","family":"Jing","sequence":"additional","affiliation":[{"name":"Shaanxi Key Laboratory of Intelligence Coordination Networks, Xi\u2019an 710106, China"},{"name":"Test and Training Base, National University of Defense Technology, Xi\u2019an 710106, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mei","family":"Gao","sequence":"additional","affiliation":[{"name":"Shaanxi Key Laboratory of Intelligence Coordination Networks, Xi\u2019an 710106, China"},{"name":"Test and Training Base, National University of Defense Technology, Xi\u2019an 710106, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,22]]},"reference":[{"key":"ref_1","unstructured":"Yang, Y.R., and Lam, S.S. 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