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With the aim of improved throughput with reduced delay, Google proposed the bottleneck bandwidth and round-trip time (BBR) congestion control algorithm in 2016. Contrasting with the traditional loss-based congestion control algorithms, it operates without bottleneck queue formation and packet losses. However, we find unexpected behaviour in BBR during testbed experiments and network simulator 3 (NS-3) simulations. We observe huge packet losses, retransmissions, and large queue formation in the bottleneck in a congested network scenario. We believe this is because of BBR’s nature of sending extra data during the bandwidth probing without considering the network conditions, and the lack of a proper recovery mechanism. In a congested network, the sent extra data creates a large queue in the bottleneck, which is sustained due to insufficient drain time. BBR lacks a proper mechanism to detect such large bottleneck queues, cannot comply with the critical congestion situation properly, and results in excessive retransmission problems. Based on these observations, we propose a derivative of BBR, called “BBR with advanced congestion detection (BBR-ACD)”, that reduces the excessive retransmissions without losing the merits. We propose a novel method to determine an actual congestion situation by considering the packet loss and delay-gradient of round-trip time, and implement a proper recovery mechanism to handle such a congestion situation. Through extensive test and NS-3 simulations, we confirmed that the proposed BBR-ACD could reduce the retransmissions by about 50% while improving the total goodput of the network.

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In late 2016, Google proposed the Bottleneck Bandwidth and Round-trip propagation time (BBR) congestion control algorithm to achieve high bandwidth and low latency for Internet traffic. Unlike loss-based congestion control algorithms, BBR works without filling the bottleneck buffer. Consequently, BBR can reduce packet loss and minimize end-to-end packet delay, which has attracted the attention of many researchers in recent years. However, some studies have reported the creation of persistent queues that cause unintended problems, resulting in a serious fairness issue between TCP BBR flows with different round-trip times (RTTs). Although existing congestion control algorithms also exhibit fairness issue between different RTT flows, BBR has a more serious problem in that the imbalance is considerable even with small RTT difference between the two flows, and the long RTT flow uses most of the bandwidth. The preponderance of long RTT flows is a serious problem because a particular user may cause imbalance by maliciously increasing the delay. Therefore, we propose a Delay-Aware BBR (DA-BBR) congestion control algorithm to mitigate the RTT fairness issue between BBR flows. In a network emulation experiment using the Mininet, the DA-BBR increased the fairness index by 1.6 times that of the original BBR, and the retransmission was greatly reduced. DA-BBR flow with short RTT demonstrated fair throughput even in competition with DA-BBR flows where RTT is five times higher.INDEX TERMS BBR, congestion control, fairness, round-trip time, TCP.

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TCP congestion control adjusts the sending rate in order to protect Internet from the continuous traffic and ensure fair coexistence among multiple flows. Especially, loss-based congestion control algorithms were mainly used, which worked relatively well for past Internet with low bandwidth and small bottleneck buffer size. However, the modern Internet uses considerably more sophisticated network equipment and advanced transmission technologies, and loss-based congestion control can cause performance degradation due to excessive queueing delay and packet loss. Therefore, Google introduced a new congestion control in 2016, Bottleneck Bandwidth Round-trip propagation time (BBR). In contrast with traditional congestion control, BBR tries to operate at the Kleinrock’s optimal operating point, where delivery rate is maximized and latency is minimized. However, when BBR and loss-based congestion control algorithms coexist on the same bottleneck link, most of bottleneck bandwidth is occupied by flows that use a particular algorithm, and excessive packet retransmission can occur. Therefore, this paper proposes a BBR congestion window scaling (BBR-CWS) scheme to improve BBR’s inter-protocol fairness with a loss-based congestion control algorithm. Through Mininet experiment results, we confirmed that fairness between BBR-CWS and CUBIC improved up to 73% and has the value of 0.9 or higher in most bottleneck buffer environments. Moreover, the number of packet retransmissions was reduced by up to 96%, compared to the original BBR.

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