BBR拥塞控制算法延迟及带宽探测优化

传统基于丢包的拥塞控制算法因为其高丢包率和引发缓冲区膨胀问题已经不能满足许多应用对网络性能的要求。谷歌提出的BBR（Bottleneck Bandwidth and Round Trip）算法以其抗丢包、高带宽利用率和低延迟等特性受到广泛关注与研究。但是BBR还存在排队延迟仍然较高、在RTT（Round Trip Time）较小环境下表现不佳、带宽探测不及时等问题。本文对BBR排队延迟和收敛性进行分析，进而提出改进方法：限制在外数据包数，并根据网络反馈适时减少拥塞窗口大小来降低延迟；在RTT较小环境下，将探测RTT阶段之前的带宽估计延续到探测RTT阶段之后；设置平稳状态最长保持时间及时退出平稳周期并进入探测周期。在NS3中的仿真实验结果表明，改进BBR降低了RTT及其抖动，提高了算法的收敛速度；能够在RTT较小环境下高效利用带宽；改进BBR能够显著提高长RTT流的带宽探测频率。

Improving Latency and Bandwidth Probe of BBR Congestion Control Algorithm

The traditional congestion control algorithm based on packet loss can’t meet the requirements of many applications for network performance because of its high packet loss rate and buffer expansion. The BBR (bottleneck bandwidth and round trip) algorithm proposed by Google has attracted extensive attention and research because of its characteristics of anti packet loss, high bandwidth utilization and low delay. However, BBR still has some problems, such as high queuing delay, poor performance in a small RTT (round trip time) environment, untimely bandwidth detection, etc. This paper analyzes the queuing delay and convergence of BBR, and then puts forward an improved method: Limit inflight data, and reduce the congestion window size timely according to the network feedback to reduce the delay; In small RTT environment, the bandwidth estimation before the probe RTT stage is retained to after probe RTT; Set the maximum holding time of steady state, exit the steady cycle in time and enter the detection cycle. The simulation results in NS3 show that the improved BBR reduces the RTT and its jitter, and improves the convergence speed of the algorithm; The bandwidth can be efficiently used in the environment with small RTT; The improved BBR can significantly improve the bandwidth probe frequency of long RTT streams.