Search Results (4)

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. Full article

The widespread adoption and popularity of various applications have led to large and frequent data transmissions, resulting in network congestion, high packet delays, and packet loss. In 2016, Google proposed the Bottleneck Bandwidth and Round-trip propagation time (BBR) algorithm to mitigate network congestion. However, its network fairness is poor. Consequently, BBRv2 and BBRv3 were introduced in 2018 and 2023 as improved versions. Although BBRv2 exhibited enhanced fairness, its bandwidth utilization rate was lower than that of other existing methods. Meanwhile, BBRv3 still lacked bandwidth fairness in its initial transmission. Therefore, we have improved the fairness based on BBRv3 by considering the maximum sending rate and utilizing connections at different times. Good fairness and bandwidth utilization are maintained on the bottleneck bandwidth with the improved method. The method outperforms Cubic Binary Increase Congestion Control (CUBIC) and BBRv3 in terms of bandwidth utilization and network usage fairness. Full article

Multipath wireless access aims to seamlessly aggregate multiple access networks to increase data rates and decrease latency. It is currently being standardized through the ATSSS architectural framework as part of the fifth-generation (5G) cellular networks. However, facilitating efficient multi-access communication in next-generation wireless networks poses several challenges due to the complex interplay between congestion control (CC) and packet scheduling. Given that enhanced ATSSS steering functions for traffic splitting advocate the utilization of multi-access tunnels using congestion-controlled multipath network protocols between user equipment and a proxy, addressing the issue of nested CC becomes imperative. In this paper, we evaluate the impact of such nested congestion control loops on throughput over multi-access tunnels using the recently introduced Multipath DCCP (MP-DCCP) tunneling framework. We evaluate different combinations of endpoint and tunnel CC algorithms, including BBR, BBRv2, CUBIC, and NewReno. Using the Cheapest Path First scheduler, we quantify and analyze the impact of the following on the performance of tunnel-based multipath: (1) the location of the multi-access proxy relative to the user; (2) the bottleneck buffer size, and (3) the choice of the congestion control algorithms. Furthermore, our findings demonstrate the superior performance of BBRv2 as a tunnel CC algorithm. Full article

The Transmission Control Protocol (TCP) serves as a cornerstone mechanism for implementing Congestion Control (CC) across the Internet. Designing a solution that provides high bandwidth utilization and mitigates the phenomenon of bufferbloat across a spectrum of diverse scenarios poses a considerable challenge. The introduction of Bottleneck Bandwidth and Round Trip propagation time (BBR) in 2016 marked a significant shift in congestion control methodology. Its improved performance and adaptability contributed to the initial acclaim and widespread interest that it received.. Unlike most currently used CCs, it operates around Kleinrock’s optimal point, thus offering high throughput even in lossy networks while preventing buffer saturation. Unfortunately, it quickly became evident that BBR was unable to fairly share bandwidth with flows characterized by different path delays, as well as loss-based CCs. In response, Google recently introduced a third iteration to address these shortcomings. This study explores the performance of BBRv3 across a wide range of scenarios, thereby considering different buffer sizes and paths with varying Round Trip Times (RTTs), and it evaluates its superiority over its predecessors. Through extensive simulations, this work assesses whether BBRv3 can finally play fair with other bandwidth contenders, which is a critical consideration given the widespread deployment of BBR. The framework is publicly available to facilitate additional validation and ensure the reproducibility of the study’s findings. The results indicate that while BBRv3 demonstrates enhanced fairness towards loss-based CC algorithms, it struggles when competing against other BBR flows, especially in multi-RTT networks, thus falling short even when compared to the initial version. Full article