Q-FCC: Queuing-aware Fair Congestion Control for Integrated Sensing and Communication Networks
Xue Zhang, Yirong Zhuang, Mingyuan Liu, Junfeng Ma, Shaochi Pan, Mingchuan Zhang, Wei Quan · 2024
Integrated Sensing and Communication (ISAC) introduces greater challenges to network transmission in terms of delay, bandwidth, and reliability. Achieving stable and efficient congestion control is a critical issue in emerging ISAC scenarios. However, many traditional congestion control algorithms primarily focus on transmission efficiency but perform poorly in ensuring fairness between different data flows. To address this limitation, this paper proposes a queuing-aware fair congestion control (Q-FCC) solution for ISAC. In particular, Q-FCC incorporates a queue status monitoring module which can provide real-time feedback on the queuing delays at targeted network switches. Additionally, this paper analyzes the traditional BBR algorithm and identifies an inherent flaw: longer RTT flows have a higher bandwidth gain coefficient compared to shorter RTT flows, leading to unfairness. Based on this insight, Q-FCC introduces bandwidth gain factor. Q-FCC uses the queue status monitoring module to categorize data flows into three types and interacts with bursty flow endpoints via ACK packets to assist them in calculating the bandwidth gain factor, which enables the control of the transmission rate. Finally, the algorithm was implemented in the Linux kernel. The results of the semi-physical simulation show that Q-FCC outperforms the traditional BBR and CUBIC algorithms in terms of bandwidth fairness and transmission stability, respectively.