Transmission Control Protocol (TCP) congestion control plays a vital role in maintaining the quality of Internet communications. However, flows with different Round-Trip Times (RTTs) and Congestion Control Algorithms (CCAs) significantly degrade throughput fairness when sharing a bottleneck link. Especially in environments where CUBIC and BBR coexist, existing controls at intermediate nodes struggle to suppress bandwidth dominance by specific flows. This study proposes a method using the P4 programmable data plane to classify flows into independent queues based on two axes: RTT length and CCA type. Furthermore, applying Fair Queuing with Variable Holding Time (FQ-VHT) to each classified queue ensures equitable bandwidth distribution for each flow, even in environments where diverse communication characteristics coexist.
Due to the rapid growth of smartphones, tablets, and IoT devices, wireless LAN traffic continues to increase, causing severe congestion in high-density environments. Although IEEE 802.11be introduces Multi-Link Operation (MLO) to improve performance by utilizing multiple links, conventional fixed channel selection and traffic allocation schemes cannot adapt to dynamically changing wireless environments. To address this problem, this paper proposes an adaptive channel selection and traffic allocation method based on a distributed spectrum management database that shares real-time channel utilization information among access points. The proposed method dynamically selects channels and allocates traffic for each MLO link according to both channel occupancy and link capacity, enabling efficient utilization of frequency resources. Simulation results using the network simulator ns-3 demonstrate that the proposed method improves total network throughput compared to conventional approaches in high-density environments.
