Adaptive congestion control in IoT networks: Leveraging one-way delay for enhanced performance.

With the exploding number of IoT devices generating vast data volumes, there is a growing risk of significant performance degradation without efficient congestion management. To tackle this challenge, efficient regulation and supervision are essential for managing congestion in IoT networks. This research work introduces a One-Way-Delay (OWD)-based congestion control (CC) method that estimates data transmission delays of the communication path and adjusts network traffic accordingly. The proposed method enhances IoT device performance by continuously monitoring OWD along the transmission path to identify and mitigate congestion. Comparative analysis with existing methods demonstrates that the proposed approach more effectively utilizes network resources, reduces congestion, and improves throughput while ensuring fairness and reliability within the IoT infrastructure. The experimental simulations show that the proposed OWD-based method outperforms well-established TCP variants such as BBR, TCP Cubic, HTCP, and New Reno, achieving average throughput improvements ranging from 4.1 % to 22.7 %. The proposed method also maintains fairness in mixed-traffic environments and effectively manages congestion in complex network topologies.