Stable And Fair Quantized Notification For 5g Mobile Network

With the coming fifth generation (5G) network, effective congestion control mechanism is needed for increasing requirements of high quality of service (QoS). Quantized Congestion Notification (QCN) is a standard layer 2 congestion control mechanism providing low latency and preventing packet loss. However, it cannot provide fairness when several flows share one bottle link. Meanwhile, QCN performs poorly in rate convergence and queue occupancy stability under bursty traffic which is normal in 5G scenario. In this paper, we address these issues and propose an enhanced QCN congestion notification algorithm called stable and fair QCN (SFQCN). SFQCN senses congestion through joint queue occupancy and incoming traffic estimation, then feedbacks individual congestion notification message with information of expected share rate to each flow. We evaluate the performance of SFQCN in terms of rate convergence and queue occupancy under typical 5G traffic using NS3 simulator. The results of simulation validate that SFQCN achieves fast and fair rate allocation while ensuring a low and stable queue occupancy at congestion point.