César: Cellular Resource Scheduling-Aware Congestion Control
Juhun Shin, Goodsol Lee, Jeongyeup Paek, Saewoong Bahk
Abstract
Delay-based congestion control algorithms (CCAs) have been proposed to tackle the bufferbloat problem of traditional loss-based CCAs. However, existing delay-based CCAs either fail to adequately consider the non-congestive delay caused by scheduling characteristics of modern cellular networks leading to improper congestion control, or face practical deployment issues, which results in an inability to fully utilize the high bandwidth and low latency that recent cellular systems provide. To resolve this problem, we propose César, a cellular resource scheduling-aware congestion control with only sender-side modification. César estimates scheduling unit through TCP ACK interval patterns to deduce the scheduling characteristics of the current cellular link, and adjusts the congestion window size based on scheduling unit in a step-wise manner to minimize the impact of the scheduling delay on congestion control. Experimental results on 5G and LTE cellular networks of three different mobile carriers show that César outperforms other state-of-the-art CCAs. Results show that throughput-over-latency performance improves by up to 2.89×, 10.09×, 1.39×, and 5.65× compared to ExLL, PropRate, BBR, and Cubic, respectively.
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