TY - GEN
T1 - RAN-Aware Delay Compensation for Delay-Sensitive Protocols in Cellular Networks
AU - Liu, Yuxin
AU - Zhang, Tianyang
AU - Wu, Qiang
AU - Ren, Ju
AU - Jamieson, Kyle
AU - Xie, Yaxiong
N1 - Publisher Copyright:
© 2026 Copyright held by the owner/author(s).
PY - 2026/5/10
Y1 - 2026/5/10
N2 - Delay-based protocols rely on end-to-end delay measurements to detect network congestion. However, in cellular networks, Radio Access Network (RAN) buffers introduce significant delays unrelated to congestion, fundamentally challenging these protocols' assumptions. We identify two major types of RAN buffers - retransmission buffers and uplink scheduling buffers - that can introduce delays comparable to congestion-induced delays, severely degrading protocol performance. We present CellNinjia, a software-based system providing real-time visibility into RAN operations, and Gandalf, which leverages this visibility to systematically handle RAN-induced delays. Unlike existing approaches that treat these delays as random noise, Gandalf identifies specific RAN operations and compensates for their effects. Our evaluation in commercial 4G LTE and 5G networks shows that Gandalf enables substantial performance improvements - up to 7.49 × for Copa and 9.53 × for PCC Vivace - without modifying the protocols' core algorithms, demonstrating that delay-based protocols can realize their full potential in cellular networks.
AB - Delay-based protocols rely on end-to-end delay measurements to detect network congestion. However, in cellular networks, Radio Access Network (RAN) buffers introduce significant delays unrelated to congestion, fundamentally challenging these protocols' assumptions. We identify two major types of RAN buffers - retransmission buffers and uplink scheduling buffers - that can introduce delays comparable to congestion-induced delays, severely degrading protocol performance. We present CellNinjia, a software-based system providing real-time visibility into RAN operations, and Gandalf, which leverages this visibility to systematically handle RAN-induced delays. Unlike existing approaches that treat these delays as random noise, Gandalf identifies specific RAN operations and compensates for their effects. Our evaluation in commercial 4G LTE and 5G networks shows that Gandalf enables substantial performance improvements - up to 7.49 × for Copa and 9.53 × for PCC Vivace - without modifying the protocols' core algorithms, demonstrating that delay-based protocols can realize their full potential in cellular networks.
KW - 5G
KW - Congestion Control
KW - LTE
KW - Radio Access Network
UR - https://www.scopus.com/pages/publications/105041147458
UR - https://www.scopus.com/pages/publications/105041147458#tab=citedBy
U2 - 10.1145/3774906.3802791
DO - 10.1145/3774906.3802791
M3 - Conference contribution
AN - SCOPUS:105041147458
T3 - SenSys 2026 - Proceedings of the 2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems, Part of CPS-IoTWeek 2026
SP - 1144
EP - 1157
BT - SenSys 2026 - Proceedings of the 2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems, Part of CPS-IoTWeek 2026
PB - Association for Computing Machinery, Inc
T2 - International Conference on Embedded Artificial Intelligence and Sensing Systems, SenSys 2026
Y2 - 11 May 2026 through 14 May 2026
ER -