TY - GEN
T1 - PBE-CC
T2 - 2020 Annual Conference of the ACM Special Interest Group on Data Communication on the Applications, Technologies, Architectures, and Protocols for Computer Communication, SIGCOMM 2020
AU - Xie, Yaxiong
AU - Yi, Fan
AU - Jamieson, Kyle
N1 - Funding Information:
We thank the anonymous SIGCOMM reviewers and our shepherd for their valuable feedback that has improved the quality of this paper. This work was supported by NSF grant CNS-1617161.
Publisher Copyright:
© 2020 ACM.
PY - 2020/7/30
Y1 - 2020/7/30
N2 - Cellular networks are becoming ever more sophisticated and overcrowded, imposing the most delay, jitter, and throughput damage to end-to-end network flows in today's internet. We therefore argue for fine-grained mobile endpoint-based wireless measurements to inform a precise congestion control algorithm through a well-defined API to the mobile's cellular physical layer. Our proposed congestion control algorithm is based on Physical-Layer Bandwidth measurements taken at the Endpoint (PBE-CC), and captures the latest 5G New Radio innovations that increase wireless capacity, yet create abrupt rises and falls in available wireless capacity that the PBE-CC sender can react to precisely and rapidly. We implement a proof-of-concept prototype of the PBE measurement module on software-defined radios and the PBE sender and receiver in C. An extensive performance evaluation compares PBE-CC head to head against the cellular-aware and wireless-oblivious congestion control protocols proposed in the research community and in deployment, in mobile and static mobile scenarios, and over busy and idle networks. Results show 6.3% higher average throughput than BBR, while simultaneously reducing 95th percentile delay by 1.8x.
AB - Cellular networks are becoming ever more sophisticated and overcrowded, imposing the most delay, jitter, and throughput damage to end-to-end network flows in today's internet. We therefore argue for fine-grained mobile endpoint-based wireless measurements to inform a precise congestion control algorithm through a well-defined API to the mobile's cellular physical layer. Our proposed congestion control algorithm is based on Physical-Layer Bandwidth measurements taken at the Endpoint (PBE-CC), and captures the latest 5G New Radio innovations that increase wireless capacity, yet create abrupt rises and falls in available wireless capacity that the PBE-CC sender can react to precisely and rapidly. We implement a proof-of-concept prototype of the PBE measurement module on software-defined radios and the PBE sender and receiver in C. An extensive performance evaluation compares PBE-CC head to head against the cellular-aware and wireless-oblivious congestion control protocols proposed in the research community and in deployment, in mobile and static mobile scenarios, and over busy and idle networks. Results show 6.3% higher average throughput than BBR, while simultaneously reducing 95th percentile delay by 1.8x.
KW - Capacity estimation
KW - Cellular network
KW - Control information
KW - LTE
KW - Physical control channel
KW - TCP congestion control
KW - Transport protocols
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U2 - 10.1145/3387514.3405880
DO - 10.1145/3387514.3405880
M3 - Conference contribution
AN - SCOPUS:85094812927
T3 - SIGCOMM 2020 - Proceedings of the 2020 Annual Conference of the ACM Special Interest Group on Data Communication on the Applications, Technologies, Architectures, and Protocols for Computer Communication
SP - 451
EP - 464
BT - SIGCOMM 2020 - Proceedings of the 2020 Annual Conference of the ACM Special Interest Group on Data Communication on the Applications, Technologies, Architectures, and Protocols for Computer Communication
PB - Association for Computing Machinery
Y2 - 10 August 2020 through 14 August 2020
ER -