TY - GEN
T1 - Are Mobiles Ready for BBR?
AU - Vargas, Santiago
AU - Gunapati, Gautham
AU - Gandhi, Anshul
AU - Balasubramanian, Aruna
N1 - Publisher Copyright:
© 2022 Association for Computing Machinery.
PY - 2022/10/25
Y1 - 2022/10/25
N2 - BBR is a new congestion control algorithm that has seen widespread Internet adoption in recent years with an estimated 40% of Internet traffic volume as BBR traffic. While many studies examine the performance and fairness of BBR on desktops and servers, there is still a question of how BBR would behave on mobile devices. This is especially important because mobiles represent a large segment of Internet devices. In this work, we study the potential performance bottlenecks of BBR if it were to be deployed on Android devices. We compare the performance of BBR and the default congestion control algorithm Cubic for different devices and device configurations. We find that BBR performs poorly compared to Cubic, especially under low-end device configurations. Further investigation reveals that this poor performance is because of packet pacing which is enabled in BBR by default. Pacing increases the computational overhead, which can affect performance for low-end devices. To address this problem, we propose a first cut solution that modifies BBR’s pacing behavior to improve performance while still retaining the benefits of packet pacing.
AB - BBR is a new congestion control algorithm that has seen widespread Internet adoption in recent years with an estimated 40% of Internet traffic volume as BBR traffic. While many studies examine the performance and fairness of BBR on desktops and servers, there is still a question of how BBR would behave on mobile devices. This is especially important because mobiles represent a large segment of Internet devices. In this work, we study the potential performance bottlenecks of BBR if it were to be deployed on Android devices. We compare the performance of BBR and the default congestion control algorithm Cubic for different devices and device configurations. We find that BBR performs poorly compared to Cubic, especially under low-end device configurations. Further investigation reveals that this poor performance is because of packet pacing which is enabled in BBR by default. Pacing increases the computational overhead, which can affect performance for low-end devices. To address this problem, we propose a first cut solution that modifies BBR’s pacing behavior to improve performance while still retaining the benefits of packet pacing.
KW - BBR
KW - Mobiles
KW - TCP Packet Pacing
UR - https://www.scopus.com/pages/publications/85141355751
U2 - 10.1145/3517745.3561438
DO - 10.1145/3517745.3561438
M3 - Conference contribution
AN - SCOPUS:85141355751
T3 - Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC
SP - 551
EP - 559
BT - IMC 2022 - Proceedings of the 2022 ACM Internet Measurement Conference
PB - Association for Computing Machinery
T2 - 22nd ACM Internet Measurement Conference, IMC 2022
Y2 - 25 October 2022 through 27 October 2022
ER -