Abstract
Multipath transport, as embodied in MPTCP, is deployed to improve throughput and reliability in mobile and residential access networks, with additional use-cases including spreading load in data centers and WANs. However, MPTCP is fundamentally tied to TCP Reno's legacy AIMD algorithm, and significantly lags behind the performance of modern single-path designs. Consequently, MPTCP fails to achieve high performance in many real-world environments. We present MPCC, a high-performance multipath congestion control architecture. To achieve our combined goals of fairness and high performance in challenging environments, MPCC employs online convex optimization (a.k.a. online learning). In experiments with a kernel implementation on emulated and live networks, MPCC significantly outperforms MPTCP.
| Original language | English |
|---|---|
| Title of host publication | CoNEXT 2020 - Proceedings of the 16th International Conference on Emerging Networking EXperiments and Technologies |
| Publisher | Association for Computing Machinery, Inc |
| Pages | 121-135 |
| Number of pages | 15 |
| ISBN (Electronic) | 9781450379489 |
| DOIs | |
| State | Published - 23 Nov 2020 |
| Event | 16th ACM Conference on Emerging Networking Experiment and Technologies, CoNEXT 2020 - Barcelona, Spain Duration: 1 Dec 2020 → 4 Dec 2020 |
Publication series
| Name | CoNEXT 2020 - Proceedings of the 16th International Conference on Emerging Networking EXperiments and Technologies |
|---|
Conference
| Conference | 16th ACM Conference on Emerging Networking Experiment and Technologies, CoNEXT 2020 |
|---|---|
| Country/Territory | Spain |
| City | Barcelona |
| Period | 1/12/20 → 4/12/20 |
Bibliographical note
Publisher Copyright:© 2020 ACM.
Keywords
- congestion control
- multipath