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Cloud services are deployed in datacenters connected though high-bandwidth Wide Area Networks (WANs). We find that WAN traffic negatively impacts the performance of datacenter traffic, increasing tail latency by 2.5x, despite its small bandwidth demand. This behavior is caused by the long round-trip time (RTT) for WAN traffic, combined with limited buffering in datacenter switches. The long WAN RTT forces datacenter traffic to take the full burden of reacting to congestion. Furthermore, datacenter traffic changes on a faster time-scale than the WAN RTT, making it difficult for WAN congestion control to estimate available bandwidth accurately. We present Annulus, a congestion control scheme that relies on two control loops to address these challenges. One control loop leverages existing congestion control algorithms for bottlenecks where there is only one type of traffic (i.e., WAN or datacenter). The other loop handles bottlenecks shared between WAN and datacenter traffic near the traffic source, using direct feedback from the bottleneck. We implement Annulus on a testbed and in simulation. Compared to baselines using BBR for WAN congestion control and DCTCP or DCQCN for datacenter congestion control, Annulus increases bottleneck utilization by 10% and lowers datacenter flow completion time by 1.3-3.5x.
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Principles for Internet Congestion Management
Given the technical flaws with—and the increasing non-observance of—the TCP-friendliness paradigm, we must rethink how the Inter- net should manage bandwidth allocation. We explore this question from first principles, but remain within the constraints of the In- ternet’s current architecture and commercial arrangements. We propose a new framework, Recursive Congestion Shares (RCS), that provides bandwidth allocations independent of which congestion control algorithms flows use but consistent with the Internet’s eco- nomics. We show that RCS achieves this goal using game-theoretic calculations and simulations as well as network emulation.
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- PAR ID:
- 10568565
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400706141
- Page Range / eLocation ID:
- 166 to 180
- Format(s):
- Medium: X
- Location:
- Sydney NSW Australia
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3651890.3672247
