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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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Datacenter Congestion Control: Identifying what is essential and making it practical
Recent years have seen a slew of papers on datacenter congestion control mechanisms. In this editorial, we ask whether the bulk of this research is needed for the common case where congestion control involves hosts responding to simple congestion signals from the network and the performance goal is reducing some average measure of Flow Completion Time. We raise this question because we find that, out of all the possible variations one could make in congestion control algorithms, the most essential feature is the switch scheduling algorithm. More specifically, we find that congestion control mechanisms that use Shortest-Remaining-Processing-Time (SRPT) achieve superior performance as long as the rate-setting algorithm at the host is reasonable. We further find that while SRPT’s performance is quite robust to host behaviors, the performance of schemes that use scheduling algorithms like FIFO or Fair Queuing depend far more crucially on the rate-setting algorithm, and their performance is typically worse than what can be achieved with SRPT. Given these findings, we then ask whether it is practical to realize SRPT in switches without requiring custom hardware. We observe that approximate and deployable SRPT (ADS) designs exist, which leverage the small number of priority queues supported in almost all commodity switches, and require only software changes in the host and the switches. Our evaluations with one very simple ADS design shows that it can achieve performance close to true SRPT and is significantly better than FIFO. Thus, the answer to our basic question – whether the bulk of recent research on datacenter congestion control algorithms is needed for the common case – is no.
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- Award ID(s):
- 1704941
- PAR ID:
- 10109153
- Date Published:
- Journal Name:
- Computer communication review
- Volume:
- 49
- Issue:
- 3
- ISSN:
- 1943-5819
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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