Just In Time Delivery: Leveraging Operating Systems Knowledge for Better Datacenter Congestion Control


Amy Ousterhout and Adam Belay, MIT CSAIL; Irene Zhang, Microsoft Research


Network links and server CPUs are heavily contended resources in modern datacenters. To keep tail latencies low, datacenter operators drastically overprovision both types of resources today, and there has been significant research into effectively managing network traffic and CPU load. However, this work typically looks at the two resources in isolation.

In this paper, we make the observation that, in the datacenter, the allocation of network and CPU resources should be co-designed for the most efficiency and the best response times. For example, while congestion control protocols can prioritize traffic from certain flows, this provides no benefit if the traffic arrives at an overloaded server that will only queue the request.

This paper explores the potential benefits of such a co-designed resource allocator and considers the recent work in both CPU scheduling and congestion control that is best suited to such a system. We propose a Chimera, a new datacenter OS that integrates a receiver-based congestion control protocol with OS insight into application queues, using the recent Shenango operating system.

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