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Programmable Calendar Queues for High-speed Packet Scheduling

Naveen Kr. Sharma, Chenxingyu Zhao, Ming Liu, Pravein G. Kannan, Changhoon Kim, Arvind Krishnamurthy, Anirudh Sivaraman

2020Year
119Citations
42Top-tier citations

Abstract

Packet schedulers traditionally focus on the prioritized transmission of packets. Scheduling is often realized through coarse-grained queue-level priorities, as in today's switches, or through fine-grained packet-level priorities, as in recent proposals such as PIFO. Unfortunately, fixed packet priorities determined when a packet is received by the traffic manager are not sufficient to support a broad class of scheduling algorithms that require the priorities of packets to change as a function of the time it has spent inside the network. In this paper, we revisit the Calendar Queue abstraction and show that it is an appropriate fit for scheduling algorithms that not only require prioritization but also perform dynamic escalation of packet priorities. We show that the calendar queue abstraction can be realized using either dataplane primitives or control-plane commands that dynamically modify the scheduling status of queues. Further, when paired with programmable switch pipelines, we can realize programmable calendar queues that can emulate a diverse set of scheduling policies. We demonstrate the power of this abstraction using three case studies that implement variants of LSTF, Fair Queueing, and pFabric in order to provide stronger delay guarantees, burst-friendly fairness, and starvation-free prioritization of short flows, respectively. We evaluate the benefits associated with these scheduling policies using both a custom simulator and a small-scale testbed.

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