@inproceedings{tahir2024efficient,
author = {Tahir, Ammar and Goyal, Prateesh and Marinos, Ilias and Evans, Mike and Mittal, Radhika},
title = {Efficient Policy-Rich Rate Enforcement with Phantom Queues},
booktitle = {ACM SIGCOMM},
year = {2024},
month = {August},
abstract = {Rate enforcement is routinely employed in modern networks (e.g. ISPs rate-limiting users traffic to the subscribed rates). In addition to correctly enforcing the desired rates, rate-limiting mechanisms must be able to support rich rate-sharing policies within each traffic aggregate (e.g. per-flow fairness, weighted fairness, and prioritization). And all of this must be done at scale to efficiently support the vast magnitude of users. There are two primary rate-limiting mechanisms – traffic shaping (that buffers packets in queues to enforce the desired rates and policies) and traffic policing (that filters packets as per the desired rates without buffering them). Policers are light-weight and scalable, but do not support rich policy enforcement and often provide poor rate enforcement (being notoriously hard to configure). Shapers, on the other hand, achieve desired rates and policies, but at the cost of high system resource (memory and CPU) utilization which impacts scalability. In this paper, we explore whether we can get the best of both worlds – the scalability of a policer with the rate and policy enforcement properties of a shaper. We answer this question in the affirmative with our system BC-PQP. BC-PQP augments a policer with (i) multiple phantom queues that simulate buffer occupancy using counters, and enable rich policy enforcement, and (ii) a novel burst control mechanism that enables auto-configuration of the queues for correct rate enforcement. We implement our rate-limiter as a middlebox over DPDK. Our evaluation shows how BC-PQP achieves the rate and policy enforcement properties close to that of a shaper while being up to 7 × more efficient.},
url = {http://approjects.co.za/?big=en-us/research/publication/efficient-policy-rich-rate-enforcement-with-phantom-queues/},
}