Multi-resource fair queueing for packet processing

@inproceedings{Ghodsi2012MultiresourceFQ,
  title={Multi-resource fair queueing for packet processing},
  author={Ali Ghodsi and Vyas Sekar and Matei A. Zaharia and Ion Stoica},
  booktitle={SIGCOMM '12},
  year={2012}
}
Middleboxes are ubiquitous in today's networks and perform a variety of important functions, including IDS, VPN, firewalling, and WAN optimization. These functions differ vastly in their requirements for hardware resources (e.g., CPU cycles and memory bandwidth). Thus, depending on the functions they go through, different flows can consume different amounts of a middlebox's resources. While there is much literature on weighted fair sharing of link bandwidth to isolate flows, it is unclear how… 
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201 Citations
Highly Influential Citations
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Background Citations
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Methods Citations
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Results Citations
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201 Citations

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Citation Type

On Low Complexity Multi-Resource Packet Scheduling with Dominant Resource Fairness
TLDR
A new multi-resource fair queueing scheme that schedules packets in a manner similar to Elastic Round Robin is designed, which requires only O(1) work to schedule a packet and is simple enough to implement in practice.
Multi-resource generalized processor sharing for packet processing
TLDR
The fairness requirements of a queueing scheme are clarified and Dominant Resource Generalized Processor Sharing (DRGPS) is presented, a fluid flow-based fair queueing idealization that strictly realizes Dominant resource Fairness (DRF) at all times.
Multi-Resource Round Robin: A low complexity packet scheduler with Dominant Resource Fairness
TLDR
A new multi-resource fair queueing scheme that schedules packets in a way similar to Elastic Round Robin is designed, which requires only O(1) work to schedule a packet and is simple enough to implement in practice.
Low complexity multi-resource fair queueing with bounded delay
TLDR
This paper presents a new fair queueing algorithm, called Group Multi-Resource Round Robin (GMR3), that schedules packets in O(1) time, while achieving near-perfect fairness with a low scheduling delay bounded by a small constant.
On Fairness-Efficiency Tradeoffs for Multi-resource Packet Processing
  • Wei Wang, B. Liang, Baochun Li
  • Computer Science
    2013 IEEE 33rd International Conference on Distributed Computing Systems Workshops
  • 2013
TLDR
It is shown in this paper that there exists a fairnessefficiency tradeoff when multiple resources are scheduled, and how to design a packet scheduling algorithm to reinforce such a tradeoff is presented.
On the Fairness-Efficiency Tradeoff for Packet Processing with Multiple Resources
TLDR
Experimental results suggest that trading off a modest level of fairness can potentially improve the efficiency to the point where the system capacity is almost saturated.
ATFQ: A Fair and Efficient Packet Scheduling Method in Multi-Resource Environments
TLDR
A novel packet scheduling method, active time fairness queuing (ATFQ), for multi-resource environments that can maximize the resource utilization with the guarantee of fairness and demonstrate that flows get better service in many aspects under ATFQ.
Low-complexity multi-resource packet scheduling for network function virtualization
  • Xin Li, Chen Qian
  • Computer Science, Business
    2015 IEEE Conference on Computer Communications (INFOCOM)
  • 2015
TLDR
This paper designs a novel low-complexity and space-efficient packet scheduling algorithm called Myopia, which supports multi- resource environments such as network function virtualization and demonstrates, via theoretical analysis, prototype implementation, and simulations, that Myopia achieves multi-resource fairness at low cost with short packet delay.
MDFS: Deadline-Driven Flow Scheduling Scheme in Multi-Resource Environments
TLDR
This paper proposes multi-resource & deadline-driven flow scheduling (MDFS) to satisfy the deadline requirements of flows in multi- resource environments and greatly outperforms the performance of other scheduling schemes.
Improving Software Middleboxes and Datacenter Task Schedulers
TLDR
This master's thesis presents Sprayer, a system that uses packet spraying to load balance packets to cores in software middleboxes and Stateful Dominant Resource Fairness (SDRF), a task scheduling policy for datacenters that looks at past allocations and enforces fairness in the long run.
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