Flow Queue PIE: A Hybrid Packet Scheduler and Active Queue Management Algorithm
draft-tahiliani-tsvwg-fq-pie-02

Transport and Services Working Group                     M. P. Tahiliani
Internet-Draft                National Institute of Technology Karnataka
Intended status: Experimental                                7 July 2025
Expires: 8 January 2026

 Flow Queue PIE: A Hybrid Packet Scheduler and Active Queue Management
                               Algorithm
                    draft-tahiliani-tsvwg-fq-pie-02

Abstract

   This document presents Flow Queue Proportional Integral controller
   Enhanced (FQ-PIE), a hybrid packet scheduler and Active Queue
   Management (AQM) algorithm to isolate flows and tackle the problem of
   bufferbloat.  FQ-PIE uses hashing to classify incoming packets into
   different queues and provide flow isolation.  Packets are dequeued by
   using a variant of the round robin scheduler.  Each such flow is
   managed by the PIE algorithm to maintain high link utilization while
   controlling the queue delay to a target value.

About This Document

   This note is to be removed before publishing as an RFC.

   The latest revision of this draft can be found at
   https://mohittahiliani.github.io/draft-tahiliani-tsvwg-fq-pie/draft-
   tahiliani-tsvwg-fq-pie.html.  Status information for this document
   may be found at https://datatracker.ietf.org/doc/draft-tahiliani-
   tsvwg-fq-pie/.

   Discussion of this document takes place on the Transport and Services
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   Source for this draft and an issue tracker can be found at
   https://github.com/mohittahiliani/draft-tahiliani-tsvwg-fq-pie.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   3
   3.  Conventions and Definitions . . . . . . . . . . . . . . . . .   3
   4.  The FQ-PIE Algorithm  . . . . . . . . . . . . . . . . . . . .   3
     4.1.  Enqueue . . . . . . . . . . . . . . . . . . . . . . . . .   4
     4.2.  Dequeue . . . . . . . . . . . . . . . . . . . . . . . . .   5
     4.3.  ECN Support . . . . . . . . . . . . . . . . . . . . . . .   5
   5.  Scope of Experimentation  . . . . . . . . . . . . . . . . . .   5
   6.  Security Considerations . . . . . . . . . . . . . . . . . . .   6
   7.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   6
   8.  References  . . . . . . . . . . . . . . . . . . . . . . . . .   6
     8.1.  Normative References  . . . . . . . . . . . . . . . . . .   6
     8.2.  Informative References  . . . . . . . . . . . . . . . . .   7
   Author's Address  . . . . . . . . . . . . . . . . . . . . . . . .   8

1.  Introduction

   Flow Queue Proportional Integral Controller Enhanced (FQ-PIE)
   combines flow queuing with the PIE (Proportional Integral controller
   Enhanced) [RFC8033] Active Queue Management (AQM) algorithm to
   provide flow isolation and reduce bufferbloat by controlling queue
   delay.  This is similar to how Flow Queue Controlled Delay (FQ-CoDel)
   [RFC8290] integrates flow queuing with the CoDel (Controlled Delay)
   AQM algorithm [RFC8289].

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   When a packet is enqueued, it is classified into different queues to
   ensure isolation between flows.  While the goal of flow queuing is to
   assign a unique queue to each flow, flows can instead be hashed into
   a set of buckets using a hash function, where each bucket corresponds
   to its own queue.  The PIE AQM operates independently on each of
   these queues, enabling each flow to receive appropriate congestion
   signals either implicitly (via packet drops) or explicitly (via
   mechanisms such as Explicit Congestion Notification (ECN) [RFC3168]).
   For dequeuing, FQ-PIE employs the Deficit Round Robin (DRR) based
   scheduler described in [RFC8290], which ensures fair packet
   scheduling across the different queues.

   FQ-PIE has been incorporated into the mainline Linux kernel as a
   queuing discipline (qdisc) [LINUX-FQ-PIE] and is supported by several
   Linux distributions, and has also been incorporated into FreeBSD
   [FREEBSD-FQ-PIE].  Additionally, an implementation of FQ-PIE is
   available in the ns-3 network simulator [ns-3-FQ-PIE].

2.  Terminology

   This document uses the terms defined in Section 1.1 of [RFC8290] and
   Sections 4 and 5 of [RFC8033].

3.  Conventions and Definitions

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "NOT RECOMMENDED", "MAY", and
   "OPTIONAL" in this document are to be interpreted as described in
   BCP 14 [RFC2119] [RFC8174] when, and only when, they appear in all
   capitals, as shown here.

4.  The FQ-PIE Algorithm

   The FQ-PIE algorithm consists of two main components: (i) flow
   queuing, which isolates competing flows by treating flows that build
   queues differently from those that do not, and (ii) the PIE AQM
   algorithm, which manages each queue and maintains a target queue
   delay (recommended as 15 ms in [RFC8033]).  Flow queuing works by
   classifying incoming packets into different queues during the enqueue
   phase and then scheduling outgoing packets from these queues during
   the dequeue phase.  The PIE algorithm, however, only operates during
   enqueue.

   The details of flow queuing and the PIE algorithm are not covered
   here; for more information, please refer to [RFC8290] and [RFC8033],
   respectively.

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4.1.  Enqueue

   The packet enqueue process is described as follows: first, the
   incoming packets are classified into different queues by hashing the
   5-tuple, which includes the protocol number, source and destination
   IP addresses, and source and destination port numbers, similar to the
   approach used in FQ-CoDel.

   Next, the packet is passed to the PIE algorithm, which uses a drop
   probability to determine whether the packet should be enqueued or
   dropped, as outlined in [RFC8033].  This drop probability is updated
   periodically (every 15 ms, as per [RFC8033]) based on the current
   queue delay’s deviation from the target delay and whether the delay
   is trending up or down.

   [RFC8033] presents two methods for calculating the current queue
   delay: one uses Little’s Law, estimating delay based on the queue
   length and the average dequeue rate; the other takes direct
   measurements using timestamps, as implemented in CoDel and FQ-CoDel.
   However, experimental studies on the PIE algorithm [REVISIT-PIE]
   indicate that while the dequeue rate is intended to estimate the
   transmission rate of packets over the outgoing link, it may instead
   reflect the rate at which packets move from the host stack (e.g.,
   Linux qdisc) to the device driver’s transmission ring.  Additionally,
   in FQ-PIE, queue delay estimates from Little’s Law can be unreliable,
   as it’s challenging to calculate an accurate per-queue dequeue rate.
   Consequently, the FQ-PIE algorithm SHOULD calculate the current queue
   delay using direct measurements with timestamps.

   It is important to note that the timestamping approach provides a
   "per-packet queue delay," while the drop probability is calculated
   periodically (every 15 ms, as specified in [RFC8033]).  Therefore,
   the FQ-PIE algorithm MAY use the queue delay value from the most
   recently dequeued packet when calculating the drop probability.

   At the time of writing this document, the Linux, FreeBSD and ns-3
   implementations use timestamps to calculate the current queue delay
   and consider the measurements from the most recently dequeued packet
   when calculating the drop probability.  Additionally, these
   implementations offer an option to use the dequeue rate estimation
   technique based on Little’s Law.

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   Lastly, if an incoming packet arrives when the total number of
   enqueued packets has already saturated the queue capacity, FQ-PIE
   drops the packet without further processing.  In contrast, FQ-CoDel
   identifies the queue with the largest current byte count (i.e., a
   "fat flow") when the queue capacity is saturated and drops half of
   the packets from this queue (up to a maximum of 64 packets, as
   specified in Section 4.1 of [RFC8290]).  FQ-PIE does not adopt this
   approach for the reasons explained below.

   Since CoDel performs its queue control operations during the dequeue
   phase and does not drop incoming packets until the queue is full, it
   tends to fill its queues more quickly than PIE, which drops packets
   randomly during the enqueue phase.  This is especially true when
   CoDel has just entered the dropping phase, as it takes time to ramp
   up its packet dropping frequency.  Therefore, the strategy of
   dropping half of the packets from a fat flow's queue suits FQ-CoDel
   but is not appropriate for FQ-PIE.  Dropping packets in bulk might
   lead to underutilization of link capacity, as FQ-PIE already enforces
   queue control during the enqueue phase.

4.2.  Dequeue

   The packet dequeue process in FQ-PIE is similar to that in FQ-CoDel,
   where a DRR-based scheduler is used to dequeue packets from each
   queue.  The key difference is that in FQ-CoDel, CoDel operates during
   this phase, whereas in FQ-PIE, PIE operates during the enqueue phase.
   The method for obtaining direct measurements of per-packet queue
   delay is the same in both FQ-PIE and FQ-CoDel, and is performed
   during the dequeue phase.

4.3.  ECN Support

   FQ-PIE MAY support ECN by marking ECN-Capable Transport (ECT) packets
   [RFC3168] instead of dropping them, in accordance with the
   recommendations in Section 5.1 of [RFC8033].  The Linux, FreeBSD and
   ns-3 implementations of FQ-PIE comply with these recommendations at
   the time of writing this document.

5.  Scope of Experimentation

   The design of the FQ-PIE algorithm as described in this document has
   been a part of the Linux kernel since version 5.6 (released on March
   29, 2020), FreeBSD since version 11.0-RELEASE (released on October
   10, 2016), and the ns-3 network simulator since version 3.34
   (released on July 14, 2021).  The following aspects can be explored
   for further study and experimentation:

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   *  The scenarios similar to those summarized in Figure 4 of [RFC7928]
      MAY be considered for an in-depth experimentation of FQ-PIE.

   *  Interactions between flow queuing and new congestion control
      algorithms, such as Bottleneck Bandwidth and Round-trip
      propagation time (BBR) [I-D.draft-ietf-ccwg-bbr].

   *  Different packet drop probability thresholds to switch from
      marking packets to dropping packets.

   *  Evaluation of the enhancements to the PIE algorithm described in
      Section 5 in [RFC8033] to decide which enhancements are suitable
      for deployment with FQ-PIE.

   *  Effectiveness of FQ-PIE in terms of providing isolation and
      minimal latency for low volume traffic (short flows) such as web
      applications, instant messaging applications, interactive
      applications and IoT applications.

   *  Different hashing mechanisms to improve the overall working of
      flow queuing.

6.  Security Considerations

   The FQ-PIE algorithm introduces no specific security exposures.  The
   flow queuing aspect of the FQ-PIE algorithm is the same as FQ-CoDel,
   and hence has similar advantages from the security perspective as
   outlined in Section 8 of [RFC8290].  The PIE aspect of the FQ-PIE
   algorithm is the same as described in [RFC8033] that does not have
   any security exposures.

7.  IANA Considerations

   This document has no IANA actions.

8.  References

8.1.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119,
              DOI 10.17487/RFC2119, March 1997,
              <https://www.rfc-editor.org/rfc/rfc2119>.

   [RFC3168]  Ramakrishnan, K., Floyd, S., and D. Black, "The Addition
              of Explicit Congestion Notification (ECN) to IP",
              RFC 3168, DOI 10.17487/RFC3168, September 2001,
              <https://www.rfc-editor.org/rfc/rfc3168>.

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   [RFC7928]  Kuhn, N., Ed., Natarajan, P., Ed., Khademi, N., Ed., and
              D. Ros, "Characterization Guidelines for Active Queue
              Management (AQM)", RFC 7928, DOI 10.17487/RFC7928, July
              2016, <https://www.rfc-editor.org/rfc/rfc7928>.

   [RFC8033]  Pan, R., Natarajan, P., Baker, F., and G. White,
              "Proportional Integral Controller Enhanced (PIE): A
              Lightweight Control Scheme to Address the Bufferbloat
              Problem", RFC 8033, DOI 10.17487/RFC8033, February 2017,
              <https://www.rfc-editor.org/rfc/rfc8033>.

   [RFC8174]  Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
              2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
              May 2017, <https://www.rfc-editor.org/rfc/rfc8174>.

   [RFC8289]  Nichols, K., Jacobson, V., McGregor, A., Ed., and J.
              Iyengar, Ed., "Controlled Delay Active Queue Management",
              RFC 8289, DOI 10.17487/RFC8289, January 2018,
              <https://www.rfc-editor.org/rfc/rfc8289>.

   [RFC8290]  Hoeiland-Joergensen, T., McKenney, P., Taht, D., Gettys,
              J., and E. Dumazet, "The Flow Queue CoDel Packet Scheduler
              and Active Queue Management Algorithm", RFC 8290,
              DOI 10.17487/RFC8290, January 2018,
              <https://www.rfc-editor.org/rfc/rfc8290>.

8.2.  Informative References

   [FREEBSD-FQ-PIE]
              Al-Saadi, R. and G. Armitage, "Dummynet AQM v0. 2–CoDel,
              FQ-CoDel, PIE and FQ-PIE for FreeBSD’s ipfw/dummynet
              Framework", Centre for Advanced Internet Architectures,
              Swinburne University of Technology, Melbourne, Australia,
              Tech. Rep. A, 160418 , October 2016,
              <https://web.archive.org/web/20241018123533/
              http://caia.swin.edu.au/reports/160418A/CAIA-TR-
              160418A.pdf>.

   [I-D.draft-ietf-ccwg-bbr]
              Cardwell, N., Swett, I., and J. Beshay, "BBR Congestion
              Control", Work in Progress, Internet-Draft, draft-ietf-
              ccwg-bbr-03, 7 July 2025,
              <https://datatracker.ietf.org/doc/html/draft-ietf-ccwg-
              bbr-03>.

   [LINUX-FQ-PIE]
              Ramakrishnan, G., Bhasi, M., Saicharan, V., Monis, L.,
              Patil, S. D., and M. P. Tahiliani, "FQ-PIE Queue

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              Discipline in the Linux Kernel: Design, Implementation and
              Challenges", 2019 IEEE 44th LCN Symposium on Emerging
              Topics in Networking (LCN Symposium) , October 2019,
              <https://ieeexplore.ieee.org/abstract/document/9000684>.

   [ns-3-FQ-PIE]
              "FQ-PIE Queue Discipline in ns-3", July 2021,
              <https://www.nsnam.org/docs/models/html/fq-pie.html>.

   [REVISIT-PIE]
              Imputato, P., Avallone, S., Tahiliani, M. P., and G.
              Ramakrishnan, "Revisiting Design Choices in Queue
              Disciplines: The PIE Case", Computer Networks , April
              2020, <https://www.sciencedirect.com/science/article/pii/
              S1389128619313775>.

Author's Address

   Mohit P. Tahiliani
   National Institute of Technology Karnataka
   P. O. Srinivasnagar, Surathkal
   Mangalore, Karnataka - 575025
   India
   Email: tahiliani@nitk.edu.in
   URI:   http://tahiliani.in

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