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Internet Engineering Task Force (IETF)                          F. BakerRequest for Comments: 7806                                        R. PanCategory: Informational                                    Cisco SystemsISSN: 2070-1721                                               April 2016On Queuing, Marking, and DroppingAbstract   This note discusses queuing and marking/dropping algorithms.  While   these algorithms may be implemented in a coupled manner, this note   argues that specifications, measurements, and comparisons should   decouple the different algorithms and their contributions to system   behavior.Status of This Memo   This document is not an Internet Standards Track specification; it is   published for informational purposes.   This document is a product of the Internet Engineering Task Force   (IETF).  It represents the consensus of the IETF community.  It has   received public review and has been approved for publication by the   Internet Engineering Steering Group (IESG).  Not all documents   approved by the IESG are a candidate for any level of Internet   Standard; seeSection 2 of RFC 5741.   Information about the current status of this document, any errata,   and how to provide feedback on it may be obtained athttp://www.rfc-editor.org/info/rfc7806.Copyright Notice   Copyright (c) 2016 IETF Trust and the persons identified as the   document authors.  All rights reserved.   This document is subject toBCP 78 and the IETF Trust's Legal   Provisions Relating to IETF Documents   (http://trustee.ietf.org/license-info) in effect on the date of   publication of this document.  Please review these documents   carefully, as they describe your rights and restrictions with respect   to this document.  Code Components extracted from this document must   include Simplified BSD License text as described in Section 4.e of   the Trust Legal Provisions and are provided without warranty as   described in the Simplified BSD License.Baker & Pan                   Informational                     [Page 1]

RFC 7806            On Queuing, Marking, and Dropping         April 2016Table of Contents1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .22.  Fair Queuing: Algorithms and History  . . . . . . . . . . . .32.1.  Generalized Processor Sharing . . . . . . . . . . . . . .32.1.1.  GPS Comparisons: Transmission Quanta  . . . . . . . .42.1.2.  GPS Comparisons: Flow Definition  . . . . . . . . . .42.1.3.  GPS Comparisons: Unit of Measurement  . . . . . . . .52.2.  GPS Approximations  . . . . . . . . . . . . . . . . . . .52.2.1.  Definition of a Queuing Algorithm . . . . . . . . . .52.2.2.  Round-Robin Models  . . . . . . . . . . . . . . . . .62.2.3.  Calendar Queue Models . . . . . . . . . . . . . . . .7       2.2.4.  Work-Conserving Models and Stochastic Fairness               Queuing . . . . . . . . . . . . . . . . . . . . . . .92.2.5.  Non-Work-Conserving Models and Virtual Clock  . . . .93.  Queuing, Marking, and Dropping  . . . . . . . . . . . . . . .103.1.  Queuing with Tail Mark/Drop . . . . . . . . . . . . . . .113.2.  Queuing with CoDel Mark/Drop  . . . . . . . . . . . . . .113.3.  Queuing with RED or PIE Mark/Drop . . . . . . . . . . . .114.  Conclusion  . . . . . . . . . . . . . . . . . . . . . . . . .125.  Security Considerations . . . . . . . . . . . . . . . . . . .136.  References  . . . . . . . . . . . . . . . . . . . . . . . . .136.1.  Normative References  . . . . . . . . . . . . . . . . . .136.2.  Informative References  . . . . . . . . . . . . . . . . .13   Acknowledgements  . . . . . . . . . . . . . . . . . . . . . . . .15   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .161.  Introduction   In the discussion of Active Queue Management (AQM), there has been   discussion of the coupling of queue management algorithms such as   Stochastic Fairness Queuing [SFQ], Virtual Clock [VirtualClock], or   Deficit Round Robin [DRR] with mark/drop algorithms such as   Controlled Delay (CoDel) [DELAY-AQM] or Proportional Integral   controller Enhanced (PIE) [AQM-PIE].  In the interest of clarifying   the discussion, we document possible implementation approaches to   that and analyze the possible effects and side effects.  The language   and model derive from the Architecture for Differentiated Services   [RFC2475].   This note is informational and is intended to describe reasonable   possibilities without constraining outcomes.  This is not so much   about "right" or "wrong" as it is "what might be reasonable" and   discusses several possible implementation strategies.  Also, while   queuing might be implemented in almost any layer, the note   specifically addresses queues that might be used in the   Differentiated Services Architecture and are therefore at or below   the IP layer.Baker & Pan                   Informational                     [Page 2]

RFC 7806            On Queuing, Marking, and Dropping         April 20162.  Fair Queuing: Algorithms and History   There is extensive history in the set of algorithms collectively   referred to as "fair queuing".  The model was initially discussed in   [RFC970], which proposed it hypothetically as a solution to the TCP   Silly Window Syndrome issue in BSD 4.1.  The problem was that, due to   a TCP implementation bug, some senders would settle into sending a   long stream of very short segments, which unnecessarily consumed   bandwidth on TCP and IP headers and occupied short packet buffers,   thereby disrupting competing sessions.  Nagle suggested that if   packet streams were sorted by their source address and the sources   treated in a round-robin fashion, a sender's effect on end-to-end   latency and increased loss rate would primarily affect only itself.   This touched off perhaps a decade of work by various researchers on   what was and is termed "fair queuing", philosophical discussions of   the meaning of the word "fair", operational reasons that one might   want a "weighted" or "predictably unfair" queuing algorithm, and so   on.2.1.  Generalized Processor Sharing   Conceptually, any fair queuing algorithm attempts to implement some   approximation to the Generalized Processor Sharing [GPS] model.   The GPS model, in its essence, presumes that a set of identified data   streams, called "flows", pass through an interface.  Each flow has a   rate when measured over a period of time; a voice session might, for   example, require 64 kbit/s plus whatever overhead is necessary to   deliver it, and a TCP session might have variable throughput   depending on where it is in its evolution.  The premise of   Generalized Processor Sharing is that on all time scales, the flow   occupies a predictable bit rate so that if there is enough bandwidth   for the flow in the long term, it also lacks nothing in the short   term.  "All time scales" is obviously untenable in a packet network   -- and even in a traditional Time-Division Multiplexer (TDM) circuit   switch network -- because a timescale shorter than the duration of a   packet will only see one packet at a time.  However, it provides an   ideal for other models to be compared against.   There are a number of attributes of approximations to the GPS model   that bear operational consideration, including at least the   transmission quanta, the definition of a "flow", and the unit of   measurement.  Implementation approaches have different practical   impacts as well.Baker & Pan                   Informational                     [Page 3]

RFC 7806            On Queuing, Marking, and Dropping         April 20162.1.1.  GPS Comparisons: Transmission Quanta   The most obvious comparison between the GPS model and common   approximations to it is that real world data is not delivered   uniformly, but in some quantum.  The smallest quantum in a packet   network is a packet.  But quanta can be larger; for example, in video   applications, it is common to describe data flow in frames per   second, where a frame describes a picture on a screen or the changes   made from a previous one.  A single video frame is commonly on the   order of tens of packets.  If a codec is delivering thirty frames per   second, it is conceivable that the packets comprising a frame might   be sent as thirty bursts per second, with each burst sent at the   interface rate of the camera or other sender.  Similarly, TCP   exchanges have an initial window (common values of which include 1,   2, 3, 4 [RFC3390], and 10 [RFC6928]), and there are also reports of   bursts of 64 KB at the relevant Maximum Segment Size (MSS), which is   to say about 45 packets in one burst, presumably coming from TCP   Segment Offload ((TSO) also called TCP Offload Engine (TOE)) engines   (at least one implementation is known to be able to send a burst of   256 KB).  After that initial burst, TCP senders commonly send pairs   of packets but may send either smaller or larger bursts [RFC5690].2.1.2.  GPS Comparisons: Flow Definition   An important engineering trade-off relevant to GPS is the definition   of a "flow".  A flow is, by definition, a defined data stream.   Common definitions include:   o  packets in a single transport layer session ("microflow"),      identified by a five-tuple [RFC2990];   o  packets between a single pair of addresses, identified by a source      and destination address or prefix;   o  packets from a single source address or prefix [RFC970];   o  packets to a single destination address or prefix; and   o  packets to or from a single subscriber, customer, or peer      [RFC6057].  In Service Provider operations, this might be a      neighboring Autonomous System; in broadband, this might be a      residential customer.   The difference should be apparent.  Consider a comparison between   sorting by source address or destination address, to pick two   examples, in the case that a given router interface has N application   sessions going through it between N/2 local destinations and N remote   sources.  Sorting by source, or in this case by source/destinationBaker & Pan                   Informational                     [Page 4]

RFC 7806            On Queuing, Marking, and Dropping         April 2016   pair, would give each remote peer an upper-bound guarantee of 1/N of   the available capacity, which might be distributed very unevenly   among the local destinations.  Sorting by destination would give each   local destination an upper-bound guarantee of 2/N of the available   capacity, which might be distributed very unevenly among the remote   systems and correlated sessions.  Who is one fair to?  In both cases,   they deliver equal service by their definition, but that might not be   someone else's definition.   Flow fairness, and the implications of TCP's congestion avoidance   algorithms, is discussed extensively in [NoFair].2.1.3.  GPS Comparisons: Unit of Measurement   And finally, there is the question of what is measured for rate.  If   the only objective is to force packet streams to not dominate each   other, it is sufficient to count packets.  However, if the issue is   the bit rate of a Service Level Agreement (SLA), one must consider   the sizes of the packets (the aggregate throughput of a flow measured   in bits or bytes).  If predictable unfairness is a consideration, the   value must be weighted accordingly.   [RFC7141] discusses measurement.2.2.  GPS Approximations   Carrying the matter further, a queuing algorithm may also be termed   "work conserving" or "non work conserving".  A queue in a work-   conserving algorithm, by definition, is either empty, in which case   no attempt is being made to dequeue data from it, or contains   something, in which case the algorithm continuously tries to empty   the queue.  A work-conserving queue that contains queued data at an   interface with a given rate will deliver data at that rate until it   empties.  A non-work-conserving queue might stop delivering even   though it still contains data.  A common reason for doing this is to   impose an artificial upper bound on a class of traffic that is lower   than the rate of the underlying physical interface.2.2.1.  Definition of a Queuing Algorithm   In the discussion following, we assume a basic definition of a   queuing algorithm.  A queuing algorithm has, at minimum:   o  some form of internal storage for the elements kept in the queue;Baker & Pan                   Informational                     [Page 5]

RFC 7806            On Queuing, Marking, and Dropping         April 2016   o  if it has multiple internal classifications, then it has      *  a method for classifying elements and      *  additional storage for the classifier and implied classes;   o  potentially, a method for creating the queue;   o  potentially, a method for destroying the queue;   o  an enqueuing method for placing packets into the queue or queuing      system; and   o  a dequeuing method for removing packets from the queue or queuing      system.   There may also be other information or methods, such as the ability   to inspect the queue.  It also often has inspectable external   attributes, such as the total volume of packets or bytes in queue,   and may have limit thresholds, such as a maximum number of packets or   bytes the queue might hold.   For example, a simple FIFO queue has a linear data structure,   enqueues packets at the tail, and dequeues packets from the head.  It   might have a maximum queue depth and a current queue depth maintained   in packets or bytes.2.2.2.  Round-Robin Models   One class of implementation approaches, generically referred to as   "Weighted Round Robin" (WRR), implements the structure of the queue   as an array or ring of subqueues associated with flows for whatever   definition of a flow is important.   The arriving packet must, of course, first be classified.  If a hash   is used as a classifier, the hash result might be used as an array   index, selecting the subqueue that the packet will go into.  One can   imagine other classifiers, such as using a Differentiated Services   Code Point (DSCP) value as an index into an array containing the   queue number for a flow, or more complex access list implementations.   In any event, a subqueue contains the traffic for a flow, and data is   sent from each subqueue in succession.   Upon entering the queue, the enqueue method places a classified   packet into a simple FIFO subqueue.Baker & Pan                   Informational                     [Page 6]

RFC 7806            On Queuing, Marking, and Dropping         April 2016   On dequeue, the subqueues are searched in round-robin order, and when   a subqueue is identified that contains data, the dequeue method   removes a specified quantum of data from it.  That quantum is at   minimum a packet, but it may be more.  If the system is intended to   maintain a byte rate, there will be memory between searches of the   excess previously dequeued.                            +-+                          +>|1|                          | +-+                          |  |                          | +-+               +-+                          | |1|             +>|3|                          | +-+             | +-+                          |  |              |  |                          | +-+      +-+    | +-+                          | |1|    +>|2|    | |3|                          | +-+    | +-+    | +-+                          |  A     |  A     |  A                          |  |     |  |     |  |                         ++--++   ++--++   ++--++                      +->| Q  |-->| Q  |-->| Q  |--+                      |  +----+   +----+   +----+  |                      +----------------------------+                       Figure 1: Round-Robin Queues2.2.3.  Calendar Queue Models   Another class of implementation approaches, generically referred to   as Calendar Queue Implementations [CalendarQueue], implements the   structure of the queue as an array or ring of subqueues (often called   "buckets") associated with time or sequence; each bucket contains the   set of packets, which may be null, intended to be sent at a certain   time or following the emptying of the previous bucket.  The queue   structure includes a look-aside table that indicates the current   depth (which is to say, the next bucket) of any given class of   traffic, which might similarly be identified using a hash, a DSCP, an   access list, or any other classifier.  Conceptually, the queues each   contain zero or more packets from each class of traffic.  One is the   queue being emptied "now"; the rest are associated with some time or   sequence in the future.  The characteristics under "load" have been   investigated in [Deadline].   Upon entering the queue, the enqueue method, considering a classified   packet, determines the current depth of that class with a view to   scheduling it for transmission at some time or sequence in the   future.  If the unit of scheduling is a packet and the queuingBaker & Pan                   Informational                     [Page 7]

RFC 7806            On Queuing, Marking, and Dropping         April 2016   quantum is one packet per subqueue, a burst of packets arrives in a   given flow, and if at the start the flow has no queued data, the   first packet goes into the "next" queue, the second into its   successor, and so on.  If there was some data in the class, the first   packet in the burst would go into the bucket pointed to by the look-   aside table.  If the unit of scheduling is time, the explanation inSection 2.2.5 might be simplest to follow, but the bucket selected   will be the bucket corresponding to a given transmission time in the   future.  A necessary side effect, memory being finite, is that there   exist a finite number of "future" buckets.  If enough traffic arrives   to cause a class to wrap, one is forced to drop something (tail   drop).   On dequeue, the buckets are searched at their stated times or in   their stated sequence, and when a bucket is identified that contains   data, the dequeue method removes a specified quantum of data from it   and, by extension, from the associated traffic classes.  A single   bucket might contain data from a number of classes simultaneously.                             +-+                           +>|1|                           | +-+                           |  |                           | +-+      +-+                           | |2|    +>|2|                           | +-+    | +-+                           |  |     |  |                           | +-+    | +-+      +-+                           | |3|    | |1|    +>|1|                           | +-+    | +-+    | +-+                           |  A     |  A     |  A                           |  |     |  |     |  |                          ++--++   ++--++   ++--++                  "now"+->| Q  |-->| Q  |-->| Q  |-->...                          +----+   +----+   +----+                             A       A         A                             |3      |2        |1                          +++++++++++++++++++++++                          ||||     Flow      ||||                          +++++++++++++++++++++++                         Figure 2: Calendar Queue   In any event, a subqueue contains the traffic for a point in time or   a point in sequence, and data is sent from each subqueue in   succession.  If subqueues are associated with time, an interesting   end case develops: if the system is draining a given subqueue and the   time of the next subqueue arrives, what should the system do?  OneBaker & Pan                   Informational                     [Page 8]

RFC 7806            On Queuing, Marking, and Dropping         April 2016   potentially valid line of reasoning would have it continue delivering   the data in the present queue on the assumption that it will likely   trade off for time in the next.  Another potentially valid line of   reasoning would have it discard any waiting data in the present queue   and move to the next.2.2.4.  Work-Conserving Models and Stochastic Fairness Queuing   Stochastic Fairness Queuing [SFQ] is an example of a work-conserving   algorithm.  This algorithm measures packets and considers a "flow" to   be an equivalence class of traffic defined by a hashing algorithm   over the source and destination IPv4 addresses.  As packets arrive,   the enqueue method performs the indicated hash and places the packet   into the indicated subqueue.  The dequeue method operates as   described inSection 2.2.2; subqueues are inspected in round-robin   sequence and a packet is removed if they contain one or more packets.   The Deficit Round Robin [DRR] model modifies the quanta to bytes and   deals with variable length packets.  A subqueue descriptor contains a   waiting quantum (the amount intended to be dequeued on the previous   dequeue attempt that was not satisfied), a per-round quantum (the   subqueue is intended to dequeue a certain number of bytes each   round), and a maximum to permit (some multiple of the MTU).  In each   dequeue attempt, the dequeue method sets the waiting quantum to the   smaller of the maximum quantum and the sum of the waiting and   incremental quantum.  It then dequeues up to the waiting quantum (in   bytes) of packets in the queue and reduces the waiting quantum by the   number of bytes dequeued.  Since packets will not normally be exactly   the size of the quantum, some dequeue attempts will dequeue more than   others, but they will over time average the incremental quantum per   round if there is data present.   [SFQ] and [DRR] could be implemented as described inSection 2.2.3.   The weakness of a classical WRR approach is the search time expended   inspecting and not choosing sub-queues that contain no data or not   enough to trigger a transmission from them.2.2.5.  Non-Work-Conserving Models and Virtual Clock   Virtual Clock [VirtualClock] is an example of a non-work-conserving   algorithm.  It is trivially implemented as described inSection 2.2.3.  It associates buckets with intervals in time that   have durations on the order of microseconds to tens of milliseconds.   Each flow is assigned a rate in bytes per interval.  The flow entry   maintains a point in time the "next" packet in the flow should be   scheduled.Baker & Pan                   Informational                     [Page 9]

RFC 7806            On Queuing, Marking, and Dropping         April 2016   On enqueue, the method determines whether the "next schedule" time is   "in the past"; if so, the packet is scheduled "now", and if not, the   packet is scheduled at that time.  It then calculates the new "next   schedule" time as the current "next schedule" time plus the length of   the packet divided by the rate.  If the resulting time is also in the   past, the "next schedule" time is set to "now"; otherwise, it is set   to the calculated time.  As noted inSection 2.2.3, there is an   interesting point regarding "too much time in the future"; if a   packet is scheduled too far into the future, it may be marked or   dropped in the AQM procedure, and if it runs beyond the end of the   queuing system, may be defensively tail dropped.   On dequeue, the bucket associated with the time "now" is inspected.   If it contains a packet, the packet is dequeued and transmitted.  If   the bucket is empty and the time for the next bucket has not arrived,   the system waits, even if there is a packet in the next bucket.  As   noted inSection 2.2.3, there is an interesting point regarding the   queue associated with "now".  If a subsequent bucket, even if it is   actually empty, would be delayed by the transmission of a packet, one   could imagine marking the packet Explicit Congestion Notification -   Congestion Experienced (ECN-CE) [RFC3168] [RFC6679] or dropping the   packet.3.  Queuing, Marking, and Dropping   Queuing, marking, and dropping are integrated in any system that has   a queue.  If nothing else, as memory is finite, a system has to drop   as discussed in Sections2.2.3 and2.2.5 in order to protect itself.   However, host transports interpret drops as signals, so AQM   algorithms use that as a mechanism to signal.   It is useful to think of the effects of queuing as a signal as well.   The receiver sends acknowledgements as data is received, so the   arrival of acknowledgements at the sender paces the sender at   approximately the average rate it is able to achieve through the   network.  This is true even if the sender keeps an arbitrarily large   amount of data stored in network queues and is the basis for delay-   based congestion control algorithms.  So, delaying a packet   momentarily in order to permit another session to improve its   operation has the effect of signaling a slightly lower capacity to   the sender.Baker & Pan                   Informational                    [Page 10]

RFC 7806            On Queuing, Marking, and Dropping         April 20163.1.  Queuing with Tail Mark/Drop   In the default case in which a FIFO queue is used with defensive tail   drop only, the effect is to signal to the sender in two ways:   o  Ack clocking, which involves pacing the sender to send at      approximately the rate it can deliver data to the receiver; and   o  Defensive loss, which is when a sender sends faster than available      capacity (such as by probing network capacity when fully utilizing      that capacity) and overburdens a queue.3.2.  Queuing with CoDel Mark/Drop   In any case wherein a queuing algorithm is used along with CoDel   [DELAY-AQM], the sequence of events is that a packet is time stamped,   enqueued, dequeued, compared to a subsequent reading of the clock,   and then acted on, whether by dropping it, marking and forwarding it,   or simply forwarding it.  This is to say that the only drop algorithm   inherent in queuing is the defensive drop when the queue's resources   are overrun.  However, the intention of marking or dropping is to   signal to the sender much earlier when a certain amount of delay has   been observed.  In a FIFO+CoDel, Virtual Clock+CoDel, or FlowQueue-   Codel [FQ-CODEL] implementation, the queuing algorithm is completely   separate from the AQM algorithm.  Using them in series results in   four signals to the sender:   o  Ack clocking, which involves pacing the sender to send at      approximately the rate it can deliver data to the receiver through      a queue;   o  Lossless signaling that a certain delay threshold has been      reached, if ECN [RFC3168] [RFC6679] is in use;   o  Intentional signaling via loss that a certain delay threshold has      been reached, if ECN is not in use; and   o  Defensive loss, which is when a sender sends faster than available      capacity (such as by probing network capacity when fully utilizing      that capacity) and overburdens a queue.3.3.  Queuing with RED or PIE Mark/Drop   In any case wherein a queuing algorithm is used along with PIE   [AQM-PIE], Random Early Detection (RED) [RFC7567], or other such   algorithms, the sequence of events is that a queue is inspected, a   packet is dropped, marked, or left unchanged, enqueued, dequeued,   compared to a subsequent reading of the clock, and then forwarded on.Baker & Pan                   Informational                    [Page 11]

RFC 7806            On Queuing, Marking, and Dropping         April 2016   This is to say that the AQM Mark/Drop Algorithm precedes enqueue; if   it has not been effective and as a result the queue is out of   resources anyway, the defensive drop algorithm steps in, and failing   that, the queue operates in whatever way it does.  Hence, in a   FIFO+PIE, SFQ+PIE, or Virtual Clock+PIE implementation, the queuing   algorithm is again completely separate from the AQM algorithm.  Using   them in series results in four signals to the sender:   o  Ack clocking, which involves pacing the sender to send at      approximately the rate it can deliver data to the receiver through      a queue;   o  Lossless signaling that a queue depth that corresponds to a      certain delay threshold has been reached, if ECN is in use;   o  Intentional signaling via loss that a queue depth that corresponds      to a certain delay threshold has been reached, if ECN is not in      use; and   o  Defensive loss, which is when a sender sends faster than available      capacity (such as by probing network capacity when fully utilizing      that capacity) and overburdens a queue.4.  Conclusion   To summarize, inSection 2, implementation approaches for several   classes of queuing algorithms were explored.  Queuing algorithms such   as SFQ, Virtual Clock, and FlowQueue-Codel [FQ-CODEL] have value in   the network in that they delay packets to enforce a rate upper bound   or to permit competing flows to compete more effectively.  ECN   marking and loss are also useful signals if used in a manner that   enhances TCP / Steam Control Transmission Protocol (SCTP) operation   or restrains unmanaged UDP data flows.   Conceptually, queuing algorithms and mark/drop algorithms operate in   series (as discussed inSection 3), not as a single algorithm.  The   observed effects differ: defensive loss protects the intermediate   system and provides a signal, AQM mark/drop works to reduce mean   latency, and the scheduling of flows works to modify flow interleave   and acknowledgement pacing.  Certain features like flow isolation are   provided by fair-queuing-related designs but are not the effect of   the mark/drop algorithm.   There is value in implementing and coupling the operation of both   queuing algorithms and queue management algorithms, and there is   definitely interesting research in this area, but specifications,   measurements, and comparisons should decouple the different   algorithms and their contributions to system behavior.Baker & Pan                   Informational                    [Page 12]

RFC 7806            On Queuing, Marking, and Dropping         April 20165.  Security Considerations   This memo adds no new security issues; it observes implementation   strategies for Diffserv implementation.6.  References6.1.  Normative References   [RFC2475]   Blake, S., Black, D., Carlson, M., Davies, E., Wang, Z.,               and W. Weiss, "An Architecture for Differentiated               Services",RFC 2475, DOI 10.17487/RFC2475, December 1998,               <http://www.rfc-editor.org/info/rfc2475>.6.2.  Informative References   [AQM-PIE]   Pan, R., Natarajan, P., and F. Baker, "PIE: A Lightweight               Control Scheme To Address the Bufferbloat Problem", Work               in Progress,draft-ietf-aqm-pie-06, April 2016.   [CalendarQueue]               Brown, R., "Calendar queues: a fast 0(1) priority queue               implementation for the simulation event set problem",               Communications of the ACM Volume 21, Issue 10, pp.               1220-1227, DOI 10.1145/63039.63045, October 1988,               <http://dl.acm.org/citation.cfm?id=63045>.   [Deadline]  Kruk, L., Lohoczky, J., Ramanan, K., and S. Shreve,               "Heavy Traffic Analysis For EDF Queues With Reneging",               The Annals of Applied Probability Volume 21, Issue No. 2,               pp. 484-545, DOI 10.1214/10-AAP681, 2011,               <http://www.math.cmu.edu/users/shreve/Reneging.pdf>.   [DELAY-AQM] Nichols, K., Jacobson, V., McGregor, A., and J. Iyengar,               "Controlled Delay Active Queue Management", Work in               Progress,draft-ietf-aqm-codel-03, March 2016.   [DRR]       Shreedhar, M. and G. Varghese, "Efficient fair queuing               using deficit round-robin", IEEE/ACM Transactions on               Networking Volume 4, Issue 3, pp. 375-385,               DOI 10.1109/90.502236, June 1996,               <http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=502236>.   [FQ-CODEL]  Hoeiland-Joergensen, T., McKenney, P., Taht, D., Gettys,               J., and E. Dumazet, "The FlowQueue-CoDel Packet Scheduler               and Active Queue Management Algorithm", Work in Progress,draft-ietf-aqm-fq-codel-06, March 2016.Baker & Pan                   Informational                    [Page 13]

RFC 7806            On Queuing, Marking, and Dropping         April 2016   [GPS]       Demers, A., University of California, Berkeley, and Xerox               PARC, "Analysis and Simulation of a Fair Queueing               Algorithm", ACM SIGCOMM Computer Communication               Review, Volume 19, Issue 4, pp. 1-12,               DOI 10.1145/75247.75248, September 1989,               <http://blizzard.cs.uwaterloo.ca/keshav/home/Papers/data/89/fq.pdf>.   [NoFair]    Briscoe, B., "Flow rate fairness: dismantling a               religion", ACM SIGCOMM Computer Communication               Review, Volume 37, Issue 2, pp. 63-74,               DOI 10.1145/1232919.1232926, April 2007,               <http://dl.acm.org/citation.cfm?id=1232926>.   [RFC970]    Nagle, J., "On Packet Switches With Infinite Storage",RFC 970, DOI 10.17487/RFC0970, December 1985,               <http://www.rfc-editor.org/info/rfc970>.   [RFC2990]   Huston, G., "Next Steps for the IP QoS Architecture",RFC 2990, DOI 10.17487/RFC2990, November 2000,               <http://www.rfc-editor.org/info/rfc2990>.   [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,               <http://www.rfc-editor.org/info/rfc3168>.   [RFC3390]   Allman, M., Floyd, S., and C. Partridge, "Increasing               TCP's Initial Window",RFC 3390, DOI 10.17487/RFC3390,               October 2002, <http://www.rfc-editor.org/info/rfc3390>.   [RFC5690]   Floyd, S., Arcia, A., Ros, D., and J. Iyengar, "Adding               Acknowledgement Congestion Control to TCP",RFC 5690,               DOI 10.17487/RFC5690, February 2010,               <http://www.rfc-editor.org/info/rfc5690>.   [RFC6057]   Bastian, C., Klieber, T., Livingood, J., Mills, J., and               R.  Woundy, "Comcast's Protocol-Agnostic Congestion               Management System",RFC 6057, DOI 10.17487/RFC6057,               December 2010, <http://www.rfc-editor.org/info/rfc6057>.   [RFC6679]   Westerlund, M., Johansson, I., Perkins, C., O'Hanlon, P.,               and K. Carlberg, "Explicit Congestion Notification (ECN)               for RTP over UDP",RFC 6679, DOI 10.17487/RFC6679, August               2012, <http://www.rfc-editor.org/info/rfc6679>.Baker & Pan                   Informational                    [Page 14]

RFC 7806            On Queuing, Marking, and Dropping         April 2016   [RFC6928]   Chu, J., Dukkipati, N., Cheng, Y., and M. Mathis,               "Increasing TCP's Initial Window",RFC 6928,               DOI 10.17487/RFC6928, April 2013,               <http://www.rfc-editor.org/info/rfc6928>.   [RFC7141]   Briscoe, B. and J. Manner, "Byte and Packet Congestion               Notification",BCP 41,RFC 7141, DOI 10.17487/RFC7141,               February 2014, <http://www.rfc-editor.org/info/rfc7141>.   [RFC7567]   Baker, F., Ed. and G. Fairhurst, Ed., "IETF               Recommendations Regarding Active Queue Management",BCP 197,RFC 7567, DOI 10.17487/RFC7567, July 2015,               <http://www.rfc-editor.org/info/rfc7567>.   [SFQ]       Mckenney, P., "Stochastic Fairness Queuing", Proceedings               of IEEE INFOCOM '90, Volume 2, pp. 733-740,               DOI 10.1109/INFCOM.1990.91316, June 1990,               <http://www2.rdrop.com/~paulmck/scalability/paper/sfq.2002.06.04.pdf>.   [VirtualClock]               Zhang, L., "VirtualClock: A New Traffic Control Algorithm               for Packet Switching Networks", Proceedings of the ACM               Symposium on Communications Architectures and               Protocols, Volume 20, DOI 10.1145/99508.99525, September               1990, <http://dl.acm.org/citation.cfm?id=99508.99525>.Acknowledgements   This note grew out of, and is in response to, mailing list   discussions in AQM, in which some have pushed an algorithm to compare   to AQM marking and dropping algorithms, but which includes flow   queuing.Baker & Pan                   Informational                    [Page 15]

RFC 7806            On Queuing, Marking, and Dropping         April 2016Authors' Addresses   Fred Baker   Cisco Systems   Santa Barbara, California  93117   United States   Email: fred@cisco.com   Rong Pan   Cisco Systems   Milpitas, California  95035   United States   Email: ropan@cisco.comBaker & Pan                   Informational                    [Page 16]