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Active Queue Management and Packet Scheduling (aqm)             G. White
Internet-Draft                                                 CableLabs
Intended status: Informational                                    R. Pan
Expires: August 18, 2014                                   Cisco Systems
                                                       February 14, 2014


                A PIE-Based AQM for DOCSIS Cable Modems
                     draft-white-aqm-docsis-pie-00

Abstract

   DOCSIS cable modems provide broadband Internet access to over one
   hundred million users worldwide.  They are commonly positioned at the
   head of the bottleneck link for traffic in the upstream direction
   (from the customer), and as a result, the impact of buffering and
   bufferbloat in the cable modem can have a significant effect on user
   experience.  The CableLabs DOCSIS 3.1 specification includes
   requirements for cable modems to support an Active Queue Management
   (AQM) algorithm that is intended to alleviate the impact that
   buffering has on latency sensitive traffic, while preserving bulk
   throughput performance.  In addition, the CableLabs DOCSIS 3.0
   specifications are being amended to contain similar requirements.

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
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at http://datatracker.ietf.org/drafts/current/.

   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on August 18, 2014.

Copyright Notice

   Copyright (c) 2014 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents



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   (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.

Table of Contents

   1.  Overview of DOCSIS AQM Requirements . . . . . . . . . . . . .   2
   2.  The DOCSIS MAC Layer and Service Flows  . . . . . . . . . . .   3
   3.  DOCSIS-PIE vs. PIE  . . . . . . . . . . . . . . . . . . . . .   4
     3.1.  Latency Target  . . . . . . . . . . . . . . . . . . . . .   4
     3.2.  Departure rate estimation . . . . . . . . . . . . . . . .   5
     3.3.  Packet drop de-randomization  . . . . . . . . . . . . . .   6
     3.4.  Enhanced burst protection . . . . . . . . . . . . . . . .   6
     3.5.  Expanded auto-tuning range  . . . . . . . . . . . . . . .   6
     3.6.  Trigger for exponential decay . . . . . . . . . . . . . .   6
     3.7.  16ms update interval  . . . . . . . . . . . . . . . . . .   7
   4.  Implementation Guidance . . . . . . . . . . . . . . . . . . .   7
   5.  References  . . . . . . . . . . . . . . . . . . . . . . . . .   7
   Appendix A.  DOCSIS-PIE Algorithm definition  . . . . . . . . . .   8
     A.1.  DOCSIS-PIE AQM Constants and Variables  . . . . . . . . .   8
       A.1.1.  Configuration parameters  . . . . . . . . . . . . . .   8
       A.1.2.  Constant values . . . . . . . . . . . . . . . . . . .   8
       A.1.3.  Variables . . . . . . . . . . . . . . . . . . . . . .   9
       A.1.4.  Public/system functions:  . . . . . . . . . . . . . .   9
     A.2.  DOCSIS-PIE AQM Control Path . . . . . . . . . . . . . . .  10
     A.3.  DOCSIS-PIE AQM Data Path  . . . . . . . . . . . . . . . .  12
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  13

1.  Overview of DOCSIS AQM Requirements

   CableLabs' DOCSIS 3.1 specification [DOCSIS_3.1] mandates that cable
   modems implement a specific variant of the Proportional Integral
   controller Enhanced (PIE) [I-D.pan-aqm-pie] active queue management
   algorithm.  This specific variant is provided for reference in
   Appendix A.  CableLabs' DOCSIS 3.0 specification [DOCSIS_3.0] is
   being amended to recommend that cable modems implement the same
   algorithm.  Both specifications allow that cable modems can
   optionally implement additional algorithms, that can then be selected
   for use by the operator via the modem's configuration file.

   These requirements on the cable modem apply to upstream
   transmissions.





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   Both specifications also include requirements (mandatory in DOCSIS
   3.1 and recommended in DOCSIS 3.0) that the Cable Modem Termination
   System (CMTS) implement active queue management for downstream
   traffic, however no specific algorithm is defined for downstream use.

2.  The DOCSIS MAC Layer and Service Flows

   The DOCSIS Media Access Control (sub-)layer provides tools for
   configuring differentiated Quality of Service for different
   applications by the use of Packet Classifiers and Service Flows.

   Each cable modem can be configured with multiple Packet Classifiers
   and Service Flows.  The maximum number of such entities that a cable
   modem supports is an implementation decision for the manufacturer,
   but modems typically support 16 or 32 Service Flows and at least that
   many Packet Classifiers.

   Each Service Flow has an associated Quality of Service (QoS)
   parameter set that defines the treatment of the packets that traverse
   the Service Flow.  These parameters include (for example) Minimum
   Reserved Traffic Rate, Maximum Sustained Traffic Rate, Peak Traffic
   Rate, Maximum Traffic Burst, Traffic Priority.  Each upstream Service
   Flow corresponds to a queue in the cable modem, and each downstream
   Service Flow corresponds to a queue in the CMTS.  The DOCSIS AQM
   requirements mandate that the CM and CMTS implement the AQM algorithm
   (and allow it to be disabled if need be) on each Service Flow queue
   independently.

   Packet Classifiers can match packets based upon several fields in the
   packet/frame headers including the Ethernet header, IP header, and
   TCP/UDP header.  Matched packets are then queued in the associated
   Service Flow queue.

   It is typical that upstream and downstream Service Flows used for
   broadband Internet access are configured with a Maximum Sustained
   Traffic Rate.  This QoS parameter rate-shapes the traffic onto the
   DOCSIS link, and is the main parameter that defines the service
   offering.  Additionally, it is common that upstream and downstream
   Service Flows are configured with a Maximum Traffic Burst and a Peak
   Traffic Rate.  These parameters allow the service to burst at a
   higher (sometimes significantly higher) rate than is defined in the
   Maximum Sustained Traffic Rate for the amount of bytes configured in
   Maximum Traffic Burst, as long as the long-term average data rate
   remains at or below the Maximum Sustained Traffic Rate.

   Mathematically, what is enforced is that the traffic placed on the
   DOCSIS link in the time interval (t1,t2) complies with the following
   rate shaping equations:



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      TxBytes(t1,t2) <= (t2-t1)*R/8 + B

      TxBytes(t1,t2) <= (t2-t1)*P/8 + 1522

   for all values t2>t1, where:

      R = Maximum Sustained Traffic Rate (bps)

      P = Peak Traffic Rate (bps)

      B = Maximum Traffic Burst (bytes)

   The result of this configuration is that the link rate available to
   the Service Flow varies based on the pattern of load.  If the load
   that the Service Flow places on the link is less than the Maximum
   Sustained Traffic Rate, the Service Flow "earns" credit that it can
   then use (should the load increase) to burst at the Peak Traffic
   Rate.  This dynamic is important since these rate changes
   (particularly the decrease in data rate once the traffic burst credit
   is exhausted) can induce a step increase in buffering latency.

3.  DOCSIS-PIE vs. PIE

   There are a number of differences between the version of the PIE
   algorithm that is mandated for cable modems in the DOCSIS
   specifications and the version described in [I-D.pan-aqm-pie].

   o  10 ms default latency target, configurable per service flow

   o  departure rate estimation

   o  packet drop de-randomization

   o  enhanced burst-protection

   o  expanded auto-tuning range

   o  trigger for exponential decay

   o  16ms update interval

3.1.  Latency Target

   The latency target (aka delay reference) is a key parameter that
   affects, among other things, the tradeoff in performance between
   latency-sensitive applications and bulk TCP applications.  Via
   simulation studies, a value of 10ms was identified as providing a
   good balance of performance.  However, it is recognized that there



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   may be service offerings for which this value doesn't provide the
   best performance balance.  As a result, this is provided as a
   configuration parameter that the operator can set independently on
   each upstream service flow.  If not explicitly set by the operator,
   the modem will use 10 ms as the default value.

3.2.  Departure rate estimation

   The PIE algorithm utilizes a departure rate estimator to track
   fluctuations in the egress rate for the queue and to generate a
   smoothed estimate of this rate for use in the drop probability
   calculation.  This estimator may be well suited to many link
   technologies, but is not ideal for DOCSIS upstream links for a number
   of reasons.

   First, the bursty nature of the upstream transmissions, in which the
   queue drains at line rate (up to ~100 Mbps for DOCSIS 3.0 and ~1 Gbps
   for DOCSIS 3.1) and then is blocked until the next transmit
   opportunity, results in the potential for inaccuracy in measurement,
   given that the PIE departure rate estimator starts each measurement
   during a transmission burst and ends each measurement during a
   (possibly different) transmission burst.  For example, in the case
   where the start and end of measurement occur within a single burst,
   the PIE estimator will calculate the egress rate to be equal to the
   line rate, rather than the average rate available to the modem.

   Second, the latency introduced by the DOCSIS request-grant mechanism
   can result in some further inaccuracy.  In typical conditions, the
   request-grant mechanism can add between ~4 ms and ~8 ms of latency to
   the forwarding of upstream traffic.  Within that range, the amount of
   additional latency that affects any individual data burst is
   effectively random, being influenced by the arrival time of the burst
   relative to the next request transmit opportunity, among other
   factors.

   Third, in the significant majority of cases, the departure rate,
   while variable, is controlled by the modem itself via the pair of
   token bucket rate shaping equations described in Section 2.
   Together, these two equations enforce a maximum sustained traffic
   rate, a peak traffic rate, and a maximum traffic burst size for the
   modem's requested bandwidth.  The implication of this is that the
   modem, in the significant majority of cases, will know precisely what
   the departure rate will be, and can predict exactly when transitions
   between peak rate and maximum sustained traffic rate will occur.
   This, as compared to the PIE estimator, which would be simply
   reacting to (and smoothing its estimate of) those rate transitions
   after the fact.




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   Finally, since the modem is already implementing the dual token
   bucket traffic shaper, it contains enough internal state to calculate
   predicted queuing delay with a minimum of computations.  Furthermore,
   these computations only need to be run every drop probability update
   interval, as opposed to the PIE estimator, which runs a similar
   number of computations on each packet dequeue event.

   For these reasons, the DOCSIS-PIE algorithm utilizes the
   configuration and state of the dual token bucket traffic shaper to
   translate queue depth into predicted queuing delay, rather than
   implementing the departure rate estimator defined in PIE.

3.3.  Packet drop de-randomization

   Similar to PIE, the DOCSIS-PIE algorithm utilizes a randomized drop
   mechanism driven by a calculated drop probability.  With an i.i.d.
   Bernoulli random number generator however, the localized probability
   of drop (over a small number of sequential packets) can vary
   radically from the desired drop probability.  In order to avoid these
   extreme excursions from the desired drop probability (p), DOCSIS-PIE
   enforces bounds as follows:

      minimum number of passed packets between drops = ceil((0.85/p)-1)

      maximum number of passed packets between drops = floor((8.5/p)+1)

3.4.  Enhanced burst protection

   The PIE algorithm contains a burst-protection feature which allows
   relatively short-lived (i.e. up to 150 ms) bursts of traffic to be
   enqueued (and thus create queuing latency) without the AQM triggering
   a packet loss.  In DOCSIS-PIE this is extended such that bursts that
   never occupy more than 1/3 of the buffer are protected even if they
   last longer than 150 ms.

3.5.  Expanded auto-tuning range

   The PIE algorithm scales the PI coefficients based on the current
   drop probability.  The DOCSIS-PIE algorithm extends this scaling to
   drop probabilities below 1e-4.

3.6.  Trigger for exponential decay

   The PIE algorithm includes a mechanism by which the drop probability
   is allowed to decay exponentially (rather than linearly) when it is
   detected that the buffer is empty.  In the DOCSIS case, recently
   arrived packets may reside in buffer due to the request-grant latency
   even if the link is effectively idle.  As a result, the buffer may



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   not be identically empty in the situations for which the exponential
   decay is intended.  To compensate for this, we trigger exponential
   decay when the buffer occupancy is less than 5ms * Peak Traffic Rate.

3.7.  16ms update interval

   PIE utilizes a 15ms update interval for the drop probability.  In the
   case of DOCSIS-PIE, we utilize 16ms as it aligns with an integer
   number of nominal MAP scheduling intervals (which are typically 2ms).

4.  Implementation Guidance

   The AQM space is an evolving one, and it is expected that continued
   research in this field may in the future result in improved
   algorithms.

   As part of defining the DOCSIS-PIE algorithm, we split the pseudocode
   definition into two components, a "data path" component and a
   "control path" component.  The control path component contains the
   packet drop probability update functionality, whereas the data path
   component contains the per-packet operations, including the drop
   decision logic.

   It is understood that some aspects of the cable modem implementation
   may be done in hardware, particularly functions that handle packet-
   processing.

   While the DOCSIS specifications don't mandate the internal
   implementation details of the cable modem, modem implementers are
   strongly advised against implementing the control path functionality
   in hardware.  The intent of this advice is to retain the possibility
   that future improvements in AQM algorithms can be accommodated via
   software updates to deployed devices.

5.  References

   [DOCSIS_3.0]
              CableLabs, "DOCSIS 3.0 MAC and Upper Layer Protocols
              Specification", November 2013, <http://www.cablelabs.com/
              wp-content/uploads/specdocs/
              CM-SP-MULPIv3.0-I23-131120.pdf>.

   [DOCSIS_3.1]
              CableLabs, "DOCSIS 3.1 MAC and Upper Layer Protocols
              Specification", October 2013, <http://www.cablelabs.com/
              wp-content/uploads/specdocs/
              CM-SP-MULPIv3.1-I01-131029.pdf>.




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   [I-D.pan-aqm-pie]
              Pan, R., Natarajan, P., Piglione, C., and M. Prabhu, "PIE:
              A Lightweight Control Scheme To Address the Bufferbloat
              Problem", draft-pan-aqm-pie-01 (work in progress),
              February 2014.

Appendix A.  DOCSIS-PIE Algorithm definition

   PIE defines two functions organized here into two design blocks:

   1.  Control path block, a periodically running algorithm that
       calculates a drop probability based on the estimated queuing
       latency and queuing latency trend.

   2.  Data path block, a function that occurs on each packet enqueue:
       per-packet drop decision based on the drop probability.

   It is desired to have the ability to update the Control path block
   based on operational experience with PIE deployments.

A.1.  DOCSIS-PIE AQM Constants and Variables

A.1.1.  Configuration parameters

   o  LATENCY_TARGET.  AQM Latency Target for this Service Flow

   o  PEAK_RATE.  Service Flow configured Peak Traffic Rate, expressed
      in Bytes/sec.

   o  MSR.  Service Flow configured Max. Sustained Traffic Rate,
      expressed in Bytes/sec.

   o  BUFFER_SIZE.  The size (in bytes) of the buffer for this Service
      Flow.

A.1.2.  Constant values

   o  A=0.25, B=2.5.  Weights in the drop probability calculation

   o  INTERVAL=16 ms.  Update interval for drop probability.

   o  DELAY_HIGH=200 ms.

   o  BURST_RESET_TIMEOUT = 1 s.

   o  MAX_BURST = 142 ms (150 ms-8 ms(update error))

   o  MEAN_PKTSIZE = 1024 bytes



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   o  MIN_PKTSIZE = 64 bytes

   o  PROB_LOW = 0.85

   o  PROB_HIGH = 8.5

   o  LATENCY_LOW = 5 ms

A.1.3.  Variables

   o  drop_prob_.  The current packet drop probability.

   o  accu_prob_. accumulated drop prob. since last drop

   o  qdelay_old_.  The previous queue delay estimate.

   o  burst_allowance_. Countdown for burst protection, initialize to 0

   o  burst_reset_. counter to reset burst

   o  burst_state_. Burst protection state encoding 3 states:

         NOBURST - no burst yet

         FIRST_BURST - first burst detected, no protection yet

         PROTECT_BURST - first burst detected, protecting burst if
         burst_allowance_ > 0

   o  queue_.  Holds the pending packets.

A.1.4.  Public/system functions:

   o  drop(packet).  Drops/discards a packet

   o  random().  Returns a uniform r.v. in the range 0 ~ 1

   o  queue_.is_full().  Returns true if queue_ is full

   o  queue_.byte_length().  Returns current queue_ length in bytes,
      including all MAC PDU bytes without DOCSIS MAC overhead

   o  queue_.enque(packet).  Adds packet to tail of queue_

   o  msrtokens().  Returns current token credits (in bytes) from the
      Max Sust.  Traffic Rate token bucket

   o  packet.size().  Returns size of packet



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A.2.  DOCSIS-PIE AQM Control Path

   The DOCSIS-PIE control path performs the following:

   o  Calls control_path_init() at service flow creation

   o  Calls calculate_drop_prob() at a regular INTERVAL (16ms)

   ================
   //  Initialization function
   control_path_init() {
       drop_prob_ = 0;
       qdelay_old_ = 0;
       burst_reset_ = 0;
       burst_state_ = NOBURST;
   }

   //  Background update, occurs every INTERVAL
   calculate_drop_prob() {

       if (queue_.byte_length() <= msrtokens()) {
           qdelay = queue_.byte_length() / PEAK_RATE;
       } else {
           qdelay = ((queue_.byte_length() - msrtokens()) / MSR \
                     +  msrtokens() / PEAK_RATE);
       }

       if (burst_allowance_ > 0) {
           drop_prob_ = 0;
       } else {
           p = A * (qdelay - LATENCY_TARGET) + \
               B * (qdelay - qdelay_old_);
           // Since A=0.25 & B=2.5, can be implemented
           // with shift and add

           if (drop_prob_ < 0.000001) {
               p /= 2048;
           } else if (drop_prob_ < 0.00001) {
               p /= 512;
           } else if (drop_prob_ < 0.0001) {
               p /= 128;
           } else if (drop_prob_ < 0.001) {
               p /= 32;
           } else if (drop_prob_ < 0.01) {
               p /= 8;
           } else if (drop_prob_ < 0.1) {
               p /= 2;
           } else if (drop_prob_ < 1) {



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               p /= 0.5;
           } else if (drop_prob_ < 10) {
               p /= 0.125;
           } else {
               p /= 0.03125;
           }

           if ((drop_prob_ >= 0.1) && (p > 0.02)) {
               p = 0.02;
           }
           drop_prob_ += p;

           /* for non-linear drop in prob */
           if (qdelay < LATENCY_LOW && qdelay_old_ < LATENCY_LOW) {
               drop_prob_ *= 0.98;    // (1-1/64) is sufficient
           } else if (qdelay > DELAY_HIGH) {
               drop_prob_ += 0.02;
           }

           drop_prob_ = max(0, drop_prob_);
           drop_prob_ = min(drop_prob_, \
                        PROB_LOW * MEAN_PKTSIZE/MIN_PKTSIZE);
       }

       if (burst_allowance_ < INTERVAL)
           burst_allowance_ = 0;
       else
           burst_allowance_ = burst_allowance_ - INTERVAL;

   // both old and new qdelay is well better than the
   // target and drop_prob_ == 0, time to clear burst tolerance
       if ((qdelay < 0.5 * LATENCY_TARGET)
           && (qdelay_old_ < 0.5 * LATENCY_TARGET)
           && (drop_prob_ == 0)
           && (burst_allowance_ == 0)){

           if (burst_state_ == PROTECT_BURST) {
               burst_state_ = FIRST_BURST;
               burst_reset_ = 0;

           } else if (burst_state_ == FIRST_BURST) {
               burst_reset_ += INTERVAL ;
               if (burst_reset_ > BURST_RESET_TIMEOUT) {
                   burst_reset_ = 0;
                   burst_state_ = NOBURST;
               }
           }
       } else if (burst_state_ == FIRST_BURST) {



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               burst_reset_ = 0;
       }

       qdelay_old_ = qdelay;

   }

A.3.  DOCSIS-PIE AQM Data Path

   The DOCSIS-PIE data path performs the following:

   o  Calls enque() in response to an incoming packet from the CMCI

   ================
   enque(packet) {

       if (queue_.is_full()) {
           drop(packet);
           accu_prob_ = 0;
       } else if (drop_early(packet, queue_.byte_length())) {
           drop(packet);
       } else {
           queue_.enque(packet);
       }
   }

   ////////////////
   drop_early(packet, queue_length) {
       if (burst_allowance_ > 0) {
           return FALSE;
       }

       if (drop_prob_ == 0) {
           accu_prob_ = 0;
       }

       if (burst_state_ == NOBURST) {                   //first burst?
           if (queue_.byte_length() < BUFFER_SIZE/3) {
               return FALSE;
           } else {
               burst_state_ = FIRST_BURST;             //burst detected
           }
       }

       //The CM can quantize packet.size to 64, 128, 256, 512, 768,
       // 1024, 1280, 1536, 2048 in the calculation below
       p1 = drop_prob_ * packet.size() / MEAN_PKTSIZE;
       p1 = min(p1, PROB_LOW);



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       accu_prob_ += p1;

      // If latency is low, don't drop packets
      if ( (qdelay_old_ < 0.5 * LATENCY_TARGET && drop_prob_ < 0.2)
               || (queue_.byte_length() <= 2 * MEAN_PKTSIZE) ) {
           return FALSE;
      }

       drop = TRUE;
       if (accu_prob_ < PROB_LOW) {  // avoid dropping too fast due
            drop = FALSE;            // to bad luck of coin tosses...
       } else if (accu_prob_ >= PROB_HIGH) { // ...and avoid droppping
           drop = TRUE;                      // too slowly
       } else {                        //Random drop
           double u = random();        // 0 ~ 1
           if (u > p1) {
              drop = FALSE;
           }
       }

       if (drop == FALSE) return FALSE;

       // In case of packet drop:
       accu_prob_ = 0;

       // Not protecting burst yet? Start protecting burst.
       // This will set the burst_allowance_ value, and
       // calculate_drop_prob() will decrement it.
       // Could implement this as a 150ms timer instead.
       if (burst_state_ == FIRST_BURST) {
           burst_state_ = PROTECT_BURST;
           burst_allowance_ = MAX_BURST;
       }
       return TRUE;
   }

Authors' Addresses

   Greg White
   CableLabs
   858 Coal Creek Circle
   Louisville, CO  80027-9750
   USA

   Email: g.white@cablelabs.com






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   Rong Pan
   Cisco Systems
   510 McCarthy Blvd
   Milpitas, CA  95134
   USA

   Email: ropan@cisco.com












































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