Internet Engineering Task Force (IETF) G. White
Request for Comments: 8034 CableLabs
Category: Informational R. Pan
ISSN: 2070-1721 Cisco Systems
December 2016
February 2017
Active Queue Management (AQM) Based on Proportional Integral Controller
Enhanced (PIE) for Data-Over-Cable Service Interface Specifications
(DOCSIS) Cable Modems
Abstract
Cable modems based on Data-Over-Cable Service Interface
Specifications (DOCSIS) provide broadband Internet access to over one
hundred million users worldwide. In some cases, the cable modem
connection is the bottleneck (lowest speed) link between the customer
and the Internet. 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 introduces
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 have also been amended to contain similar
requirements. This document describes the requirements on AQM that
apply to DOCSIS equipment, including a description of the "DOCSIS-
PIE" algorithm that is required on DOCSIS 3.1 cable modems.
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; see Section 2 of RFC 7841.
Information about the current status of this document, any errata,
and how to provide feedback on it may be obtained at
http://www.rfc-editor.org/info/rfc8034.
Copyright Notice
Copyright (c) 2016 2017 IETF Trust and the persons identified as the
document authors. All rights reserved.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Overview of DOCSIS AQM Requirements . . . . . . . . . . . . . 3
3. The DOCSIS MAC Layer and Service Flows . . . . . . . . . . . 3
4. DOCSIS-PIE vs. PIE . . . . . . . . . . . . . . . . . . . . . 5
4.1. Latency Target . . . . . . . . . . . . . . . . . . . . . 5
4.2. Departure Rate Estimation . . . . . . . . . . . . . . . . 5
4.3. Enhanced Burst Protection . . . . . . . . . . . . . . . . 6
4.4. Expanded Auto-Tuning Range . . . . . . . . . . . . . . . 7
4.5. Trigger for Exponential Decay . . . . . . . . . . . . . . 7
4.6. Drop Probability Scaling . . . . . . . . . . . . . . . . 7 8
4.7. Support for Explicit Congestion Notification . . . . . . 8
5. Implementation Guidance . . . . . . . . . . . . . . . . . . . 8
6. Security Considerations . . . . . . . . . . . . . . . . . . . 9
7. References . . . . . . . . . . . . . . . . . . . . . . . . . 9
7.1. Normative References . . . . . . . . . . . . . . . . . . 9
7.2. Informative References . . . . . . . . . . . . . . . . . 9
Appendix A. DOCSIS-PIE Algorithm Definition . . . . . . . . . . 10
A.1. DOCSIS-PIE AQM Constants and Variables . . . . . . . . . 10
A.1.1. Configuration Parameters . . . . . . . . . . . . . . 10
A.1.2. Constant Values . . . . . . . . . . . . . . . . . . . 10
A.1.3. Variables . . . . . . . . . . . . . . . . . . . . . . 11
A.1.4. Public/System Functions . . . . . . . . . . . . . . . 11
A.2. DOCSIS-PIE AQM Control Path . . . . . . . . . . . . . . . 11 12
A.3. DOCSIS-PIE AQM Data Path . . . . . . . . . . . . . . . . 14
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 15
1. Introduction
A recent resurgence of interest in active queue management, arising
from a recognition of the inadequacies of drop-tail queuing in the
presence of loss-based congestion control algorithms, has resulted in
the development of new algorithms that appear to provide very good
congestion feedback to current TCP algorithms, while also having
operational simplicity and low complexity. One of these algorithms
has been selected as a requirement for cable modems built according
to the DOCSIS 3.1 specification [DOCSIS_3.1]. The Data-Over-Cable
Service Interface Specifications (DOCSIS) define the broadband
technology deployed worldwide for Ethernet and IP service over hybrid
fiber-coaxial cable systems. The most recent revision of the DOCSIS
technology, version 3.1, was originally published in October 2013 and
provides support for up to 10 Gbps downstream (toward the customer)
and 1 Gbps upstream (from the customer) capacity over existing cable
networks. Previous versions of the DOCSIS technology did not contain
requirements for AQM. This document outlines the high-level AQM
requirements for DOCSIS systems, discusses some of the salient
features of the DOCSIS Media Access Control (MAC) layer, and
describes the DOCSIS-PIE algorithm -- largely by comparing it to its
progenitor, the PIE algorithm [RFC8033].
2. 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) AQM algorithm [RFC8033]. This specific
variant is provided for reference in Appendix A, and simulation
results comparing it to drop-tail queuing and other AQM options are
given in [CommMag] and [DOCSIS-AQM]. In addition, CableLabs' DOCSIS
3.0 specification [DOCSIS_3.0] has been 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
(i.e., from the customer to the Internet).
Both specifications also include requirements (mandatory in DOCSIS
3.1 and recommended in DOCSIS 3.0) that the Cable Modem Termination
System (CMTS) implement AQM for downstream traffic; however, no
specific algorithm is defined for downstream use.
3. The DOCSIS MAC Layer and Service Flows
The DOCSIS Media Access Control (sub-)layer provides tools for
configuring differentiated Quality of Service (QoS) for different
applications by the use of Packet Classifiers and Service Flows.
Each Service Flow has an associated 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, and 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 needed) 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.
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 upstream Service Flows and at
least that many Packet Classifiers. Similarly, the CMTS supports
multiple downstream Service Flows and multiple Packet Classifiers per
cable modem.
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:
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.
4. 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 [RFC8033]. These
differences are described in the following subsections.
4.1. Latency Target
The latency target (a.k.a. delay reference) is a key parameter that
affects, among other things, the trade-off in performance between
latency-sensitive applications and bulk TCP applications. Via
simulation studies, a value of 10 ms was identified as providing a
good balance of performance. However, it is recognized that there
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.
4.2. 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 3.
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 the Peak Traffic Rate and Maximum Sustained Traffic Rate will
occur. Compare this to the PIE estimator, which would be simply
reacting to (and smoothing its estimate of) those rate transitions
after the fact.
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 at 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.
4.3. Enhanced Burst Protection
The PIE algorithm [RFC8033] has two states: INACTIVE and ACTIVE.
During the INACTIVE state, AQM packet drops are suppressed. The
algorithm transitions to the ACTIVE state when the queue exceeds 1/3
of the buffer size. Upon transition to the ACTIVE state, PIE
includes a burst protection feature in which the AQM packet drops are
suppressed for the first 150 ms. Since DOCSIS-PIE is predominantly
deployed on consumer broadband connections, a more sophisticated
burst protection was developed to provide better performance in the
presence of a single TCP session.
Where the PIE algorithm has two states, DOCSIS-PIE has three. The
INACTIVE and ACTIVE states in DOCSIS-PIE are identical to those
states in PIE. The QUIESCENT state is a transitional state between
INACTIVE and ACTIVE. The DOCSIS-PIE algorithm transitions from
INACTIVE to QUIESCENT when the queue exceeds 1/3 of the buffer size.
In the QUIESCENT state, packet drops are immediately enabled, and
upon the first packet drop, the algorithm transitions to the ACTIVE
state (where drop probability is reset to zero for the 150 ms
duration of the burst protection as in PIE). From the ACTIVE state,
the algorithm transitions to QUIESCENT if the drop probability has
decayed to zero and the queuing latency has been less than half of
the LATENCY_TARGET for two update intervals. The algorithm then
fully resets to the INACTIVE state if this "quiet" condition exists
for the duration of the BURST_RESET_TIMEOUT (1 second). One end
result of the addition of the QUIESCENT state is that a single packet
drop can occur relatively early on during an initial burst, whereas
all drops would be suppressed for at least 150 ms of the burst
duration in PIE. The other end result is that if traffic stops and
then resumes within 1 second, DOCSIS-PIE can directly drop a single
packet and then re-enter burst protection, whereas PIE would require
that the buffer exceed 1/3 full.
4.4. Expanded Auto-Tuning Range
The PIE algorithm scales the PI Proportional and Integral coefficients
based on the current drop probability. The DOCSIS-PIE algorithm
extends this scaling to cover values of drop probability greater than
1, which can occur as a
wider range result of the drop probability. probability scaling
function described in Section 4.6. As an example, if a flood of non-
responsive 64-byte packets were to arrive at a rate that is twice the
departure rate, the DOCSIS-PIE steady-state condition would be to
drop 50% of these packets, which implies that drop probability would
have the value of 8.00.
4.5. 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 the buffer due to the request-grant
latency even if the link is effectively idle. As a result, the
buffer may 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 5 ms * Peak
Traffic Rate.
4.6. Drop Probability Scaling
The DOCSIS-PIE algorithm scales the calculated drop probability based
on the ratio of the packet size to a constant value of 1024 bytes
(representing approximate average packet size). While [RFC7567] in
general recommends against this type of scaling, we note that DOCSIS-
PIE is expected to be used predominantly to manage upstream queues in
residential broadband deployments, where we believe the benefits
outweigh the disadvantages. As a safeguard to prevent a flood of
small packets from starving flows that use larger packets, DOCSIS-PIE
limits the scaled probability to a defined maximum value of 0.85.
4.7. Support for Explicit Congestion Notification
DOCSIS-PIE does not include support for Explicit Congestion
Notification (ECN). Cable modems are essentially IEEE 802.1d
Ethernet bridges and so are not designed to modify IP header fields.
Additionally, the packet-processing pipeline in a cable modem is
commonly implemented in hardware. As a result, introducing support
for ECN would have engendered engender a more significant redesign of cable modem data paths,
path hardware, and implementations would have been be difficult or impossible to modify in the
future. At the time of the development of DOCSIS-PIE, which
coincided with the development of modem chip designs, the benefits of
ECN marking relative to packet drop were considered to be relatively
minor; there was considerable discussion about differential treatment
of ECN-capable packets in the AQM drop/
mark drop/mark decision, and there were
some initial suggestions that a new ECN approach was needed. Due to
this uncertainty, we chose not to include support for ECN.
5. Implementation Guidance
The AQM space is an evolving one, and it is expected that continued
research in this field may result in improved algorithms in the
future.
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.
6. Security Considerations
This document describes an active queue management algorithm based on
[RFC8033] for implementation in DOCSIS cable modem devices. This
algorithm introduces no specific security exposures.
7. References
7.1. Normative References
[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, December 2016,
<http://www.rfc-editor.org/info/rfc8033>.
7.2. Informative References
[CommMag] White, G., "Active queue management in DOCSIS 3.1
networks", IEEE Communications Magazine vol. 53, no. 3,
pp. 126-132, DOI 10.1109/MCOM.2015.7060493, March 2015.
[DOCSIS-AQM]
White, G., "Active Queue Management in DOCSIS 3.x Cable
Modems", May 2014, <http://www.cablelabs.com/wp-
content/uploads/2014/06/DOCSIS-AQM_May2014.pdf>.
[DOCSIS_3.0]
CableLabs, "MAC and Upper Layer Protocols Interface
Specification", DOCSIS 3.0, December 2015,
<http://www.cablelabs.com/wp-content/uploads/specdocs/
CM-SP-MULPIv3.0-I29-151210.pdf>. January 2017,
<https://apps.cablelabs.com/specification/CM-SP-
MULPIv3.0>.
[DOCSIS_3.1]
CableLabs, "MAC and Upper Layer Protocols Interface
Specification", DOCSIS 3.1, December 2015, June 2016,
<http://www.cablelabs.com/wp-content/uploads/specdocs/
CM-SP-MULPIv3.1-I08-151210.pdf>.
CM-SP-MULPIv3.1-I09-160602.pdf>.
[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>.
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 -- block, a function that occurs on each packet enqueue: enqueue
that implements a per-packet drop decision based on the drop
probability.
It is desirable 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/second
o MSR. Service Flow configured Maximum Sustained Traffic Rate,
expressed in bytes/second
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 BURST_RESET_TIMEOUT = 1 second
o MAX_BURST = 142 ms (150 ms - 8 ms (update error))
o MEAN_PKTSIZE = 1024 bytes
o MIN_PKTSIZE = 64 bytes
o PROB_LOW = 0.85
o PROB_HIGH = 8.5
o LATENCY_LOW = 5 ms
o LATENCY_HIGH = 200 ms
A.1.3. Variables
o drop_prob_. The current packet drop probability
o accu_prob_. Accumulated drop probability 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 aqm_state_. AQM activity state encoding 3 states:
INACTIVE - Queue staying below 1/3 full, suppress AQM drops
QUIESCENT - Transition state
ACTIVE - Normal AQM drops (after burst protection period)
o queue_. Holds the pending packets
A.1.4. Public/System Functions
o drop(packet). Drops/discards a packet
o random(). Returns a uniform random value 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
Maximum Sustained Traffic Rate token bucket
o packet.size(). Returns size of packet
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 (16 ms)
================
// Initialization function
control_path_init() {
drop_prob_ = 0;
qdelay_old_ = 0;
burst_reset_ = 0;
aqm_state_ = INACTIVE;
}
// 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;
burst_allowance_ = max(0, burst_allowance_ - INTERVAL);
} 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) {
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;
/* some special cases */
if (qdelay < LATENCY_LOW && qdelay_old_ < LATENCY_LOW) {
drop_prob_ *= 0.98; // exponential decay
} else if (qdelay > LATENCY_HIGH) {
drop_prob_ += 0.02; // ramp up quickly
}
drop_prob_ = max(0, drop_prob_);
drop_prob_ = min(drop_prob_, \
PROB_LOW * MEAN_PKTSIZE/MIN_PKTSIZE);
}
// Check if all is quiet
quiet = (qdelay < 0.5 * LATENCY_TARGET)
&& (qdelay_old_ < 0.5 * LATENCY_TARGET)
&& (drop_prob_ == 0)
&& (burst_allowance_ == 0);
// Update AQM state based on quiet or !quiet
if ((aqm_state_ == ACTIVE) && quiet) {
aqm_state_ = QUIESCENT;
burst_reset_ = 0;
} else if (aqm_state_ == QUIESCENT) {
if (quiet) {
burst_reset_ += INTERVAL ;
if (burst_reset_ > BURST_RESET_TIMEOUT) {
burst_reset_ = 0;
aqm_state_ = INACTIVE;
}
} else {
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 still in burst protection, suppress AQM drops
if (burst_allowance_ > 0) {
return FALSE;
}
// if drop_prob_ goes to zero, clear accu_prob_
if (drop_prob_ == 0) {
accu_prob_ = 0;
}
if (aqm_state_ == INACTIVE) {
if (queue_.byte_length() < BUFFER_SIZE/3) {
// if queue is still small, stay in
// INACTIVE state and suppress AQM drops
return FALSE;
} else {
// otherwise transition to QUIESCENT state
aqm_state_ = QUIESCENT;
}
}
//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);
accu_prob_ += p1;
// Suppress AQM drops in certain situations
if ( (qdelay_old_ < 0.5 * LATENCY_TARGET && drop_prob_ < 0.2)
|| (queue_.byte_length() <= 2 * MEAN_PKTSIZE) ) {
return FALSE;
}
if (accu_prob_ < PROB_LOW) { // avoid dropping too fast due
return FALSE; // to bad luck of coin tosses...
} else if (accu_prob_ >= PROB_HIGH) { // ...and avoid dropping
drop = TRUE; // too slowly
} else { //Random drop
double u = random(); // 0 ~ 1
if (u > p1)
return FALSE;
else
drop = TRUE;
}
// At this point, drop == TRUE, so packet will be dropped.
// Reset accu_prob_
accu_prob_ = 0;
// If in QUIESCENT state, packet drop triggers
// ACTIVE state and start of burst protection
if (aqm_state_ == QUIESCENT) {
aqm_state_ = ACTIVE;
burst_allowance_ = MAX_BURST;
}
return TRUE;
}
Authors' Addresses
Greg White
CableLabs
858 Coal Creek Circle
Louisville, CO 80027-9750
United States of America
Email: g.white@cablelabs.com
Rong Pan
Cisco Systems
510 McCarthy Blvd
Milpitas, CA 95134
United States of America
Email: ropan@cisco.com