Internet DRAFT - draft-ietf-core-cocoa
draft-ietf-core-cocoa
CoRE Working Group C. Bormann
Internet-Draft Universitaet Bremen TZI
Intended status: Informational A. Betzler
Expires: August 25, 2018 Fundacio i2CAT
C. Gomez
I. Demirkol
Universitat Politecnica de Catalunya/Fundacio i2CAT
February 21, 2018
CoAP Simple Congestion Control/Advanced
draft-ietf-core-cocoa-03
Abstract
CoAP, the Constrained Application Protocol, needs to be implemented
in such a way that it does not cause persistent congestion on the
network it uses. The CoRE CoAP specification defines basic behavior
that exhibits low risk of congestion with minimal implementation
requirements. It also leaves room for combining the base
specification with advanced congestion control mechanisms with higher
performance.
This specification defines more advanced, but still simple CoRE
Congestion Control mechanisms, called CoCoA. The core of these
mechanisms is a Retransmission TimeOut (RTO) algorithm that makes use
of Round-Trip Time (RTT) estimates, in contrast with how the RTO is
determined as per the base CoAP specification (RFC 7252). The
mechanisms defined in this document have relatively low complexity,
yet they improve the default CoAP RTO algorithm. The design of the
mechanisms in this specification has made use of input from
simulations and experiments in real networks.
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 https://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."
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This Internet-Draft will expire on August 25, 2018.
Copyright Notice
Copyright (c) 2018 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
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1. Terminology . . . . . . . . . . . . . . . . . . . . . . . 3
2. Context . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
3. Area of Applicability . . . . . . . . . . . . . . . . . . . . 4
4. Advanced CoAP Congestion Control: RTO Estimation . . . . . . 5
4.1. Blind RTO Estimate . . . . . . . . . . . . . . . . . . . 6
4.2. Measurement-based RTO Estimate . . . . . . . . . . . . . 6
4.2.1. Differences with the algorithm of RFC 6298 . . . . . 7
4.2.2. Discussion . . . . . . . . . . . . . . . . . . . . . 7
4.3. Lifetime, Aging . . . . . . . . . . . . . . . . . . . . . 8
5. Advanced CoAP Congestion Control: Non-Confirmables . . . . . 9
5.1. Discussion . . . . . . . . . . . . . . . . . . . . . . . 9
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 9
7. Security Considerations . . . . . . . . . . . . . . . . . . . 10
8. References . . . . . . . . . . . . . . . . . . . . . . . . . 10
8.1. Normative References . . . . . . . . . . . . . . . . . . 10
8.2. Informative References . . . . . . . . . . . . . . . . . 11
Appendix A. Supporting evidence . . . . . . . . . . . . . . . . 11
A.1. Older versions of the draft and improvement . . . . . . . 12
A.2. References . . . . . . . . . . . . . . . . . . . . . . . 12
Appendix B. Pseudocode . . . . . . . . . . . . . . . . . . . . . 13
B.1. Updating the RTO estimator . . . . . . . . . . . . . . . 13
B.2. RTO aging . . . . . . . . . . . . . . . . . . . . . . . . 14
B.3. Variable Backoff Factor . . . . . . . . . . . . . . . . . 14
Appendix C. Examples . . . . . . . . . . . . . . . . . . . . . . 15
C.1. Example A.1: weak RTTs . . . . . . . . . . . . . . . . . 15
C.2. Example A.2: VBF and aging . . . . . . . . . . . . . . . 15
C.3. Example B: VBF and aging . . . . . . . . . . . . . . . . 16
Appendix D. Analysis: difference between strong and weak
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estimators . . . . . . . . . . . . . . . . . . . . . 16
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . 17
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 17
1. Introduction
CoAP, the Constrained Application Protocol, needs to be implemented
in such a way that it does not cause persistent congestion on the
network it uses. The CoRE CoAP specification defines basic behavior
that exhibits low risk of congestion with minimal implementation
requirements. It also leaves room for combining the base
specification with advanced congestion control mechanisms with higher
performance.
The present specification defines such an advanced CoRE Congestion
Control mechanism, with the goal of improving performance while
retaining safety as well as the simplicity that is appropriate for
constrained devices. Hence, we are calling this mechanism Simple
Congestion Control/Advanced, or CoCoA for short.
CoCoA calculates the retransmission time-out (RTO) based on RTT
estimations with and without loss. By taking retransmissions (in a
potentially lossy network) into account when estimating the RTT, this
algorithm reacts to congestion with a lower sending rate. For non-
confirmable packets, it also limits the sending rate to 1/RTO;
assuming that the RTO estimation in CoCoA works as expected, RTO
should be slightly greater than the RTT, thus CoCoA would be more
conservative than the original specification in [RFC7641].
In the Internet, congestion control is typically implemented in a way
that it can be introduced or upgraded unilaterally. Still, a new
congestion control scheme must not be introduced lightly. To ensure
that the new scheme is not posing a danger to the network,
considerable work has been done on simulations and experiments in
real networks. Some of this work will be mentioned in "Discussion"
subsections in the following sections; an overview is given in
Appendix A. Extended rationale for this specification can also be
found in the historical Internet-Drafts
[I-D.bormann-core-congestion-control] and
[I-D.eggert-core-congestion-control], as well as in the minutes of
the IETF 84 CoRE WG meetings.
1.1. Terminology
This specification uses terms from [RFC7252]. In addition, it
defines the following terminology:
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Initiator: The endpoint that sends the message that initiates an
exchange. E.g., the party that sends a confirmable message, or a
non-confirmable message (see Section 4.3 of [RFC7252]) conveying a
request.
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.
The term "byte", abbreviated by "B", is used in its now customary
sense as a synonym for "octet".
2. Context
In the definition of the CoAP protocol [RFC7252], an approach was
taken that includes a very simple basic scheme (lock-step with the
number of parallel exchanges usually limited to 1) in the base
specification together with performance-enhancing advanced
mechanisms.
The present specification is based on the approved text in the
[RFC7252] base specification. It is making use of the text that
permits advanced congestion control mechanisms and allows them to
change protocol parameters, including NSTART and the binary
exponential backoff mechanism. Note that Section 4.8 of [RFC7252]
limits the leeway that implementations have in changing the CoRE
protocol parameters.
The present specification also assumes that, outside of exchanges,
non-confirmable messages can only be used at a limited rate without
an advanced congestion control mechanism (this is mainly relevant for
[RFC7641]). It is also intended to address the [RFC8085] guideline
about combining congestion control state for a destination; and to
clarify its meaning for CoAP using the definition of an endpoint.
The present specification does not address multicast or dithering
beyond basic retransmission dithering.
3. Area of Applicability
The present algorithm is intended to be generally applicable. The
objective is to be "better" than default CoAP congestion control in a
number of characteristics, including achievable goodput for a given
offered load, latency, and recovery from bursts, while providing more
predictable stress to the network and the same level of safety from
catastrophic congestion. The algorithm defined in this document is
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intended to adapt to the current characteristics of any underlying
network, and therefore is well suited for a wide range of network
conditions, in terms of bandwidth, latency, load, loss rate,
topology, etc. In particular, CoCoA has been found to perform well
in scenarios with latencies ranging from the order of milliseconds to
peaks of dozens of seconds, as well as in single-hop and multihop
topologies. Link technologies used in existing evaluation work
comprise IEEE 802.15.4, GPRS, UMTS and Wi-Fi (see Appendix A). CoCoA
is also expected to work suitably across the general Internet. The
algorithm does require three state variables per scope plus the state
needed to do RTT measurements, so it may not be applicable to the
most constrained devices (say, class 1 as per [RFC7228]).
The scope of each instance of the algorithm in the current set of
evaluations has been the five-tuple, i.e., CoAP + endpoint (transport
address) for Initiator and Responder. Potential applicability to
larger scopes needs to be examined.
4. Advanced CoAP Congestion Control: RTO Estimation
For an initiator that plans to make multiple requests to one
destination endpoint, it may be worthwhile to make RTT measurements
in order to compute a more appropriate RTO than the default initial
timeout of 2 to 3 s. In particular, a wide spectrum of RTT values is
expected in different types of networks where CoAP is used. Those
RTTs range from several orders of magnitude below the default initial
timeout to values larger than the default. The algorithm defined in
this document is based on the algorithm for RTO estimation defined in
[RFC6298], with appropriately extended default/base values, as
proposed in Section 4.2.1. Note that such a mechanism must, during
idle periods, decay RTO estimates that are shorter or longer than the
default RTO estimate back to the default RTO estimate, until fresh
measurements become available again, as proposed in Section 4.3.
RTT variability challenges RTO estimation. In TCP, delayed ACKs
contribute to RTT variability, since this option adds a delay of up
to 500 ms (typically, 200 ms) before an ACK is sent by a receiving
TCP endpoint. However, one important consideration not relevant for
TCP is the fact that a CoAP round-trip may include application
processing time, which may be hard to predict, and may differ between
different resources available at the same endpoint. Also, for
communications with networks of constrained devices that apply radio
duty cycling, large and variable round-trip times are likely to be
observed. Servers will only trigger their early ACKs (with a non-
piggybacked response to be sent later) based on the default timers,
e.g. after 1 s. A client that has arrived at a RTO estimate shorter
than 1 s SHOULD therefore use a larger backoff factor for
retransmissions to avoid expending all of its retransmissions
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(MAX_RETRANSMIT, see Section 4.2 of [RFC7252], normally 4) in the
default interval of 2 to 3 s. The approach chosen for a mechanism
with variable backoff factors is presented in Section 4.2.1.
It may also be worthwhile to perform RTT estimation not just based on
information measured from a single destination endpoint, but also
based on entire hosts (IP addresses) and/or complete prefixes (e.g.,
maintain an RTT estimate for a whole /64). The exact way this can be
used to reduce the amount of state in an initiator is for further
study.
4.1. Blind RTO Estimate
The initial RTO estimate for an endpoint is set to 2 seconds (the
initial RTO estimate is used as the initial value for both E_weak_
and E_strong_ below).
If only the initial RTO estimate is available, the RTO estimate for
each of up to NSTART exchanges started in parallel is set to 2 s
times the number of parallel exchanges, e.g. if two exchanges are
already running, the initial RTO estimate for an additional exchange
is 6 seconds.
4.2. Measurement-based RTO Estimate
The RTO estimator runs two copies of the algorithm defined in
[RFC6298], using the same variables and calculations to estimate the
RTO, with the differences introduced in Section 4.2.1: One copy for
exchanges that complete on initial transmissions (the "strong
estimator", E_strong_), and one copy for exchanges that have run into
retransmissions, where only the first two retransmissions are
considered (the "weak estimator", E_weak_). For the latter, there is
some ambiguity whether a response is based on the initial
transmission or the retransmissions. For the purposes of the weak
estimator, the time from the initial transmission counts. Responses
obtained after the third retransmission are not used to update an
estimator.
The overall RTO estimate is an exponentially weighted moving average
computed of the strong and the weak estimator, which is evolved after
each contribution to the weak estimator (1) or to the strong
estimator (2), from the estimator (either the weak or strong
estimator) that made the most recent contribution:
RTO := w_weak * E_weak_ + (1 - w_weak) * RTO (1)
RTO := w_strong * E_strong_ + (1 - w_strong) * RTO (2)
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(Splitting this update into the two cases avoids making the
contribution of the weak estimator too big in naturally lossy
networks.)
The default values for the corresponding weights, w_weak and
w_strong, are 0.25 and 0.5, respectively. These values have been
found to offer good performance in evaluations (see Appendix A).
Pseudocode and examples for the overall RTO estimate presented are
available in Appendix B.1 and Appendix C.1.
4.2.1. Differences with the algorithm of RFC 6298
This subsection presents three differences of the algorithm defined
in this document with the one defined in [RFC6298]. The first two
recommend new parameter settings. The third one is the variable
backoff factor (VBF), which replaces RFC6298's simple exponential
backoff that always multiplies the RTO by a factor of 2 when the RTO
timer expires.
The initial value for each of the two RTO estimators is 2 s.
For the weak estimator, the factor K (the RTT variance multiplier) is
set to 1 instead of 4. This is necessary to avoid a strong increase
of the RTO in the case that the RTTVAR value is very large, which may
be the case if a weak RTT measurement is obtained after one or more
retransmissions.
In order to avoid that exchanges with small initial RTOs (i.e. RTO
estimate lower than 1 s) use up all retransmissions in a short
interval of time, the RTO for a retransmission is multiplied by 3 for
each retransmission as long as the RTO is less than 1 s.
On the other hand, to avoid exchanges with large initial RTOs (i.e.,
RTO estimate greater than 3 s) not being able to carry out all
retransmissions within MAX_TRANSMIT_WAIT (normally 93 s), the RTO is
multiplied only by 1.5 when RTO is greater than 3 s.
Pseudocode for the variable backoff factor is in Appendix B.3.
The binary exponential backoff is truncated at 32 seconds. Similar
to the way retransmissions are handled in the base specification,
they are dithered between 1 x RTO and ACK_RANDOM_FACTOR x RTO.
4.2.2. Discussion
In contrast to [RFC6298], this algorithm attempts to make use of
ambiguous information from retransmissions. This is motivated by the
high non-congestion loss rates expected in constrained node networks,
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and the need to update the RTO estimators even in the presence of
loss. This approach appears to contravene the mandate in
Section 3.1.1 of [RFC8085] that "latency samples MUST NOT be derived
from ambiguous transactions". However, those samples are not simply
combined into the strong estimator, but are used to correct the
limited knowledge that can be gained from the strong RTT measurements
by employing an additional weak estimator. In fact, the weak
estimator allows to better update the RTO estimator when mostly weak
RTTs are available, either due to the lossy nature of links or due to
congestion-induced losses. In the presence of the latter, and
compared to a strong-only estimator (w_weak=0), spurious timeouts are
avoided and the rate of retries is reduced, which allows to decrease
congestion. Evidence that has been collected from experiments
appears to support that the overall effect of using this data in the
way described is beneficial (Appendix A).
Some evaluation has been done on earlier versions of this
specification [Betzler2013]. A more recent (and more comprehensive)
reference is [Betzler2015].
4.3. Lifetime, Aging
The state of the RTO estimators for an endpoint SHOULD be kept as
long as possible. If other state is kept for the endpoint (such as a
DTLS connection), it is very strongly RECOMMENDED to keep the RTO
state alive at least as long as this other state. In the absence of
such other state, the RTO state SHOULD be kept at least long enough
to avoid frequent returns to inappropriate initial values. For the
default parameter set of Section 4.8 of [RFC7252], it is strongly
RECOMMENDED to keep it for at least 255 s.
If an estimator has a value that is lower than 1 s, and it is left
without further update for 16 times its current value, the RTO
estimate is doubled. If an estimator has a value that is higher than
3 s, and it is left without further update for 4 times its current
value, the RTO estimate is set to be
RTO := 1 s + (0.5 * RTO)
(Note that, instead of running a timer, it is possible to implement
these RTO aging calculations cumulatively at the time the estimator
is used next.)
Pseudocode and examples for the aging mechanism presented are
available in Appendix B.2 and in Appendix C.2.
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5. Advanced CoAP Congestion Control: Non-Confirmables
A CoAP endpoint MUST NOT send non-confirmables to another CoAP
endpoint at a rate higher than defined by this document. Independent
of any congestion control mechanisms, a CoAP endpoint can always send
non-confirmables if their rate does not exceed 1 B/s.
Non-confirmables that form part of exchanges are governed by the
rules for exchanges.
Non-confirmables outside exchanges (e.g., [RFC7641] notifications
sent as non-confirmables) are governed by the following rules:
1. Of any 16 consecutive messages towards this endpoint that aren't
responses or acknowledgments, at least 2 of the messages must be
confirmable.
2. An RTO as specified in Section 4 must be used for confirmable
messages.
3. The packet rate of non-confirmable messages cannot exceed 1/RTO,
where RTO is the overall RTO estimator value at the time the non-
confirmable packet is sent.
5.1. Discussion
The mechanism defined above for non-confirmables is relatively
conservative. More advanced versions of this algorithm could run a
TFRC-style Loss Event Rate calculator [RFC5348] and apply the TCP
equation to achieve a higher rate than 1/RTO.
[RFC7641], Section 4.5.1, specifies that the rate of Non-Confirmables
SHOULD NOT exceed 1/RTT on average, if the server can maintain an RTT
estimate for a client. CoCoA limits the packet rate of Non-
Confirmables in this situation to 1/RTO. Assuming that the RTO
estimation in CoCoA works as expected, RTO[k] should be slightly
greater than the RTT[k], thus CoCoA would be more conservative. The
expectation therefore is that complying with the NON rate set by
CoCoA leads to complying with [RFC7641].
6. IANA Considerations
This document makes no requirements on IANA. (This section to be
removed by RFC editor.)
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7. Security Considerations
The security considerations of, e.g., [RFC5681], [RFC2914], and
[RFC8085] apply. Some issues are already discussed in the security
considerations of [RFC7252].
If a malicious node manages to prevent the delivery of some packets,
a consequence will be an RTO increase, which will further reduce
network performance. Note that this type of attack is not specific
for CoCoA (and not even specific for CoAP), and many congestion
control algorithms increase the RTO upon packet loss detection.
While it is hard to prevent radio jamming, some mitigation for other
forms of this type of attack is provided by network access control
techniques. Also, the weak estimator in CoCoA increases the chances
of obtaining RTT measurements in the presence of heavy packet losses,
allowing to keep the RTO updated, which in turn allows recovery from
a jamming attack in reasonable time.
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/info/rfc2119>.
[RFC2914] Floyd, S., "Congestion Control Principles", BCP 41,
RFC 2914, DOI 10.17487/RFC2914, September 2000,
<https://www.rfc-editor.org/info/rfc2914>.
[RFC6298] Paxson, V., Allman, M., Chu, J., and M. Sargent,
"Computing TCP's Retransmission Timer", RFC 6298,
DOI 10.17487/RFC6298, June 2011,
<https://www.rfc-editor.org/info/rfc6298>.
[RFC7252] Shelby, Z., Hartke, K., and C. Bormann, "The Constrained
Application Protocol (CoAP)", RFC 7252,
DOI 10.17487/RFC7252, June 2014,
<https://www.rfc-editor.org/info/rfc7252>.
[RFC8085] Eggert, L., Fairhurst, G., and G. Shepherd, "UDP Usage
Guidelines", BCP 145, RFC 8085, DOI 10.17487/RFC8085,
March 2017, <https://www.rfc-editor.org/info/rfc8085>.
[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/info/rfc8174>.
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8.2. Informative References
[Betzler2013]
Betzler, A., Gomez, C., Demirkol, I., and J. Paradells,
"Congestion control in reliable CoAP communication",
ACM MSWIM'13 p. 365-372, DOI 10.1145/2507924.2507954,
2013.
[Betzler2015]
Betzler, A., Gomez, C., Demirkol, I., and J. Paradells,
"CoCoA+: an Advanced Congestion Control Mechanism for
CoAP", Ad Hoc Networks Vol. 33 pp. 126-139,
DOI 10.1016/j.adhoc.2015.04.007, October 2015.
[I-D.bormann-core-congestion-control]
Bormann, C. and K. Hartke, "Congestion Control Principles
for CoAP", draft-bormann-core-congestion-control-02 (work
in progress), July 2012.
[I-D.eggert-core-congestion-control]
Eggert, L., "Congestion Control for the Constrained
Application Protocol (CoAP)", draft-eggert-core-
congestion-control-01 (work in progress), January 2011.
[RFC5348] Floyd, S., Handley, M., Padhye, J., and J. Widmer, "TCP
Friendly Rate Control (TFRC): Protocol Specification",
RFC 5348, DOI 10.17487/RFC5348, September 2008,
<https://www.rfc-editor.org/info/rfc5348>.
[RFC5681] Allman, M., Paxson, V., and E. Blanton, "TCP Congestion
Control", RFC 5681, DOI 10.17487/RFC5681, September 2009,
<https://www.rfc-editor.org/info/rfc5681>.
[RFC7228] Bormann, C., Ersue, M., and A. Keranen, "Terminology for
Constrained-Node Networks", RFC 7228,
DOI 10.17487/RFC7228, May 2014,
<https://www.rfc-editor.org/info/rfc7228>.
[RFC7641] Hartke, K., "Observing Resources in the Constrained
Application Protocol (CoAP)", RFC 7641,
DOI 10.17487/RFC7641, September 2015,
<https://www.rfc-editor.org/info/rfc7641>.
Appendix A. Supporting evidence
(Editor's note: The references local to this appendix may need to be
merged with those from the specification proper, depending on the
discretion of the RFC editor.)
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CoCoA has been evaluated by means of simulation and experimentation
in diverse scenarios comprising different link layer technologies,
network topologies, traffic patterns and device classes. The main
overall evaluation result is that CoCoA consistently delivers a
performance which is better than, or at least similar to, that of
default CoAP congestion control. While the latter is insensitive to
network conditions, CoCoA is adaptive and makes good use of RTT
samples.
It has been shown over real GPRS and IEEE 802.15.4 mesh network
testbeds that in these settings, in comparison to default CoAP, CoCoA
increases throughput and reduces the time it takes for a network to
process traffic bursts, while not sacrificing fairness. In contrast,
other RTT-sensitive approaches such as Linux-RTO or Peak-Hopper-RTO
may be too simple or do not adapt well to IoT scenarios,
underperforming default CoAP under certain conditions [1]. On the
other hand, CoCoA has been found to reduce latency in GPRS and WiFi
setups, compared with default CoAP [2].
CoCoA performance has also been evaluated for non-confirmable traffic
over emulated GPRS/UMTS links and over a real IEEE 802.15.4 mesh
testbed. Results show that since CoCoA is adaptive, it yields better
packet delivery ratio than default CoAP (which does not apply
congestion control to non-confirmable messages) or Observe (which
introduces congestion control that is not adaptive to network
conditions) [3, 4].
A.1. Older versions of the draft and improvement
CoCoA has evolved since its initial draft version. Its core has
remained mostly stable since draft-bormann-core-cocoa-02. The
evolution of CoCoA has been driven by research work. This process,
including evaluations of early versions of CoCoA, as well as
improvement proposals that were finally incorporated in CoCoA, is
reflected in published works [5-10].
A.2. References
[1] A. Betzler, C. Gomez, I. Demirkol, J. Paradells, "CoAP
congestion control for the Internet of Things", IEEE Communications
Magazine, July 2016.
[2] F. Zheng, B. Fu, Z. Cao, "CoAP Latency Evaluation", draft-
zheng-core-coap-lantency-evaluation-00, 2016 (work in progress).
[3] A. Betzler, C. Gomez, I. Demirkol, "Evaluation of Advanced
Congestion Control Mechanisms for Unreliable CoAP Communications",
PE-WASUN, Cancun, Mexico, 2015.
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[4] A. Betzler, J. Isern, C. Gomez, I. Demirkol, J. Paradells,
"Experimental Evaluation of Congestion Control for CoAP
Communications without End-to-End Reliability", Ad Hoc Networks,
Volume 52, 1 December 2016, Pages 183-194.
[5] A. Betzler, C. Gomez, I. Demirkol, J. Paradells, "Congestion
Control in Reliable CoAP Communication", 16th ACM International
Conference on Modeling, Analysis and Simulation of Wireless and
Mobile Systems (MSWIM'13), Barcelona, Spain, Nov. 2013.
[6] A. Betzler, C. Gomez, I. Demirkol, M. Kovatsch, "Congestion
Control for CoAP cloud services", 8th International Workshop on
Service-Oriented Cyber-Physical Systems in Converging Networked
Environments (SOCNE) 2014, Barcelona, Spain, Sept. 2014.
[7] A. Betzler, C. Gomez, I. Demirkol, J. Paradells, "CoCoA+: an
advanced congestion control mechanism for CoAP", Ad Hoc Networks
journal, 2015.
[8] Bhalerao, Rahul, Sridhar Srinivasa Subramanian, and Joseph
Pasquale. "An analysis and improvement of congestion control in the
CoAP Internet-of-Things protocol." 2016 13th IEEE Annual Consumer
Communications & Networking Conference (CCNC). IEEE, 2016.
[9] I Jaervinen, L Daniel, M Kojo, "Experimental evaluation of
alternative congestion control algorithms for Constrained Application
Protocol (CoAP)", IEEE 2nd World Forum on Internet of Things (WF-
IoT), 2015.
[10] Balandina, Ekaterina, Yevgeni Koucheryavy, and Andrei Gurtov.
"Computing the retransmission timeout in coap." Internet of Things,
Smart Spaces, and Next Generation Networking. Springer Berlin
Heidelberg, 2013. 352-362.
Appendix B. Pseudocode
B.1. Updating the RTO estimator
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// Default values
ALPHA = 0.125 // RFC 6298
BETA = 0.25 // RFC 6298
W_STRONG = 0.5
W_WEAK = 0.25
updateRTO(retransmissions, RTT) {
if (retransmissions == 0) {
RTTVAR_strong = (1 - BETA) * RTTVAR_strong
+ BETA * (RTT_strong - RTT);
RTT_strong = (1 - ALPHA) * RTT_strong + ALPHA * RTT;
E_strong = RTT_strong + 4 * RTTVAR_strong;
RTO = W_STRONG * E_strong + (1 - W_STRONG) * RTO;
} else if (retransmissions <= 2) {
RTTVAR_weak = (1 - BETA) * RTTVAR_weak
+ BETA * (RTT_weak - RTT);
RTT_weak = (1 - ALPHA) * RTT_weak + ALPHA * RTT;
E_weak = RTT_weak + 1 * RTTVAR_weak;
RTO = W_WEAK * E_weak + (1 - W_WEAK) * RTO
}
}
B.2. RTO aging
checkAging() {
clock_time difference = getCurrentTime() - lastUpdatedTime;
if ((RTO < 1s) && (difference > (16 * RTO))) {
RTO = 2 * RTO;
lastUpdatedTime = getCurrentTime();
} else if ((RTO > 3s) && (difference > (4 * RTO))) {
RTO = 1s + 0.5 * RTO;
lastUpdatedTime = getCurrentTime();
}
}
B.3. Variable Backoff Factor
backOffRTO() {
if (RTO < 1s) {
RTO = RTO * 3;
} else if (RTO > 3s) {
RTO = RTO * 1.5;
} else {
RTO = RTO * 2;
}
}
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Appendix C. Examples
C.1. Example A.1: weak RTTs
A large network of sensor nodes that report periodical measurements
is operating normally, without congestion. The nodes transmit their
sensor readings via CON messages every 20 s in an asynchronous way
towards a server located behind a gateway, obtaining strong RTT
measurements (RTT 1.1 s, RTTVAR 0.1 s) that lead to the calculation
of an RTO of 1.5 s (in average) in each node. In this mode of
operation, no aging is applied, since the RTO is refreshed before the
aging mechanism applies.
Suddenly, upon detection of a global event, the majority of sensor
nodes start transmitting at a higher rate (every 5 s) to increase the
resolution of the acquired data, which creates heavy congestion that
leads to packet losses and an important increase of real RTT between
the nodes and the server (RTT 2 s, RTTVAR 1 s). Due to the packet
losses and spurious retransmissions (which can fuel congestion even
more), many nodes are not able to update their RTO via strong RTT
measurements, but they are able to obtain weak RTT measurements. A
node with an initial RTO of 1.5 s would run into a retransmission,
before obtaining an ACK (given the RTT of 2 s and that the ACK is not
lost).
This weak RTT measurement would increase the overall RTO of the node
to 1.875 s (RTO = 0.25 * 3 s + 0.75 * 1.5 s). Following the same
calculus (and RTT/RTTVAR values), after obtaining another weak RTT,
the RTO would increase to 2.156 s. At this point, the benefits of
the weak RTT measurements are twofold:
1. Further spurious retransmissions are avoided as the RTO has
increased above the real RTT.
2. The increase of RTOs across the whole network reduces the rate
with which retransmissions are generated, decreasing the network
congestion (which leads to an RTT and packet loss decrease).
C.2. Example A.2: VBF and aging
Assuming that the frequency of message generation is even higher
(every 3 s) and the real RTT would further increase due to
congestion, the RTO at some point would increase to 4 s. Since now
the RTO is above 3 s, no longer a binary backoff is used to avoid the
RTO growing too much in case of retransmissions. As the generation
of data from the nodes ceases at some point (the network returns to a
normal state), the aging mechanism would reduce the RTO automatically
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(with an RTO of 4 s, after 16 s the RTO would be shifted to 3 s
before a new RTT is measured).
C.3. Example B: VBF and aging
A network of nodes connected over 4G with an Internet service is
calculating very small RTO values (0.3 s) and the nodes are
transmitting CON messages every 1 s. Suddenly, the connection
quality gets worse and the nodes switch to a more stable, yet slower
connection via GPRS. As a result of this change, the nodes run into
retransmissions, as the real RTT has increased above the calculated
RTO.
Since the RTO is below 1 s, the Variable Backoff Factor increases the
backoff values quickly to avoid spurious retransmissions (0.9 s first
retry, 2.7 s second retry, etc.). Further, if due to the packet
losses and increased delays in the network no new RTT measurements
are obtained, the aging mechanism automatically increases the RTO
(doubling it) after 3.8 s (16 * 0.3 s) to adapt better to the sudden
changes of network conditions. Without the Variable Backoff Factor
and the aging mechanism, the number of spurious retransmissions would
be much higher and the RTO would be corrected more slowly.
Appendix D. Analysis: difference between strong and weak estimators
This section analyzes the difference between the strong and weak RTO
estimators. If there is no congestion, assume a static RTT of R'.
Then, E_strong_can be expressed as:
E_strong_ = R' + G,
since RTTVAR is reduced constantly by RTTVAR = RTTVAR * 3/4
(according to [RFC6298], and SRTT=R'), G would be dominant term in
the max(G, K * RTTVAR) expression in the long run.
For the weak estimator: assume that the RTO setting converges to
E_strong_ calculated above in the long run. If there is a packet
loss, and an RTT is obtained for the first retransmission, then the
weak RTT sample obtained by the weak estimator is:
RW' = R'+ G + R'
Therefore, E_weak_ can be expressed as:
E_weak_ = RW' + max(G, RW'/2) = 3 * R'
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Acknowledgements
The first document to examine CoAP congestion control issues in
detail was [I-D.eggert-core-congestion-control], to which this draft
owes a lot.
Michael Scharf did a review of CoAP congestion control issues that
asked a lot of good questions. Several Transport Area
representatives made further significant inputs this discussion
during IETF84, including Lars Eggert, Michael Scharf, and David
Black. Andrew McGregor, Eric Rescorla, Richard Kelsey, Ed Beroset,
Jari Arkko, Zach Shelby, Matthias Kovatsch and many others provided
very useful additions. Further reviews by Michael Scharf and Ingemar
Johansson led to further improvements, including some more discussion
in the appendices.
Authors from Universitat Politecnica de Catalunya have been supported
in part by the Spanish Government's Ministerio de Economia y
Competitividad through projects TEC2009-11453, TEC2012-32531,
TEC2016-79988-P and FEDER.
Carles Gomez has been funded in part by the Spanish Government
(Ministerio de Educacion, Cultura y Deporte) through the Jose
Castillejo grant CAS15/00336. His contribution to this work has been
carried out in part during his stay as a visiting scholar at the
Computer Laboratory of the University of Cambridge, in collaboration
with Prof. Jon Crowcroft.
Authors' Addresses
Carsten Bormann
Universitaet Bremen TZI
Postfach 330440
Bremen D-28359
Germany
Phone: +49-421-218-63921
Email: cabo@tzi.org
August Betzler
Fundacio i2CAT
Mobile and Wireless Internet Group
C/ del Gran Capita, 2
Barcelona 08034
Spain
Email: august.betzler@i2cat.net
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Carles Gomez
Universitat Politecnica de Catalunya/Fundacio i2CAT
Escola d'Enginyeria de Telecomunicacio i Aeroespacial
de Castelldefels
C/Esteve Terradas, 7
Castelldefels 08860
Spain
Phone: +34-93-413-7206
Email: carlesgo@entel.upc.edu
Ilker Demirkol
Universitat Politecnica de Catalunya/Fundacio i2CAT
Departament d'Enginyeria Telematica
C/Jordi Girona, 1-3
Barcelona 08034
Spain
Email: ilker.demirkol@entel.upc.edu
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