Computing
Co
put g the
t e Retransmission
et a s ss o
Timeout in COAP
Prof. Andrei Gurtov,
PhD student Ekaterina Dashkova
Centre for Wireless Communications, University of Oulu
Introduction
` Fast development of wireless sensor networks (WSNs) requires creation
of the new protocol solutions and infrastructure that enables stable and
efficient use of WSN with the Internet
`
Constrained Application Protocol (CoAP) is a generic web protocol that
satisfies special requirements of constrained environment, especially
considering
id i energy, bbuilding
ildi automation
i and
d other
h M2M applications
li i
MAMMOTH Project in Finland
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Funded by Ubicom program of Tekes 2011-2013
Consortium
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Ericsson – Nomadic Lab
Sensinode
Renesas Mobile
There Corporation
Kajaani Data Center operator
Aalto University – DCS (Prof
(Prof.Ylä-Jääski)
Ylä Jääski)
University of Oulu – Mediateam (Prof. Ojala)
University of Oulu – CWC (Prof. Gurtov)
3
Project Scope
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Mass-scale M2M services
` Billions of web resources, a billion nodes
CoRE architecture scalability in M2M
` Protocols between M2M devices and services
Lightweight
g
g yet
y sufficient securityy for M2M
M2M service developer requirements & APIs
Billion node network & service emulation
4
Main Project Goals
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Large-scale emulation of an M2M system
` Using the Kajaani/CSC supercomputer
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Analysis & optimization of CoRE in M2M
` Scalability, load balancing, HTTP comparison
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Optimized M2M protocol security
C
Congestion
i controll ffor mass-scale
l M2M
M2M Services
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Centralized vs. distributed M2M architecture
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Gateway aggregation
Service API
Real and test M2M platform software
Data format scalability
Standardization contributions to IETF and other SDOs
5
Reference Network Topology
Congestion Control in CoAP: current status
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CoAP has reliable transmission mode with simple congestion control
mechanism available on top of retransmission timer
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CoAP doesn’t provide internal congestion control mechanisms for non
reliable transmission mode that likely will be majority of traffic
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UDP protocol is used by CoAP at Transport layer, so no congestion control
is provided
`
Draft ”CoAP Simple
p Congestion
g
Control/Advance” was published
p
byy CoRE
Working Group on Aug. 13, 2012
Data Link Layer Techniques
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C i SSense M
Carrier
Multiple
li l A
Access (CSMA)
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Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA)
Carrier Sense Multiple Access with Collision Detection (CSMA/CD)
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Frequency Division Multiple Access (FDMA)
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Time Division Multiple Access (TDMA)
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O d
On-demand
d TDMA extension
i off IEEE802.15.4
IEEE802 15 4 MAC
Hybrid TDMA/FDMA
TDMA/FDMA-based
based medium access
Network Layer Techniques
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Beacon Order Based RED (BOB-RED) - active queue
management technique :
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divides traffic on real-time and non-real time
virtual threshold function
dynamic adjusted per-flow drop probability
dynamic modification of beacon order (BO) and super-frame
order (SO) strategy
Transport Layer Techniques
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Sensor Transmission Control Protocol (STCP)
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Pump Slowly Fetch Quickly
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Light UDP
Background of the Study
Importance of RTO
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RTO – retransmission timer – the time that elapses after
a packet has been sent until the sender considers it lost
and therefore retransmits it
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RTO is a prediction of the upper limit of the round-trip
time (RTT)
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It is ggreatlyy influence reliable peer-to-peer
p
p
performance
p
Importance of RTO
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Spurious timeout - too optimistic retransmission time
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it causes unnecessary traffic
reducing a connection’s effective throughput
A conservative retransmission timer
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itt causes long
o g idlee times
t es before
be o e the
t e lost
ost packet
pac et iss retransmitted
et a s tte
Importance of the CC parameters
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Round-trip time variation (RTTVAR) increase quickly with
load (if load is ρ variation scale like (1- ρ)-1)
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Exponential back-off mechanism is very important for an
endpoint embedded in the network with the unknown
topology and constantly changing competing conversation
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WSNs are expected to have high packet-loss rates in this
situation accurate RTO estimation becomingg more topical
p
CoAP Simple Congestion Control
CoAP Simple Congestion Control/Advanced
draft-bormann-core-cocoa-00 C. Bormann Universitaet
Bremen TZI , August 13, 2012
`
Algorithm from RFC6298 was taken as basis for RTO
estimation calculation and couple
p of changes
g were proposed
p p
by the authors:
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initial RTO estimate is set to 2 seconds
the
h RTO estimator
i
runs two copies
i defined
d fi d in
i RFC6298
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copy that completes on initial transmission (”strong” estimator)
copy
py that runs into retransmissions (”weak”
(
estimator))
the overall RTO estimate is calculated as an average of the currently
calculated (”weak” or ”strong”) value and that had been calculated
on the previous step
CoAP Advanced Congestion Control
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Advanced part of the algorithm describing rules for sending
non-confermable messages:
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limiting rate for sending non-confermable messages 1B/s
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non-confermable messages must be sent 1 per RTO
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at least of 2 of 16 messages must be confermable
CoAP Simple Congestion Control
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Constant which are used: alpha = 1/8, beta = 1/4, K = 4
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SRTT (smoothed RTT) keeps history of RTT
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RTTVAR (RTT variation) keeps history of variations of RTT
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G (granularity) should at least be an order less than the RTT
CoAP Simple Congestion Control
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After the first RTT measurement
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SRTT <- RTT
RTTVAR <- RTT/2
After a subsequent RTT measurement
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RTTVAR <- (1 - beta) * RTTVAR + beta * |SRTT - RTT|
SRTT <- (1 - alpha) * SRTT + alpha * RTT
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RTO<- SRTT + max (G, K*RTTVAR)
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RTO_overall = 0.5*RTO_recent + 0.5*RTO_overall
Modifications
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To the existing model we proposed several modifications:
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If RTT sample was taken after initial transmission we forget
prehistory:
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RTO_overall = RTO_recent
If RTT sample was taken after retransmissiom occurs we
follow the rule of RTO estimation:
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RTO_overall = 0.5*RTO_recent + 0.5*RTO_overall
Modifications
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If RTT – SRTT < 0 then we skip the rule of changigng
RTTVAR while if RTT – SRTT > 0 we using standard
formular to change it
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Instead constant coefficients alpha and beta we propose
to use gamma = RTT/RTO
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If gamma > 0.5 we are changing its value on 1-gamma
gamma
Modifications
` Source:
M. Zubair Shafiq, Lusheng Ji, Alex X. Liu, Jeffrey Pang, Jia Wang “A First Look at Cellular Machine-toMachine Traffic - Large Scale Measurement and Characterization”,
SIGMETRICS’12, June 11–15, 2012, London, England, UK.
Model and the toolkit
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On the previous slide there was a source from which we took RTT variation
interval (0.5 ; 2) seconds
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At the same time when the packet loss increases importance of RTO
estimation increases as well
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We used Matlab as the toolkit for algorithm realization and first-step
first step testing
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In the model we assume simple end-to-end scheme with the same delay in
b th endpoints
both
d i t
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Plots on the next slides depicts the difference between performance of the
C C AP RTO estimation
CoCoAP
i
i algorithm
l i h and
d our modified
difi d version
i
Simulation Results 1
Simulation Results 2
Simulation Results 3
Simulation Results 4
Conclusion
According to the test results modified algorithm works
b
better
than
h classical
l i l one
`
IIt is
i more agressive
i bbut at the
h same time
i
more efficient
ffi i
in
i
stable conditions as well as when some unpredictable
events occur
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C implementation will be evaluated in Cooja simulator
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In future work we plan to implement proposed algorithm
in the emulator and test on real data
Bibliography
`
draft “CoAP Simple Congestion Control/Advanced” draftbormann-core-cocoa-00 < http://tools.ietf.org/html/draftb
bormann-core-cocoa-00
00 >
`
M. Zubair
M
Z b i Shafiq,
Sh fi Lusheng
L h
Ji Alex
Ji,
Al X.
X Liu,
Li JJeffrey
ff
P
Pang, Jia
Ji Wang
W
“A First Look at Cellular Machine-to-Machine Traffic - Large
Scale Measurement and Characterization
Characterization”, SIGMETRICS
SIGMETRICS’12
12,
June 11–15, 2012, London, England, UK.
R. Ludwig, K. Sklower “The
The Eifel Retransmission Timer
Timer”,, ACM
CCR,Volume 30 Issue 3, July 2000
`