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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Performance Analysis of the Contention AccessPeriod in the slotted IEEE 802.15.4 for Wireless
Body Sensor Networks
Manuel AymerichTutor: Nadia Khaled
Dept. Teorıa de Senal y ComunicacionesUniversidad Carlos III de Madrid
Leganes, May 21, 2009
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Outline
1 Motivation and ObjectivesMotivation and Objectives
2 State-of-the-ArtMAC design in WBSNOverview of the sloted IEEE 802.15.4 CAP
3 Analytical ModelDevelopmentAnalytical Formulation
4 High Pathloss WBSNAnalysisChanges in the Analytical Model
5 ResultsInitial ConsiderationsComparison ACK and non-ACK trafficPerformance Results for a high path loss WBSN
6 Conclusions2 / 37
Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Outline
1 Motivation and ObjectivesMotivation and Objectives
2 State-of-the-ArtMAC design in WBSNOverview of the sloted IEEE 802.15.4 CAP
3 Analytical ModelDevelopmentAnalytical Formulation
4 High Pathloss WBSNAnalysisChanges in the Analytical Model
5 ResultsInitial ConsiderationsComparison ACK and non-ACK trafficPerformance Results for a high path loss WBSN
6 Conclusions3 / 37
Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Motivation and Objectives
Motivation
WBSN ⇒ tremendous international
interest in recent years.
Advances in low power, lowcost, wireless MEMC systems.Significant progress in wearableand implantable biosensors.
WBSN Applications:
In-vivo monitoring: everydayhealthcare, sports.Video Games.
System requirements:
Single hop star topology.Low-power.Low-cost.Self-configuring.
ECG &Tilt Sensor
MotionSensors
SpO2 &Motion Sensor
Personal Server
Network CoordinatorTemperature &
Humidity Sensor
IEEE 802.15.4
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Motivation and Objectives
Objectives
According to Dr. Leonard Fass, Director of GE Healthcare:
”One of the greatest barriers to the adoption of emerging BSNtechnologies is the whether or not they can be integrated withexisting systems, under common standards.”
The novel IEEE 802.15.4 standard is poised to become the globalstandard for low data rate, low energy consumption WSN.
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Motivation and Objectives
Objectives
Analyze the CAP of the slotted IEEE 802.15.4 standardworking under a WBSN application scheme.
1 Star topology.2 Acknowledged uplink traffic (nodes-to-coordinator).3 High pathloss human body channel.
How?
Extend an a state-of-the-art analytical model of the IEEE802.15.4 CAP for acknowledged traffic and under a WBSNchannel.Evaluate it in terms of energy consumption and throughput.Compare with ns-2 simulation results.
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Outline
1 Motivation and ObjectivesMotivation and Objectives
2 State-of-the-ArtMAC design in WBSNOverview of the sloted IEEE 802.15.4 CAP
3 Analytical ModelDevelopmentAnalytical Formulation
4 High Pathloss WBSNAnalysisChanges in the Analytical Model
5 ResultsInitial ConsiderationsComparison ACK and non-ACK trafficPerformance Results for a high path loss WBSN
6 Conclusions6 / 37
Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
MAC design in WBSN
Energy Efficiency in WBSN MAC Protocols
The MAC layer directly controls energy operation.
Major causes of energy waste in WBSN:
1 Collisions2 Idle listening3 Overhearing4 Packet overhead
WBSN MAC design focuses on minimizing energyconsumption.
Contention based protocols: turning radio into sleep statewhen it is not needed.Scheduled based protocols: low duty cycling.
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Overview of the sloted IEEE 802.15.4 CAP
MAC Layer
Operational Modes:
IEEE 802.15.4 MAC
Beacon Enabled Non-Beacon Enabled
Superframe Unslotted CSMA/CA
Contention Access Period Contention Free Period
Slotted CSMA/CA GTS Allocation
Non-beacon-enabled mode:Distributed system without coordinator.Ad-hoc.
Beacon-enabled mode:CoordinatedSynchronization through beacon.Superframe time structure to organize communication.
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Overview of the sloted IEEE 802.15.4 CAP
Beacon-Enabled Mode
Beacon frames are periodically sent by the coordinator every BI.Delimits the superframe structure and enables communication.
Superframe structure:
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Overview of the sloted IEEE 802.15.4 CAP
CAP CSMA/CA Mechanism
NB = 0, CW = 2
Battery lifeextension?
BE = macMinBE
BE = lesser of(2, macMinBE)
Locate backoffperiod boundary
Delay forrandom(2BE - 1) unit
backoff periods
Perform CCA onbackoff period
boundary
Channel idle?
CW = 2, NB = NB+1,BE = min(BE+1, aMaxBE)
CW = CW - 1
CW = 0?NB>
macMaxCSMABackoffs?
Failure Success
Slotted CSMA
Y
Y Y
Y
N
N
N
N
Step 1. Init
Step 2. BackoffProcedure
Step 3. CCA
Step 4. ACK
Example...
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Outline
1 Motivation and ObjectivesMotivation and Objectives
2 State-of-the-ArtMAC design in WBSNOverview of the sloted IEEE 802.15.4 CAP
3 Analytical ModelDevelopmentAnalytical Formulation
4 High Pathloss WBSNAnalysisChanges in the Analytical Model
5 ResultsInitial ConsiderationsComparison ACK and non-ACK trafficPerformance Results for a high path loss WBSN
6 Conclusions11 / 37
Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Development
About the Analytical Model
Based on Ramachandran et al. model from University ofWashington.
Inspired on Bianchi’s analysis of IEEE 802.11.
Models sensors and channel using Markov chains.
Unacknowledged traffic.
No channel Model.
Choice:
Accuracy of the model with respect to ns-2 simulations.
Amenability for extension.
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Development
Model Assumptions
One-hop star topology
Fixed number of sensing devices (M)
Only CAP with no inactive period
No data packet retransmissions
Data packets of fixed N-backoff slots duration.
Packets arrive at the nodes according to a Poisson arrival rateλ.
No buffering at the nodes.
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Analytical Formulation
Markov Chain Model for a Sensing Node
1-p
IDLE
BO3
CS31
CS32
BO4
CS41
CS42
1-p3n 1-p4
n
p3n
pic
pi|ic
(1-p i
c )(1-p 4
n )
(1-p i|i
c )(1-p 4
n )
(1-p i|i
c )p 4n
(1-pic)p4
n
p4n
pic
pi|ic
p(1-p 1n )
pp1n
BO1
CS11
CS12
BO2
CS21
CS22
1-p1n 1-p2
n
p1n
pic
pi|ic
(1-p i
c )(1-p 2
n )
(1-p i|i
c )(1-p 3
n )
(1-p i|i
c )p 2n
(1-pic)p2
n
p2n
pic
pi|ic
(1-p i
c )(1-p 3
n )
(1-p i|i
c )(1-p 2
n )
(1-p i|i
c )p 3n
(1-pic)p3
n
BO5
CS51
CS52
(1-p i
c )(1-p 5
n )
(1-p i|i
c )(1-p 5
n )
(1-p i|ic )p 5
n
(1-pic)p5
n
p5n
pic
pi|ic
1-p5n
ACK
TX
(1-pic)
(1-pi|ic)
1
1
Backoff before channel sensing
Max number of backoffs/trials to re-access channel when sensed busy for one packet
Channel must be sensed idle during CW=2 consecutive
backoff slots
Channel Access failure
This Markov Chain is solved an equation relating pci and the probability that a
node accesses the channel pnt.
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Analytical Formulation
Markov Chain Model For the Channel
IDLE,IDLE
SUCCESS
BUSY,IDLE
FAILURE
α
δ=1-α-β
β
11
1
NO node begins transmission
One and only one node begins transmission
More than one node begins transmission at
the same time
This Markov Chain is solved the second necessary equation relating pci and the probability
that a node accesses the channel pnt to characterize completely the whole system.
Consistent non linearequation system forpc
i/i , pci and pn
t .which can be solvedfollowing numericalapproximationtechniques.
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Analytical Formulation
Time Spent in the ACK and (BUSY,IDLE) States
tack_min Lack
(a) Slot timing for the derivation of tsuccess
… idleACKdata …
… idle
tack_max
…
(a) Slot timing for the derivation of tfailure
collision
0.6 ≤ tack ≤ 1.6 (1)
The presence of acknowledgements makes the time spent in the (ACK) nodestate and (BUSY,IDLE) channel state non deterministic:
1 On the previous model, it was just one slot.
2 Determining these timings is an important aspect of our contributedmodel.
3 Probabilistic approach to determine the mean time spent on this states. 16 / 37
Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Analytical Formulation
Performance MetricsAggregated throughput:
Relative time spent in the successful channel state.
S =Nπc
s
πcii + T c
B,Iπc
bi+ Nπc
s + Nπcf
=Nβ
1 + T cB,I
(1 − α) + N(β + δ)(2)
Average power consumption per node:
Relative time spent on transmitting, receiving and idle node states.
Yav = (pnidle − pn
beacon + pnbo − pn
ir )Yidle + (pncs + pn
ir + pnbeacon + pn
ack )Yrx + pntx Ytx (3)
Per node bytes-per-Joule capacity:
η =(S/M)(250 × 103/8)
Yav(4)
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Outline
1 Motivation and ObjectivesMotivation and Objectives
2 State-of-the-ArtMAC design in WBSNOverview of the sloted IEEE 802.15.4 CAP
3 Analytical ModelDevelopmentAnalytical Formulation
4 High Pathloss WBSNAnalysisChanges in the Analytical Model
5 ResultsInitial ConsiderationsComparison ACK and non-ACK trafficPerformance Results for a high path loss WBSN
6 Conclusions18 / 37
Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Analysis
Path Loss Model for the Human Body
The human body is a very lossy medium.
Transmissions near the human body are not always possible.
Recently E. Reusens et al. and A. Fort et al. proposed the useof a lognormal model distribution+shadowing deviation todetermine the node’s communication range:
PL = PdB + Ps = P0,dB + 10nlog(d/d0) + tσ
The PL exponent n is varied empirically to match themeasured data.Ps = tσ is the shadowing component.t =√
2erfc−1[2(1− p)]
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Analysis
Parameter Values for the Shadowing Model
parameter value LOS value NLOS
d0 10 cm 10 cm
P0,dB 35.7 dB 48.8 dB
σ 6.2 dB 5.0 dB
n 3.38 5.9
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Changes in the Analytical Model
New Channel Markov Chain
IDLE,IDLE
SUCCESS
BUSY,IDLE
FAILURE
α
βPe+ δ
β(1-P e)
11
1
Inclusion of the packet loss rate Pe .
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Outline
1 Motivation and ObjectivesMotivation and Objectives
2 State-of-the-ArtMAC design in WBSNOverview of the sloted IEEE 802.15.4 CAP
3 Analytical ModelDevelopmentAnalytical Formulation
4 High Pathloss WBSNAnalysisChanges in the Analytical Model
5 ResultsInitial ConsiderationsComparison ACK and non-ACK trafficPerformance Results for a high path loss WBSN
6 Conclusions22 / 37
Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Initial Considerations
Flow diagram to Obtain Results
ns-2
Config Script.tcl
Trace File .tr
gawkAnalyzerNAM
Topology.scn
Matlab
Output Data.txt
Analyzer script.awk
Seed Value
Simul Init
Performance Graphs
Nam File .nam
Topology Animator
Matlab
Analytical Init
Solution
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Initial Considerations
Parameters Used
aMinBE = 3 aMaxBE = 5CSMA/CA parameters macMaxCSMABackoffs = 5 CW = 2
BCO = 6 SFO = 6Analytical parameters pn
beacon = 1/3072Data Packet size N = Ldata = 10backoffslots nbeacon = 2backoffslots
Number of sensing Nodes M = 12
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Initial Considerations
CC2420 Energy State Values
Max [dBm] Min [dBm]Sensitivity S(R) -94 -90
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Comparison ACK and non-ACK traffic
Throughput
10−3
10−2
10−1
100
10−2
10−1
100
Per packet arrival rate λ [packet per packet duration]
Cha
nnel
thro
ughp
ut, S
Analytical ACK
Simulation ACK
Analytical NO ACK
Simulation NO ACK
10−3
10−2
10−1
100
0
2
4
6
8
10
12
14
Per packet arrival rate λ [packet per packet duration]%
cha
nge
in th
roug
hput
Excellent accuracy of our analytical model capturing throughput
performance.26 / 37
Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Comparison ACK and non-ACK traffic
ns-2 Overhearing Bug
10−3
10−2
10−1
100
10−1
100
101
102
Per packet arrival rate λ [packet per packet duration]
Per
−no
de p
ower
con
sum
ptio
n, Y
av [m
W]
Analytical NO ACKSimulation NO ACK
Figure: Per node power consumption27 / 37
Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Comparison ACK and non-ACK traffic
ns-2 Overhearing Bug
10−3
10−2
10−1
100
10−2
10−1
100
101
102
Per packet arrival rate λ [packet per packet duration]
Per
−no
de T
x po
wer
con
sum
ptio
n,Y
tx [m
W] Analytical NO ACK
Simulation NO ACK
10−3
10−2
10−1
100
10−2
10−1
100
101
102
Per packet arrival rate λ [packet per packet duration]
,Per
−no
de R
x po
wer
con
sum
ptio
n,Y
rx [m
W]
Analytical NO ACKSimulation NO ACK
10−3
10−2
10−1
100
10−1
100
101
102
Per packet arrival rate λ [packet per packet duration]
Per
−no
de Id
le p
ower
con
sum
ptio
n, Y
idle
[mW
] Analytical NO ACKSimulation NO ACK
Simulation Rx energy increases.
Simulation Idle energy decreases.
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Comparison ACK and non-ACK traffic
Average per node power consumption
10−3
10−2
10−1
100
100
101
Per packet arrival rate λ [packet per packet duration]
Per
−no
de p
ower
con
sum
ptio
n, Y
av [m
W]
Analytical ACKAnalytical NO ACK
10−3
10−2
10−1
100
0
1
2
3
4
5
6
7
Per packet arrival rate λ [packet per packet duration]
% c
hang
e in
per
nod
e po
wer
con
sum
ptio
n
The inclusion of the ACK increases energy consumption.
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Comparison ACK and non-ACK traffic
Bytes per Joule capacity
10−3
10−2
10−1
100
102
Per packet arrival rate λ [packet per packet duration]
Byt
es p
er J
oule
cap
acity
, η [K
B/J
]
Bytes per Joule capacity comparison
Analytical ACKAnalytical NO ACK
10−3
10−2
10−1
100
0
2
4
6
8
10
12
14
16
Per packet arrival rate λ [packet per packet duration]%
cha
nge
in b
ytes
−pe
r−Jo
ule
capa
city
The optimal energy-throughput trade off, archived for a datarate of
λ = 0.04 = 10kbps29 / 37
Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Performance Results for a high path loss WBSN
Throughput in the LOS channel
10−3
10−2
10−1
100
10−2
10−1
100
Per packet arrival rate λ [packet per packet duration]
Cha
nnel
thro
ughp
ut, S
Throughput comparison WBSN channel with LOS
Analytical ACK Pe=0%Analytical ACK Pe=5%Simulation ACK Pt=1mWSimulation ACK Pt=0.1mW
Figure: Throughput comparison WBSN channel with LOS
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Performance Results for a high path loss WBSN
Average per node power consumption LOS channel
10−3
10−2
10−1
100
100
101
Per packet arrival rate λ [packet per packet duration]
Per
−no
de p
ower
con
sum
ptio
n, Y
av [m
W]
LOS channel
Analytical ACK Pt=1mWAnalytical ACK Pt=0.1mW
Figure: Per-node power consumption in LOS channel
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Performance Results for a high path loss WBSN
Throughput in NLOS channel
10−3
10−2
10−1
100
10−2
10−1
100
Per packet arrival rate λ [packet per packet duration]
Cha
nnel
thro
ughp
ut, S
Throughput comparison BSN channel with NLOS
Simulation ACK Pt=1mWSimulation ACK Pt=0.32mWAnalytical ACK Pe=0%Analytical ACK Pe=5%
Figure: Throughput comparison WBSN channel with NLOS
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Performance Results for a high path loss WBSN
Hidden terminal problem
For high data rates, the hidden terminal problem becomesdominant, and collapses our model.
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Outline
1 Motivation and ObjectivesMotivation and Objectives
2 State-of-the-ArtMAC design in WBSNOverview of the sloted IEEE 802.15.4 CAP
3 Analytical ModelDevelopmentAnalytical Formulation
4 High Pathloss WBSNAnalysisChanges in the Analytical Model
5 ResultsInitial ConsiderationsComparison ACK and non-ACK trafficPerformance Results for a high path loss WBSN
6 Conclusions34 / 37
Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Conclusions
Extension of an analytical model of the slotted CSMA/CAprocedure in the CAP of the IEEE 802.15.4 standard toacknowledged traffic.The validity of the analytical model has been demonstratedcomparing with simulation results.For the purpose of conducting near realistic simulations, theChipcon CC2420 IEEE 802.15.4 transceiver energy parametershave been used.The results of the analytical model resolution have been thenemployed to predict throughput and energy consumption.We have uncovered one of the main problems of using IEEE802.15.4 in a human body environment: hidden node problem⇒ multihop topology or the use of relays could be moresuited.
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Future Work
Solve the overhearing ns-2 simulation bug.
Include in the model, the possibility of hidden nodes.
Study the GTS implementation, particularly effective forWBSN applications that have timing constraints.
Use a multi-hop topology strategy to solve energy issues.
Study other sophisticated channel models available in theliterature to perform different evaluations and contrast studies.
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Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Questions?
Thank you for your attention!
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