Wireless body sensor networks (WBSN) are a particular type of wireless sensor networks (WSN) that are becoming an important topic in the technological research community. Advances in the reduction of the power consumption and cost of these networks have led to solutions mature enough for their use in a broad range of applications such as sportsman or health monitoring. The development of those applications has been stimulated by the finalization of the IEEE 802.15.4 standard, which defines the medium access control (MAC) and physical layer (PHY) for low-rate wireless personal area networks (LR-WPAN). One of the MAC schemes proposed is slotted Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA). This project analyzes the performance of this MAC, based on a state-of-the-art analytical model for a star topology, which captures the behavior of the MAC using two Markov chain models; the per-node state model and the channel state model. More importantly, we extend this model to include acknowledged traffic. The impact of including acknowledgments is evaluated in terms of energy consumption, throughput and latency. The performance predicted by the analytical model has been extensively verified with simulations using the ns-2 IEEE 802.15.4 contributed module. Throughput, energy consumption and latency analysis is performed. Additionally, we have simulated a statistical channel model describing the radio channel behavior around the human body to calculate the packet error rate (PER) found in a typical WBSN under the aforementioned standard. This PER is then introduced into our analytical model.

1. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Performance Analysis of the Contention Access
Period in the slotted IEEE 802.15.4 for Wireless
Body Sensor Networks
Manuel Aymerich
Tutor: Nadia Khaled
Dept. Teor´ de Se˜al y Comunicaciones
ıa n
Universidad Carlos III de Madrid
Legan´s, May 21, 2009
e
1 / 37

2. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Outline
1 Motivation and Objectives
Motivation and Objectives
2 State-of-the-Art
MAC design in WBSN
Overview of the sloted IEEE 802.15.4 CAP
3 Analytical Model
Development
Analytical Formulation
4 High Pathloss WBSN
Analysis
Changes in the Analytical Model
5 Results
Initial Considerations
Comparison ACK and non-ACK traffic
Performance Results for a high path loss WBSN
6 Conclusions
2 / 37

3. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Outline
1 Motivation and Objectives
Motivation and Objectives
2 State-of-the-Art
MAC design in WBSN
Overview of the sloted IEEE 802.15.4 CAP
3 Analytical Model
Development
Analytical Formulation
4 High Pathloss WBSN
Analysis
Changes in the Analytical Model
5 Results
Initial Considerations
Comparison ACK and non-ACK traffic
Performance Results for a high path loss WBSN
6 Conclusions
3 / 37

4. 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, low
cost, wireless MEMC systems.
Significant progress in wearable
ECG &
and implantable biosensors. Tilt Sensor
SpO2 & IEEE 802.15.4
Motion Sensor
WBSN Applications:
Personal Server
In-vivo monitoring: everyday
healthcare, sports.
Video Games.
Motion
System requirements: Sensors
Network Coordinator
Single hop star topology. Temperature &
Humidity Sensor
Low-power.
Low-cost.
Self-configuring.
4 / 37

5. 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 BSN
technologies is the whether or not they can be integrated with
existing systems, under common standards.”
The novel IEEE 802.15.4 standard is poised to become the global
standard for low data rate, low energy consumption WSN.
5 / 37

6. 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 standard
working 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 IEEE
802.15.4 CAP for acknowledged traffic and under a WBSN
channel.
Evaluate it in terms of energy consumption and throughput.
Compare with ns-2 simulation results.
5 / 37

7. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Outline
1 Motivation and Objectives
Motivation and Objectives
2 State-of-the-Art
MAC design in WBSN
Overview of the sloted IEEE 802.15.4 CAP
3 Analytical Model
Development
Analytical Formulation
4 High Pathloss WBSN
Analysis
Changes in the Analytical Model
5 Results
Initial Considerations
Comparison ACK and non-ACK traffic
Performance Results for a high path loss WBSN
6 Conclusions
6 / 37

8. 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 Collisions
2 Idle listening
3 Overhearing
4 Packet overhead
WBSN MAC design focuses on minimizing energy
consumption.
Contention based protocols: turning radio into sleep state
when it is not needed.
Scheduled based protocols: low duty cycling.
7 / 37

9. 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:
Coordinated
Synchronization through beacon.
Superframe time structure to organize communication.
8 / 37

10. 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:
9 / 37

11. 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
Slotted CSMA
Delay for
random(2BE - 1) unit
NB = 0, CW = 2 backoff periods
Step 1. Init
Battery life
Y
BE = lesser of
Perform CCA on
backoff period
Step 2. Backoff
extension? (2, macMinBE)
N
boundary
Procedure
BE = macMinBE
Channel idle?
Y
Step 3. CCA
N
Locate backoff CW = 2, NB = NB+1, CW = CW - 1
Step 4. ACK
period boundary BE = min(BE+1, aMaxBE)
Example...
N NB> N
macMaxCSMABackoffs CW = 0?
?
Y Y
Failure Success
10 / 37

12. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Outline
1 Motivation and Objectives
Motivation and Objectives
2 State-of-the-Art
MAC design in WBSN
Overview of the sloted IEEE 802.15.4 CAP
3 Analytical Model
Development
Analytical Formulation
4 High Pathloss WBSN
Analysis
Changes in the Analytical Model
5 Results
Initial Considerations
Comparison ACK and non-ACK traffic
Performance Results for a high path loss WBSN
6 Conclusions
11 / 37

13. 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 of
Washington.
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.
12 / 37

14. 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 rate
λ.
No buffering at the nodes.
13 / 37

15. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Analytical Formulation
Markov Chain Model for a Sensing Node
Max number of backoffs/trials to re-access
channel when sensed busy for one packet
Backoff before channel
sensing 1-p1n 1-p2n 1-p3n 1-p4n 1-p5n
BO1 BO2 BO3 BO4 BO5
)
3 n
)
)
2 n
4 n
n)
)
5 n
-p
-p
-p
p1
1-
-p
)(1
)(1
)(1
p(
)(1
c
)
)
)
c
c
2 n
4 n
n
5 n)
-p
c
i
-p
-p
p1n i
i
n p3n p4n
3
p2
-p
-p
1-p p5n
-p
-p
(1
i
-p
(1
(1
)1
)1
(1
1
)1
i|i c (
i|i c (
i|i c)(
i|i c (
p
p
p
p
(1-
(1-
(1-
(1-
IDLE CS11 CS21 CS31 CS41 CS51
pp1n (1-pic)
(1-pic)p2n (1-pic)p3n (1-pic)p4n (1-pic)p5n
n
1
2 n
n
3 n
c )p
4
pic
p
pic pic c )p 5
p
pic pic
)
i|i c
)
i|i c
i|i
-p -p i|
i
-p
-p
(1 (1
(1
(1
ACK CS12 CS22 CS32 CS42 CS52
(1-pi|ic)
pi|ic pi|ic pi|ic pi|ic pi|ic
1
TX
Channel Access failure
Channel must be
sensed idle during
CW=2 consecutive This Markov Chain is solved an equation relating pci and the probability that a
backoff slots node accesses the channel pnt.
14 / 37

16. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Analytical Formulation
Markov Chain Model For the Channel
One and only one node
begins transmission
SUCCESS
β
α 1 Consistent non linear
1 equation system for
NO node begins IDLE,IDLE BUSY,IDLE
transmission pi/i , pic and pt .
c n
which can be solved
δ= 1
1- following numerical
α-
β
FAILURE approximation
techniques.
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.
15 / 37

17. 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
… data ACK idle …
tack_min Lack
(a) Slot timing for the derivation of tsuccess
… collision idle …
tack_max
(a) Slot timing for the derivation of tfailure
0.6 ≤ tack ≤ 1.6 (1)
The presence of acknowledgements makes the time spent in the (ACK) node
state 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 contributed
model.
3 Probabilistic approach to determine the mean time spent on this states. 16 / 37

18. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Analytical Formulation
Performance Metrics
Aggregated throughput:
Relative time spent in the successful channel state.
c
Nπs Nβ
S = = (2)
c
πii + c c
TB,I πbi c c
+ Nπs + Nπf c
1 + TB,I (1 − α) + N(β + δ)
Average power consumption per node:
Relative time spent on transmitting, receiving and idle node states.
n n n n n n n n n
Yav = (pidle − pbeacon + pbo − pir )Yidle + (pcs + pir + pbeacon + pack )Yrx + ptx Ytx (3)
Per node bytes-per-Joule capacity:
(S/M)(250 × 103 /8)
η= (4)
Yav
17 / 37

19. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Outline
1 Motivation and Objectives
Motivation and Objectives
2 State-of-the-Art
MAC design in WBSN
Overview of the sloted IEEE 802.15.4 CAP
3 Analytical Model
Development
Analytical Formulation
4 High Pathloss WBSN
Analysis
Changes in the Analytical Model
5 Results
Initial Considerations
Comparison ACK and non-ACK traffic
Performance Results for a high path loss WBSN
6 Conclusions
18 / 37

20. 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 use
of a lognormal model distribution+shadowing deviation to
determine the node’s communication range:
PL = PdB + Ps = P0,dB + 10nlog (d/d0 ) + tσ
The PL exponent n is varied empirically to match the
measured data.
Ps = tσ is the shadowing component.
√
t = 2erfc −1 [2(1 − p)]
19 / 37

21. 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
20 / 37

22. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Changes in the Analytical Model
New Channel Markov Chain
SUCCESS
)
Pe
1-
β(
α 1
1
IDLE,IDLE BUSY,IDLE
βP 1
e+
δ
FAILURE
Inclusion of the packet loss rate Pe .
21 / 37

23. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Outline
1 Motivation and Objectives
Motivation and Objectives
2 State-of-the-Art
MAC design in WBSN
Overview of the sloted IEEE 802.15.4 CAP
3 Analytical Model
Development
Analytical Formulation
4 High Pathloss WBSN
Analysis
Changes in the Analytical Model
5 Results
Initial Considerations
Comparison ACK and non-ACK traffic
Performance Results for a high path loss WBSN
6 Conclusions
22 / 37

24. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Initial Considerations
Flow diagram to Obtain Results
Analytical Init Simul Init
Config Script
Seed Value
.tcl
Matlab Topology Analyzer script
.scn ns-2 .awk
Nam File Trace File gawk Output Data
NAM .nam .tr .txt
Analyzer
Solution Topology Animator Performance Graphs Matlab
23 / 37

25. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Initial Considerations
Parameters Used
aMinBE = 3 aMaxBE = 5
CSMA/CA parameters macMaxCSMABackoffs = 5 CW = 2
BCO = 6 SFO = 6
Analytical parameters n
pbeacon = 1/3072
Data Packet size N = Ldata = 10backoffslots nbeacon = 2backoffslots
Number of sensing Nodes M = 12
24 / 37

26. 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
25 / 37

27. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Comparison ACK and non-ACK traffic
Throughput
0
10 14
Analytical ACK
Simulation ACK 12
Analytical NO ACK
Simulation NO ACK
10
% change in throughput
Channel throughput, S
8
−1
10
6
4
2
−2
10 0
−3 −2 −1 0 −3 −2 −1 0
10 10 10 10 10 10 10 10
Per packet arrival rate λ [packet per packet duration] Per packet arrival rate λ [packet per packet duration]
Excellent accuracy of our analytical model capturing throughput
performance.
26 / 37

28. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Comparison ACK and non-ACK traffic
ns-2 Overhearing Bug
2
10
Analytical NO ACK
Simulation NO ACK
Per−node power consumption, Yav [mW]
1
10
0
10
−1
10
−3 −2 −1 0
10 10 10 10
Per packet arrival rate λ [packet per packet duration]
Figure: Per node power consumption
27 / 37

29. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Comparison ACK and non-ACK traffic
ns-2 Overhearing Bug
2 2 2
10 10 10
Analytical NO ACK Analytical NO ACK
Analytical NO ACK
Per−node Idle power consumption, Yidle [mW]
Simulation NO ACK
,Per−node Rx power consumption,Yrx [mW]
Simulation NO ACK
Per−node Tx power consumption,Ytx [mW]
Simulation NO ACK
1 1
10 10
1
10
0 0
10 10
0
10
−1 −1
10 10
−2 −2 −1
10 10 10
−3 −2 −1 0 −3 −2 −1 0 −3 −2 −1 0
10 10 10 10 10 10 10 10 10 10 10 10
Per packet arrival rate λ [packet per packet duration] Per packet arrival rate λ [packet per packet duration] Per packet arrival rate λ [packet per packet duration]
Simulation Rx energy increases.
Simulation Idle energy decreases.
27 / 37

30. 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
1
10 7
Analytical ACK
Analytical NO ACK 6
% change in per node power consumption
Per−node power consumption, Yav [mW]
5
4
3
2
1
0
10
0
−3 −2 −1 0 −3 −2 −1 0
10 10 10 10 10 10 10 10
Per packet arrival rate λ [packet per packet duration] Per packet arrival rate λ [packet per packet duration]
The inclusion of the ACK increases energy consumption.
28 / 37

31. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Comparison ACK and non-ACK traffic
Bytes per Joule capacity
Bytes per Joule capacity comparison
16
Analytical ACK
Analytical NO ACK 14
% change in bytes−per−Joule capacity
Bytes per Joule capacity, η [KB/J]
12
10
8
6
4
2
10
2
0
−3 −2 −1 0 −3 −2 −1 0
10 10 10 10 10 10 10 10
Per packet arrival rate λ [packet per packet duration] Per packet arrival rate λ [packet per packet duration]
The optimal energy-throughput trade off, archived for a datarate of
λ = 0.04 = 10kbps
29 / 37

32. 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
Throughput comparison WBSN channel with LOS
0
10
Channel throughput, S
−1
10
Analytical ACK Pe=0%
Analytical ACK Pe=5%
Simulation ACK Pt=1mW
Simulation ACK Pt=0.1mW
−2
10
−3 −2 −1 0
10 10 10 10
Per packet arrival rate λ [packet per packet duration]
Figure: Throughput comparison WBSN channel with LOS
30 / 37

33. 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
LOS channel
1
10
Analytical ACK Pt=1mW
Analytical ACK Pt=0.1mW
Per−node power consumption, Yav [mW]
0
10
−3 −2 −1 0
10 10 10 10
Per packet arrival rate λ [packet per packet duration]
Figure: Per-node power consumption in LOS channel
31 / 37

34. 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
Throughput comparison BSN channel with NLOS
0
10
Channel throughput, S
−1
10
Simulation ACK Pt=1mW
Simulation ACK Pt=0.32mW
Analytical ACK Pe=0%
Analytical ACK Pe=5%
−2
10
−3 −2 −1 0
10 10 10 10
Per packet arrival rate λ [packet per packet duration]
Figure: Throughput comparison WBSN channel with NLOS
32 / 37

35. 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 becomes
dominant, and collapses our model.
33 / 37

36. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Outline
1 Motivation and Objectives
Motivation and Objectives
2 State-of-the-Art
MAC design in WBSN
Overview of the sloted IEEE 802.15.4 CAP
3 Analytical Model
Development
Analytical Formulation
4 High Pathloss WBSN
Analysis
Changes in the Analytical Model
5 Results
Initial Considerations
Comparison ACK and non-ACK traffic
Performance Results for a high path loss WBSN
6 Conclusions
34 / 37

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/CA
procedure in the CAP of the IEEE 802.15.4 standard to
acknowledged traffic.
The validity of the analytical model has been demonstrated
comparing with simulation results.
For the purpose of conducting near realistic simulations, the
Chipcon CC2420 IEEE 802.15.4 transceiver energy parameters
have been used.
The results of the analytical model resolution have been then
employed to predict throughput and energy consumption.
We have uncovered one of the main problems of using IEEE
802.15.4 in a human body environment: hidden node problem
⇒ multihop topology or the use of relays could be more
suited.
35 / 37

38. 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 for
WBSN applications that have timing constraints.
Use a multi-hop topology strategy to solve energy issues.
Study other sophisticated channel models available in the
literature to perform different evaluations and contrast studies.
36 / 37

39. Motivation and Objectives State-of-the-Art Analytical Model High Pathloss WBSN Results Conclusions
Questions?
Thank you for your attention!
37 / 37