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´ ıa de Se˜ nal y Comunicaciones Universidad Carlos III de Madrid Legan´ es, May 21, 2009 1 / 37
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.
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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
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
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
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