PFC_Analysis of IEEE 802.15.4 in WBSN

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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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PFC_Analysis of IEEE 802.15.4 in WBSN

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

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