Impact of Radio Irregularity on Wireless Sensor Networks

1. Impact of Radio Irregularity onWireless Sensor Networks Gang Zhou, Tian He, Sudha Krishnamurthy, John A. Stankovic Computer Science Department,University of Virginia June 2004

2. Outline • Motivation, State of Art and Contributions • Analyze Radio Irregularity • Radio Irregularity Model (RIM) • Impact on Routing and MAC Layer • Solutions for Radio Irregularity • Conclusion and Future Work

3. Motivation • Evidence of radio irregularity of low power wireless devices in physical environment • Need for models to regenerate radio irregularity in simulations • Need for better protocols to address irregularity in running systems

4. State of Art • Spherical radio range assumption in current research • Localization, Sensing Coverage, Topology Control • Experiments Related to Radio Irregularity • Deepak Ganesan, etc., “Complex Behavior at Scale: An Experimental Study of Low-Power Wireless Sensor Networks” , UCLA/CSD-TR 02-0013, 2002 • Alberto Cerpa, etc., “SCALE: A Tool for Simple Connectivity Assessment in Lossy Environments”, CENS-TR 03-0021, 2003 • Jerry Y. Zhao, etc., “Understanding Packet Delivery Performance in Dense Wireless Sensor Network”, ACM SenSys, 2003 • Alec Woo, etc., “Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks”, ACM SenSys, 2003 • DOI Concept (our previous work) • Tian He, etc., “Range-Free Localization Schemes in Large Scale Sensor Networks”, MobiCom, 2003

5. Contributions • RIM: a new radio energy model that considers irregularity • Implemented in GlomoSim • Review the impact of radio irregularity on • MAC layer • Routing layer • Solutions to deal with radio irregularity • Symmetric Geographic Forwarding • Bounded Distance Forwarding • Bidirectional Flooding • Learning Function • RTS Broadcast • High Energy Asymmetry Detection

6. Motivation, State of Art and Contributions • Analyze Radio Irregularity • Radio Irregularity Model (RIM) • Impact on Routing Layer • Impact on Routing and MAC Layer • Solutions for Radio Irregularity • Conclusion and Future Work

7. Figure 1: Signal Strength over Time in Four Directions Radio signal properties - 1 • Non-isotropic Path Loss:The radio signal from a transmitter has different path losses in different directions.

8. Figure 2: Signal Strength Values in Different Directions Non-isotropic Path Loss • Reasons: • Reflection, diffraction and scattering in environment • Hardware calibration differences (non-isotropic antenna gain)

9. Figure 2: Signal Strength Values in Different Directions Radio signal properties - 2 • Continuous variation:The signal path loss varies continuously with incremental changes of the propagation direction from a transmitter.

10. (a) One mote with different battery status (b) Different motes with the same battery status Radio signal property - 3 • Heterogeneity:Different nodes have different signal sending powers • Reasons: • Different battery status • Different hardware calibration

11. Motivation, State of Art and Contributions • Contributions • Analyze Radio Irregularity • Radio Irregularity Model (RIM) • Impact on Routing Layer • Impact on Routing and MAC Layer • Solutions for Radio Irregularity • Conclusion and Future Work

12. Figure 4: Degree of Irregularity RIM - DOI • Degree of Irregularity (DOI): • Definition: the maximum received signal strength percentage variation per unit degree change in the direction of radio propagation. • Account for non-isotropic path loss

13. RIM - VSP • Variance of Sending Power (VSP): • Definition: the maximum percentage variance of the signal sending power among different devices. • Account for heterogeneous sending power

14. Signal receiving power = signal sending power – DOI adjusted path loss + fading DOI adjusted path loss = path loss* KD Signal receiving power = VSP adjusted signal sending power – DOI adjusted path loss + fading VSP adjusted signal sending power = RIM – propagation formula Signal receiving power = signal sending power - path loss + fading

15. Motivation, State of Art and Contributions • Analyze Radio Irregularity • Radio Irregularity Model (RIM) • Impact on Routing and MAC Layer • Solutions for Radio Irregularity • Conclusion and Future Work

16. Figure 6: Route Discovery Using Multi-Round Technique Figure 5: Impact on Path-Reversal Technique Analyze the Impact • Impact on: • Path-Reversal technique • Multi-Round technique • Used in AODV, DSR, LAR

17. Figure 7: Impact on Neighbor Discovery Technique Analyze the Impact • Impact on: • Neighbor-Discovery technique • Used in GF, GPSR, SPEED

18. Simulation Configuration

19. Increase DOI Increase VSP E2E Loss Ratio • GF has rapidly increasing E2E loss ratio • AODV and DSR have low E2E loss ratio

20. Increase DOI Increase VSP Average E2E Delay • GF has constant E2E delay • AODV and DSR have increasing E2E delay

21. Increase DOI Increase VSP # of Control Packets • GF has constant # of control packets • AODV and DSR have increasing # of control packets

22. Increase DOI Increase VSP Energy Consumption • GF has decreasing energy consumption • AODV and DSR increasing energy consumption

23. Motivation, State of Art and Contributions • Analyze Radio Irregularity • Radio Irregularity Model (RIM) • Impact on Routing and MAC Layer • Solutions for Radio Irregularity • Conclusion and Future Work

24. Solutions • Symmetric Geographic Forwarding • Bounded Distance Forwarding • Bidirectional Flooding • Learning Function • RTS Broadcast • High Energy Asymmetry Detection • Symmetric Geographic Forwarding • Detect and block asymmetric channels • Only use symmetric channels for geographic forwarding • Implementation: Add all neighbors’ IDs in beacon messages • Optimization: estimate the channel quality statistically • Currently implemented in a tracking system [MobiSys 2004]

25. Increase DOI Increase VSP SGF --- E2E Loss Ratio • SGF has constantly low E2E loss ratio

26. Increase DOI Increase VSP SGF --- Average E2E Delay • SGF has almost constant E2E delay

27. Increase DOI Increase VSP SGF --- # of Control Packets • SGF has the same # of control packets as that of GF

28. Increase DOI Increase VSP SGF --- Energy Consumption • SGF has a little increasing energy consumption

29. Figure 7: Percentage of Reporting Nodes Bounded Distance Forwarding • Bounded Distance Forwarding restricts the distance over which a node can forward a message in a single hop. • An add-on rule • Tested in a running system with 60 MICA2 motes

30. Motivation, State of Art and Contributions • Analyze Radio Irregularity • Radio Irregularity Model (RIM) • Impact on Routing and MAC Layer • Solutions for Radio Irregularity • Conclusion and Future Work

31. Conclusion - 1 • The first effort to bridge the gap: • between isotropic radio energy models assumed by most simulators in WSN and the real non-isotropic radio properties

32. Conclusion - 2 • Review the impact of radio irregularity on Routing and MAC layers • Radio irregularity has a greater impact on the routing layer than on the MAC layer. • Routing protocols, such as AODV and DSR, that use multi-round discovery technique, can deal with radio irregularity, but with high overhead. • Routing protocols, such as geographic forwarding, which are based on neighbor discovery technique, are severely affected by radio irregularity. • Solutions for radio irregularity • SGF has as low loss ratio as that of AODV and DSR, but much lower control overhead and energy consumption.

33. Future work • To evaluate and further refine the RIM model • Experiments in more types of environments • Experiments with different types of devices and different types of antennas • Radio pattern variation with system aging and environment changes • Analyze the impact of radio irregularity on other protocols • Localization, Sensing Coverage, Topology Control • Analyze and evaluate the remaining four solutions • Bidirectional Flooding • Learning Function • RTS Broadcast • High Energy Asymmetry Detection

34. Thanks to the MobiSys Shepherd and anonymous reviewers for their valuable criticisms! The End!