FBRT: A Feedback-Based Reliable Transport Protocol for Wireless Sensor Networks

1. 1st Year MPhil Presentation FBRT: A Feedback-Based Reliable Transport Protocol for Wireless Sensor Networks Yangfan Zhou November, 2004 Supervisors: Dr. Michael Lyu and Dr. Jiangchuan Liu

2. Presentation Outlines • 1. Introduction • 2. Design Considerations • 3. Protocol Implementation • 4. Simulation Results • 5. Conclusion

3. Presentation Outlines • 1. Introduction • 2. Design Considerations • 3. Protocol Implementation • 4. Simulation Results • 5. Conclusion

4. Introduction • Wireless Sensor Networks (WSN) • Sensors nodes measure physical phenomena. • Target tracking • Environment data measurement • Engineering measurement • Sensor nodes form an ad-hoc multi-hop wireless network to convey data to a sink.

5. Introduction • WSN Challenges • WSN suffers from energy constraint • WSN condition • Unreliable wireless link • High packet loss rate • Network Dynamics • Node failures • Link failures • Dynamic traffic load

6. Introduction • Reliable sensor-to-sink data transport for WSN • It is Important • Objective • to assure that the sink can receive desired information is very important. • The work presented here is to address this problem.

7. Introduction • Reliable sensor-to-sink data transport for WSN • 100% reliable data transport is not necessary. • Reliability means desired information has been achieved • Source sensors might have different contributions

8. Introduction • Reliable sensor-to-sink data transport for WSN Bias the transport scheme

9. Introduction • Current Approaches on WSN data transport • RMST: Reliable Multi-Segment Transport by Heidemann et al, SNPA’03 • PSFQ: Pump Slowly, Fetch Quicklyby C. Wan et al, WSNA’02 Not applicable for sensor-to-sink data transport

10. Introduction • ESRT: Event to Sink Reliable Transport by Sankarasubramaniam et al, MobiHoc’03 • Congestion detection • Queue Length • Reliability consideration • Receiving rate of the incoming packets • Rate adjustment • Unbiased adjustment

11. Introduction • CODA: Congestion Detection and Avoidance by C. Wan, SenSys'03,    • Congestion detection • channel sampling • Congestion avoidance • Slowing down the sending rate • It has not addressed the reliability issues.

12. Presentation Outlines • 1. Introduction • 2. Design Considerations • 3. Protocol Implementation • 4. Simulation Results • 5. Conclusion

13. Motivations • Issues to be addressed to provide reliable sensor-to-sink data transport • Source reporting rate adjustment scheme • Routing scheme

14. Design Considerations • Reporting Rate Control • Relationship between receiving rates and distortion • Different contributions of source nodes. • Different energy costs for communication. • Rate control scheme should employ an optimization approach to minimize energy consumption of the WSN. • Adjust the rates so that energy consumption is minimized subjected to that the distortion is in a given range.

15. Design Considerations • Distortion and Sensor Contribution • Application Specific, should be determined by applications. • Rate Control • Cooperation of the application and the transport protocol. Figure

16. Design Considerations • Communication cost estimation • Hop number from the source to the sink • Simple • Inaccurate • Node Price • Our metrics: Total number of packets sent by the in-network nodes for per packet received by the sink • Accurate • Physical layer overhead • But hard to implement

17. Design Considerations • Node Price NP(x): Node price of X = node n’s downstream neighbors Perc(i): the percentage of traffic that is routed to node i The hop loss rate between node n and node i The loss rate of the path from node i to the sink

18. NP(sink) = 0 PathLossRate(Sink) = 0 Sink PathLossRate(2) PathLossRate(3) 2 NP(2) NP(3) 3 HopLossRate(2) HopLossRate(3) Perc(3) Perc(2) 1

19. Design Considerations • Node Price Estimation • Each node can calculate its NP and PathLossRate based on • The feedback of NP and PathLossRate of its downstream neighbors • The HopLossRate to each of its downstream neighbors • The routing scheme: Perc(i) • Two unknowns • The HopLossRate • The routing scheme (Discussed Later)

20. Design Considerations • Hop Loss Rate • mainly caused by three factors • Congestion • Signal Interference • Fading. • packet loss rate will exhibit graceful increasing behavior as the communication load increases (IEEE 802.11 MAC) • reasonable to estimate the packet loss rate based on an exponential weighted moving average (EWMA) estimation approach.

21. Design Considerations • Accurate and Current Hop Loss Rate Estimation • Indicates the congestion condition well • Indicates the weak link well • Node Price: based on loss rate estimation • Indicates the dynamic wireless communication condition from the node to the sink well • can help to determine the reporting rates • can help to determine the routing scheme

22. Design Considerations • Routing Schemes • Minimizing local NP. • Locally optimal energy consumption, minimizing the energy consumed for the sink to receive per packet from me) 2 NP(2) NP(3) 3 HopLossRate(2) HopLossRate(3) Perc(3) Perc(2) 1

23. Design Considerations • Routing Schemes: Oscillation Avoidance

24. Analysis • Routing Schemes: Oscillation Avoidance • Gradually shift traffic to best path • Adaptive to downstream dynamics 2 NP(2) NP(3) 3 HopLossRate(2) HopLossRate(3) Perc(3) Perc(2) 1

25. Presentation Outlines • 1. Introduction • 2. Motivations and Design Considerations • 3. Protocol Implementation • 4. Simulation Results • 5. Conclusion

26. Protocol Implementation • Task assignment: Broadcast interest packet • Get possible downstream neighbor information • Select path with the lowest hop number to the sink as tentative best path • Low reporting rate requirement tentatively

27. Protocol Implementation • Link loss rate estimation • Measured according to packet serial numbers holes • Estimated with an EWMA approach.

28. Protocol Implementation • Feedback of communication condition • Checking the following parameters in a given interval • A node’ NP • A node’s path loss rate to the sink • Link loss rate from upstream neighbors • If they are changed, feed back the new value to upstream nodes • higher priority.

29. Protocol Implementation • Feedback of newly desired reporting rates Application Application Rate adjustment Sensor Data Rate adjustment feedback Sensor Data & Source NP FBRT FBRT FBRT Node Encapsulate my NP into data packets The Sink Source

30. Presentation Outlines • 1. Introduction • 2. Motivations and Design Considerations • 3. Protocol Implementation • 4. Simulation Results • 5. Conclusion

31. Simulation results • Coding FBRT over NS-2 • Setting of the network • Scheme 1: Based on directed diffusion with ESRT scheme. (*) • Scheme 2: FBRT (o)

32. Simulation results • Simulation Network

33. Simulation results • Results Energy consumed of the WSN (J)

34. Simulation results • Results

35. Presentation Outlines • 1. Introduction • 2. Motivations and Design Considerations • 3. Protocol Implementation • 4. Simulation Results • 5. Conclusion

36. Conclusion • we propose FBRP, a feedback-based protocol to address reliable sensor-to-sink data transport issue • FBRP optimizes the energy consumptions with two schemes. • the sink's rate control scheme that feeds back the optimal reporting rate of each source. • the locally optimal routing scheme for in-network nodes according to the feedback of downstream communication conditions. • Simulation results verify its effectiveness for reducing energy consumption.

37. Thank You