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

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

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

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.

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

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.

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

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

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

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

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.

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

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

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.

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

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

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

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

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)

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 MAC) –reasonable to estimate the packet loss rate based on an exponential weighted moving average (EWMA) estimation approach.

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

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

Design Considerations Routing Schemes: Oscillation Avoidance

Analysis –Gradually shift traffic to best path –Adaptive to downstream dynamics Perc(2) 2 3 Perc(3) 1 HopLossRate(2) HopLossRate(3) NP(3) NP(2)

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

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

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

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.

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

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

Simulation results Coding FBRT over NS-2 –Setting of the network –Scheme 1: Based on directed diffusion with ESRT scheme. (*) –Scheme 2: FBRT (o) Area of sensor field1500m*1500m Number of sensor nodes100 MAC IEEE without CTS/RTS and ACK Radio power Packet length36 bytes Transmit Power0.660 W Receive Power0.395 W Feedback interval1 second IFQ length50 packets Simulation Time1000 seconds

Simulation results Simulation Network

Simulation results Results Energy consumed of the WSN (J)

Simulation results Results

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

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.

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