FBRT: A Feedback-Based FBRT: A Feedback-Based Reliable Transport Protocol Reliable Transport Protocol

for Wireless Sensor Networksfor Wireless Sensor Networks

Yangfan ZhouYangfan Zhou

November, 2004November, 2004

Supervisors: Dr. Michael Lyu and Dr. Jiangchuan LiuSupervisors: Dr. Michael Lyu and Dr. Jiangchuan Liu

11stst Year MPhil Presentation Year MPhil Presentation

Presentation OutlinesPresentation Outlines

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

Presentation OutlinesPresentation Outlines

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

IntroductionIntroduction

• 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.

IntroductionIntroduction• 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

IntroductionIntroduction

• 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.

IntroductionIntroduction

• 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

IntroductionIntroduction• Reliable sensor-to-sink data transport for WSN

Bias the transport scheme

IntroductionIntroduction• 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

IntroductionIntroduction

– 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

IntroductionIntroduction

– 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 OutlinesPresentation Outlines

• 1. Introduction

• 2. Design Considerations• 3. Protocol Implementation• 4. Simulation Results• 5. Conclusion

MotivationsMotivations

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

Design ConsiderationsDesign 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 ConsiderationsDesign Considerations

• Distortion and Sensor Contribution– Application Specific, should be determined by

applications.

• Rate Control– Cooperation of the application and the

transport protocol.

Figure

Design ConsiderationsDesign 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 ConsiderationsDesign Considerations• Node Price

NP(x): Node price of X = node n’s downstream neighborsPerc(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

}))](1())(1[()({

]}1)())(1())(1[()({)(

iiii

ii

iii

neHopLossRatntePathLossRanPerc

nNPneHopLossRatntePathLossRanPercnNP

)...1( mini

)...1( mini

)( ineHopLossRat

)(tePathLossRa

}))](1())(1[()({1)(

i

ii neHopLossRatntePathLossRaiPercntePathLossRa

Perc(2)

2

3

Perc(3)1

PathLossRate(2)

PathLossRate(3)

HopLossRate(2)HopLossRate(3)

NP(3)NP(2)

Sink

NP(sink) = 0PathLossRate(Sink) = 0

Design ConsiderationsDesign 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 ConsiderationsDesign 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.

)(~

)1()1()( mLmeHopLossRatmeHopLossRat

Design ConsiderationsDesign 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 ConsiderationsDesign 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 ConsiderationsDesign Considerations

• Routing Schemes: Oscillation Avoidance

AnalysisAnalysis• Routing Schemes: Oscillation Avoidance

– Gradually shift traffic to best path– Adaptive to downstream dynamics

higher

lowesthigherhigher NP

NPNPPerc

high

lowhighhigh NP

NPNPPerc

Perc(2)

2

3

Perc(3)1

HopLossRate(2)HopLossRate(3)

NP(3)NP(2)

Presentation OutlinesPresentation Outlines

• 1. Introduction• 2. Motivations and Design Considerations

• 3. Protocol Implementation• 4. Simulation Results• 5. Conclusion

Protocol ImplementationProtocol 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 ImplementationProtocol Implementation

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

Protocol ImplementationProtocol 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 ImplementationProtocol Implementation• Feedback of newly desired reporting rates

FBRT

Application

Sensor Data& Source NP

Rate adjustmentfeedback

The Sink

FBRT

Node

FBRT

Encapsulate my NP into data packets

Rate adjustment Sensor Data

Application

Source

Presentation OutlinesPresentation Outlines

• 1. Introduction• 2. Motivations and Design Considerations• 3. Protocol Implementation

• 4. Simulation Results• 5. Conclusion

Simulation resultsSimulation 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 field 1500m*1500m

Number of sensor nodes 100

MACIEEE 802.11 without

CTS/RTS and ACK

Radio power 0.2818

Packet length 36 bytes

Transmit Power 0.660 W

Receive Power 0.395 W

Feedback interval 1 second

IFQ length 50 packets

Simulation Time 1000 seconds

Simulation resultsSimulation results• Simulation Network

Simulation resultsSimulation results

• Results

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cons

umed

of

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Simulation resultsSimulation results• Results

Presentation OutlinesPresentation Outlines

• 1. Introduction• 2. Motivations and Design Considerations• 3. Protocol Implementation• 4. Simulation Results

• 5. Conclusion

ConclusionConclusion• 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.

• Thank You