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
Presentation Outlines
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•
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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
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•
•
•
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
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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
ni (i  1...m)
Design Considerations
• Node Price
{Perc(n )  [(1  PathLossRate(n ))  (1  HopLossRat e(n ))  NP(n )  1]}
NP( n ) 
{Perc(n )  [(1  PathLossRate(n ))  (1  HopLossRat e(n ))]}
i
i
i
i
i
i
i
i
i
NP(x): Node price of X
ni (i  1...m) = node n’s downstream neighbors
Perc(i): the percentage of traffic that is routed to node i
HopLossRat e(ni ) The hop loss rate between node n and node i
PathLossRate()The loss rate of the path from node i to the sink
PathLossRate(n)  1  {Perc(i )  [(1  PathLossRate(ni ))  (1  HopLossRat e(ni ))]}
i
Sink
NP(sink) = 0
PathLossRate(Sink) = 0
PathLossRate(2)
PathLossRate(3)
2
NP(3)
NP(2)
3
HopLossRate(2)
HopLossRate(3)
Perc(3)
Perc(2)
1
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
802.11 MAC)
– reasonable to estimate the packet loss rate based on
an exponential weighted moving average (EWMA)
estimation approach.
~
HopLossRat e(m)    HopLossRat e(m  1)  (1   ) L (m)
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)
2
NP(3)
NP(2)
3
HopLossRate(2)
HopLossRate(3)
Perc(3)
Perc(2)
1
Design Considerations
• Routing Schemes: Oscillation Avoidance
Perchigher 
NPhigher  NPlowest
NPhigher
Analysis
• Routing Schemes: Oscillation Avoidance
– Gradually shift traffic to best path
– Adaptive to downstream dynamics
Perchigh 
NPhigh  NPlow
NPhigh
2
NP(3)
NP(2)
3
HopLossRate(2)
HopLossRate(3)
Perc(3)
Perc(2)
1
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
Application
Application
Rate adjustment
Rate adjustment
feedback
Sensor Data
& Source NP
FBRT
FBRT
Node
Sensor
Data
FBRT
Encapsulate
my NP into
data packets
The Sink
Source
Presentation Outlines
• 1. Introduction
• 2. Motivations and Design Considerations
• 3. Protocol Implementation
• 4. Simulation
• 5. Conclusion
Results
Simulation results
• Coding FBRT over NS-2
– Setting of the network
Area of sensor field
1500m*1500m
Number of sensor nodes
100
MAC
IEEE 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
– Scheme 1: Based on directed diffusion with ESRT scheme. (*)
– Scheme 2: FBRT (o)
Simulation results
• Simulation Network
Energy consumed of the WSN (J)
Simulation results
• Results
Simulation results
• Results
Presentation Outlines
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•
•
•
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.
• Thank You