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16/19/2015 EFFICIENT PARKING METER MANAGEMENT SYSTEM APRIL 26, 2006 STEPHEN DABIDEEN YIZENIA MORA ADVISORS: DR. ROCH GUERIN AND DR. SALEEM KASSAM
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26/19/2015 Project Overview Assumptions City-wide wireless network Parking meters with wireless and sensing capabilities Goal Get information about the meters’ status to a central office Objectives Design and implement communication protocol Evaluation metrics: reliability and energy efficiency
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36/19/2015 Central Station
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46/19/2015 Statement of Problem
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56/19/2015 Hardware
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6 Hardware
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7 Head Meter Rotation Goal: maximize the life of the system Transmitter with two levels of power Evenly distribute role of head meter Option 1: fixed, predefined rotationOption 1: fixed, predefined rotation Option 2: dynamically determined rotationOption 2: dynamically determined rotation Pick the neighbor with highest battery level
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86/19/2015 SAFE Goal Reliably and Efficiently route information to the current head meter Routing table Local Next hop A function of distance and reliability Link Quality Additive Increase Multiplicative decrease Synchronization Store & Forward - single transmission per cycle
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96/19/2015 Single-Path, Best-Effort Routing Data sent to best next hop and forwarded if received
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106/19/2015 Single-Path, Best-Effort Routing Packets lost due to collisions Data loss cumulative Data Missed
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116/19/2015 Cost to send a packet of size b (b = 8): Energy = 1.9 * b + 266 μJ Incremental cost fixed cost Incremental cost fixed cost Cost to send x times: Energy = [1.9*b + 266]*x μJ Cost to send through x Paths Since data piggy-backs on other packets:Since data piggy-backs on other packets: Energy = [1.9*b]*x + 266 μJ Multi-Transmission vs. Multi-Path
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126/19/2015 Full Multi-Path Routing Improves reliability More paths = More energy Data Missed
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136/19/2015 SAFE Synchronized Adaptive-Forwarding Efficient Routing Protocol Defines two types of paths Primary: Deterministic Best-Effort Secondary: Probabilistic Central station provides feedback Adaptive-Forwarding: Probability Matrix used to create secondary paths as needed Synchronization
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146/19/2015 Probabilistic Multi-Path Routing Reduces redundancy without sacrificing reliability Uses multi-path only when needed Primary Path Secondary Path
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156/19/2015 Probabilistic Multi-Path Routing Primary Path Secondary Path Fewer Paths, Same level of reliability
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166/19/2015 The SAFE Probability Matrix 3-D matrix Meter, Current Head Meter, ProbabilityMeter, Current Head Meter, Probability Determination Proactive ResponseProactive Response Long term, time-of-day variations Reactive ResponseReactive Response Temporary, unpredicted periods of unreliability User chooses tradeoff Reliability vs. energy consumptionReliability vs. energy consumption
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176/19/2015 Failure Recovery Loss of a head meter Transient loop => count to infinityTransient loop => count to infinity Loss of a non-head meter Link Quality decreasesLink Quality decreases Fragmentation Head meter in each groupHead meter in each group Defragmentation Single head meterSingle head meter
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186/19/2015 Experimental Results Energy calculations for transmitting and receiving only Group of 6 meters Routing Type Reliability (% data loss) Energy Consumption (J/cycle) Best-Effort, Single Path 17.70.00600 SAFE: 10% response 3.70.00601 SAFE: 30% response 2.00.00606 Full Multi-Path 1.40.00617
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196/19/2015 Conclusion Goal and Objectives SAFE routing protocol Two types of paths: primary and secondary Probabilities determined by the central station Allows the user to trade reliability for energy efficiency Designed for our project but easily adaptable
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206/19/2015 Acknowledgements Prof. Roch Guerin (Advisor) Prof. Saleem Kassam (Advisor) Prof. CJ Taylor (Instructor) Prof. Ken Laker (Instructor) Mr. Phil Farnum (Instructor) Mr. Sid Deliwala (Gismos & Gadgets) TCOM Lab (StarEast Boards) CIS & ESE Departments (Funding)
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