Data Preference Matters - Cyber

Data Preference Matters:
A New Perspective of Safety Data Dissemination
in Vehicular Ad Hoc Networks
Qiao Xiang1 , Xi Chen1 , Linghe Kong1 , Lei Rao2 and Xue Liu1
1 School
of Computer Science, McGill University
Motors Research Lab
2 General
April 29th, 2015
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Introduction
Outline
1
Introduction
2
Quantifying Data Preferences
3
PVCast: a Packet-Value-Based Dissemination Protocol
4
Performance Evaluation
5
Conclusion and Future Work
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Introduction
Background
Introduction
Vehicular Ad Hoc Networks
Communication infrastructure for Intelligent
Transportation Systems (ITS)
Operate in a dynamic environment
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Introduction
Background
Introduction
Safety Data Dissemination
Crucial for vehicle safety
Contain periodic routine data and event-driven emergency
data
More emphasis on QoS, e.g., small delay and high
coverage
(a) Collision Avoidance
(b) Lane Change
Sources:www.gm.com and www.Mercedes-Benz.com
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Introduction
Background
Data Preferences
When collecting safety data, vehicles have
preferences on
Closer, Newer and More important data
Related works do not consider these preferences
Counter-Based Dissemination
Farthest-First Dissemination
Probabilistic Forwarding
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Introduction
Our Focus
Our Focus
Quantifying data preferences
Designing lightweight distributed dissemination
protocol
Satisfying data preferences of all the vehicles
Understanding system benefits
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Introduction
Our Focus
Outline
1
Introduction
2
Quantifying Data Preferences
3
PVCast: a Packet-Value-Based Dissemination Protocol
4
Performance Evaluation
5
Conclusion and Future Work
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Quantifying Data Preferences
Outline
1
Introduction
2
Quantifying Data Preferences
3
PVCast: a Packet-Value-Based Dissemination Protocol
4
Performance Evaluation
5
Conclusion and Future Work
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Quantifying Data Preferences
Data Preferences
Vehicles show the following preferences when
collecting safety data:
Spatial preference: the closer, the better;
Temporal preference: the newer, the better;
Type preference: the more important, the better.
Quantify these preferences on a per-packet level
Packet Value = Spatial Value×Temporal Value×Type Value.
Given a packet p, its packet-value for vehicle v :
PVv (p) = Sv (p) · Tv (p) · Wp .
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Quantifying Data Preferences
Spatial-Value Function
Given a data packet p, its spatial-value
decreases as p is disseminated away from its
origin;
becomes zeros after p exceeds the Range of
Interest.
Figure: Region of Interest
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Quantifying Data Preferences
Spatial-Value Function
Sv(p)
Range of Interest
0
Distance
Figure: Spatial-Value vs. Dissemination Distance.
Sv (p) =
max(α − βdpv , 0), if vehicle v moves towards (xp , yp )
0
otherwise.
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Quantifying Data Preferences
Temporal-Value Function
Collecting real-time data is crucial for safety
applications;
New packets have much higher temporal-value
than old ones;
Figure: New data should be disseminated first.
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Quantifying Data Preferences
Temporal-Value Function
Temporal-value decreases as time elapses;
The decreasing speed becomes slower with time;
Old packets still have value, e.g., for statistic
analysis.
Tv(p)
Tv (p) = e −µtypep te (p) .
Emergency Message
Routine Message
0
Elapsed Time
Figure: Temporal-Value vs. Elapsed Time.
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Quantifying Data Preferences
Type-Value Function
Emergency messages are more important than
routine messages.
Wp
Emergency Message
Routine Message
0
Figure: Type-Value vs. Message Types.
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Quantifying Data Preferences
Quantifying Data Preferences
Putting pieces together,
PVv (p) = Sv (p) · Tv (p) · Wp .
Packet-value data preference: Given any two
packets p1 and p2 , vehicle v always has a higher
data preference to p1 over p2 if PVv (p1 ) > PVv (p2 ).
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PVCast: a Packet-Value-Based Dissemination Protocol
Outline
1
Introduction
2
Quantifying Data Preferences
3
PVCast: a Packet-Value-Based Dissemination Protocol
4
Performance Evaluation
5
Conclusion and Future Work
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PVCast: a Packet-Value-Based Dissemination Protocol
PVCast in A Nutshell
PVCast in A Nutshell
A new packet p
Packet Value
Update
No
PVA(p)=0
1-Hop Dissemination Utility
Computation
Probabilistic Broadcast Test
Fail
Discard packet
Contention Window Size
Assignment
Broadcast
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PVCast: a Packet-Value-Based Dissemination Protocol
1-Hop Dissemination Utility
1-Hop Dissemination Utility
Utility = Packet Value × Effective Dissemination Coverage.
Effective Dissemination Coverage
U
A
edcA (p) = 5 − 2 = 3
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PVCast: a Packet-Value-Based Dissemination Protocol
Probabilistic Broadcast Test
Probabilistic Broadcast Test
Broadcast Probability
Piecewise function of dissemination utility
Higher dissemination utility
→ Higher chance for broadcasting
0
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Dissemintation Utility
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PVCast: a Packet-Value-Based Dissemination Protocol
Contention Window Size Assignment
Contention Window Size Assignment
Minimum CW Size
Piecewise function of dissemination utility
Higher dissemination utility
→ Smaller minimum CW size
→ Higher priority to get channel access
0
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Dissemintation Utility
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Performance Evaluation
Outline
1
Introduction
2
Quantifying Data Preferences
3
PVCast: a Packet-Value-Based Dissemination Protocol
4
Performance Evaluation
5
Conclusion and Future Work
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Performance Evaluation
Simulation Settings
Simulation Settings
2000m × 30m two-way road
Speed limit: 100kph
SUMO-generated vehicle trace,
N ∈ {20, 40, 60, 80, 100}
Transmission range: 300m
Range of interest: 1200m
Routine message: 10/sec
Emergency message: 1/sec with 0.5 probability
in certain segment
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Performance Evaluation
Simulation Settings
Simulation Settings
Comparison
CBD, FARTHEST, slottedP and PVCast
Metrics
Per-Vehicle Throughput
Broadcast Rate
Broadcast Efficiency
Per-Packet Delivery Delay
Per-Packet Vehicle Coverage
Per-Vehicle Emergency Throughput
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Performance Evaluation
Evaluation Results
Evaluation Results
Per-Vehicle Throughput (pkt/sec)
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Performance Evaluation
Evaluation Results
Evaluation Results
Broadcast Rate
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Performance Evaluation
Evaluation Results
Evaluation Results
Broadcast Efficiency
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Performance Evaluation
Evaluation Results
Evaluation Results
Per-Packet Delivery Delay (ms)
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Performance Evaluation
Evaluation Results
Evaluation Results
Per-Packet Vehicle Coverage
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Performance Evaluation
Evaluation Results
Evaluation Results
Per-Vehicle Emergency Throughput (pkt/sec)
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Conclusion and Future Work
Outline
1
Introduction
2
Quantifying Data Preferences
3
PVCast: a Packet-Value-Based Dissemination Protocol
4
Performance Evaluation
5
Conclusion and Future Work
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Conclusion and Future Work
Conclusion and Future Work
Conclusion
Quantification of data preferences in VANET
Integration of data preferences in the design of
dissemination protocol
System benefits in terms of low latency and high
coverage
Future Work
A more comprehensive model of data preference
Joint adaption of power, data rate and
contention window based on packet-value
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