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

1School of Computer Science, McGill University2General Motors Research Lab

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 NetworksCommunication infrastructure for IntelligentTransportation Systems (ITS)

Operate in a dynamic environment

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Introduction Background

Introduction

Safety Data DisseminationCrucial for vehicle safety

Contain periodic routine data and event-driven emergencydata

More emphasis on QoS, e.g., small delay and highcoverage

(a) Collision Avoidance (b) Lane Change

Sources:www.gm.com and www.Mercedes-Benz.comQiao Xiang et al. (McGill) IEEE INFOCOM’15 04/29/2015 4/ 31

Introduction Background

Data Preferences

When collecting safety data, vehicles havepreferences on

Closer, Newer and More important data

Related works do not consider these preferences

Counter-Based DisseminationFarthest-First DisseminationProbabilistic Forwarding

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Introduction Our Focus

Our Focus

Quantifying data preferences

Designing lightweight distributed disseminationprotocol

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 whencollecting 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 itsorigin;

becomes zeros after p exceeds the Range ofInterest.

Figure: Region of Interest

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Quantifying Data Preferences

Spatial-Value Function

Distance

Range of Interest

Sv(p)

0

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 safetyapplications;

New packets have much higher temporal-valuethan 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 statisticanalysis.

Elapsed Time

Tv(p)

0

Emergency Message

Routine Message

Figure: Temporal-Value vs. Elapsed Time.

Tv(p) = e−µtypep te(p).

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Quantifying Data Preferences

Type-Value Function

Emergency messages are more important thanroutine messages.

Wp

0

Emergency Message

Routine Message

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 twopackets p1 and p2, vehicle v always has a higherdata 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

Fail

No

Discard packet

Packet Value Update

1-Hop Dissemination Utility Computation

Contention Window Size Assignment

Probabilistic Broadcast Test

PVA(p)=0

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

AU

edcA(p) = 5− 2 = 3

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PVCast: a Packet-Value-Based Dissemination Protocol Probabilistic Broadcast Test

Probabilistic Broadcast Test

Piecewise function of dissemination utility

Higher dissemination utility→ Higher chance for broadcasting

Dissemintation Utility

Bro

adca

st P

roba

bilit

y

0

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PVCast: a Packet-Value-Based Dissemination Protocol Contention Window Size Assignment

Contention Window Size Assignment

Piecewise function of dissemination utility

Higher dissemination utility→ Smaller minimum CW size→ Higher priority to get channel access

Dissemintation Utility

Min

imum

CW

Siz

e

0

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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 probabilityin 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 ofdissemination protocol

System benefits in terms of low latency and highcoverage

Future Work

A more comprehensive model of data preference

Joint adaption of power, data rate andcontention window based on packet-value

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