On Scheduling of Data Dissemination in Vehicular Networks with Mesh Backhaul

Liu Zhongyi

M.S. Candidate, Peking Univ.lzy@net.pku.edu.cn

2008-02-19(To Appear on IEEE ICC’08 Vehi-mobi Workshop)

2

Outline

• Background & Motivation• System Model• Scheduling Algorithms• Performance Evaluation• Conclusions and Future Work

Problem

Metrics

Algorithms

Evaluation

Methodology

3

Background & Motivation-Vehicular Networks

• Vehicular Networks– Networks for C2C and C2R

communications– Based on wireless

communication technologies (Ad hoc, multi-channel, etc)

• Characteristics– Restricted Network

Topology and Mobility Pattern

– Frequent changes of network topology

– Network partition may occur under sparse car density

– Multi-path fading effects

• Applications– Safety applications

(collision avoidance, emergency warning)

– Internet access “on the go”– Data collection via sensors

on vehicles

4

Background and Motivation-Motivation

TIME and SPACEConstraints of Messages

Messages should be Disseminated in a specificduration and a givencoverage

Trade-offs between Reliability And fairness

•Traffic Congestion

•Car Accident

•Road maintenance & Traffic Control

•Reliability: the quality of service for a single message

•Fairness: whether different messages are given the same level of chances

5

System Model-Network Architecture

Car Accident

!!

Disseminate event message to left-side and downside areas

Attributes of a message•Content•(x,y)•Radius•duration

Mesh Roadside Unit (MRU)

Vehicle

6

System Model-Metrics

• Reliability Metric • Is the message disseminated in all its requested duration?– TRM indicates reliability

in the time dimension• Is the message

disseminated in all its requested area?– SRM depicts reliability in

the space dimension• Can we specify the level

of reliability we want?– K indicates the reliability

level

* (1 )* (0 1)RM TRM SRM

@

MRU

( , )i

i

m MRU

iR

MRU

TR m i

NTRM

N

( )m

messages

SR mSRM

N

_ ( , )( , )

( )

D time m iTR m i

Duration m _

_

( )mD MRU

mC MRU

NSR m

N

7

System Model-Metrics

m1

m2

m1

m2

m1

t0 t0+ t0+2* △ △

t0 t0+ t0+2* △ △

t0 t0+ t0+2* △ △

1.Message input

2. 1st schedule

3. 2nd schedule

K=1 K=2

TRM=1/2+1/2=1

TRM=1+0=1

TRM=(1/2)^2+(1/2)^2=1/2

TRM=(1)^2+(0)^2=1

Illustration for Reliability Level

8

System Model-Metrics

• Fairness Metric

• Combined Metric

* (1 )* (0 1)i

iDi

MRU RD

R MRU

N

NNFM

N N

* (1 )* (0 1)CM RM FM

9

Scheduling Algorithms

Reliability-orientedalgorithms

Fairness-orientedalgorithms

Hybrid Schemes

MQIF: Maximum Quality Increment First (using estimated Quality Increment as the selection criteria)

LSF: Least Selected First (using the number of scheduling times as the selection criteria)

•Combine via threshold: conditional-MQIF,conditional-LSF (easy to be adapted to different application scenarios)•Combine via hybrid selection criteria:MQILSF

10

Performance Evaluation

Simulation Scenario Simulation Parameters

The effects of reliability level should be evaluated

The effects of threshold values should also be

evaluated

11

Performance Evaluation-Comparison of different scheduling algorithms

0 5 10 15 20 25 30 35 40 45 50

0.52

0.54

0.56

0.58

0.6

0.62

Iteration of Runs

Rel

iabi

lity

Met

ric

MQIFLSFCond-MQIFCond-LSFMQILSF

0 5 10 15 20 25 30 35 40 45 500.96

0.965

0.97

0.975

0.98

0.985

0.99

0.995

1

1.005

Iteration of Runs

Fai

rnes

s M

etric

MQIFLSFCond-MQIFCond-LSFMQILSF

0 5 10 15 20 25 30 35 40 45 500.74

0.75

0.76

0.77

0.78

0.79

0.8

0.81

Iteration of Runs

Com

bine

d M

etric

MQIFLSFCond-MQIFCond-LSFMQILSF

Reliability Metric Fairness Metric Combined Metric

Summary:•LSF and MQIF achieve the worst reliability and fairness, respectively•MQIF does not result in the best reliability. The Reason?•Hybrid schemes achieve better reliability and Fairness, therefore better overall performance

e.g. The reliability metric of Cond-LSF is about 7% higher than that of LSF; the fairness metric of MQILSF is about 11% higher than that of MQIF

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Performance Evaluation-Effects of Reliability Level

Messages Received by the NetworkGSR

Message Disseminated by the Network

1 2 3 4 50.95

0.955

0.96

0.965

0.97

0.975

0.98

0.985

0.99

0.995

1

K

Glo

bal S

ervi

ce R

atio

MQIF

MQILSF

Cond-MQIF

1 2 3 4 50.9

0.91

0.92

0.93

0.94

0.95

0.96

0.97

0.98

0.99

1

K

Ave

rage

Loc

al S

ervi

ce R

atio

MQIF

MQILSF

Cond-MQIF

1 2 3 4 50.93

0.94

0.95

0.96

0.97

0.98

0.99

1

K

Fai

rnes

s M

etric

MQIF

MQILSF

Cond-MQIF

Global Service Ratio(GSR)

Average Local Service Ratio(Average-LSR)

Fairness Metric

Average-LSR is the average of the service ratio of all MRUs

Summary: GSR, Average-LSR and FMall decreases as the reliability level increases

13

Performance Evaluation-Effects of Threshold Values

5 10 15 20 25 30 350.548

0.55

0.552

0.554

0.556

0.558

0.56

0.562

0.564

MQIF Threshold

Rel

iabi

lity

Met

ric

Cond-MQIF

5 10 15 20 25 30 350.985

0.986

0.987

0.988

0.989

0.99

0.991

0.992

0.993

0.994

0.995

MQIF Threshold

Fai

rnes

s M

etric

Cond-MQIF

In Cond-MQIF, RM decreases as the threshold value increases

In Cond-MQIF, FM increases as the threshold value increases

Summary: As the threshold value increases, more opportunities are givenTo the LSF strategy while less are given to MQIF.

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Conclusions and Future Work• We argue that there are

trade-offs between reliability and fairness in the data dissemination of vehicular networks

• Metrics for both reliability and fairness are proposed– RM covers both the SPACE

and TIME dimensions and can specify different reliability levels

– FM concerns only whether there is a chance for service for a message (without regarding whether the same level of opportunities are given to different messages)

• One reliability-oriented, one fairness oriented and 3 hybrid algorithms are developed and evaluated

• Future work– Better fairness metric– Message urgencies not

considered– Traffic density not

considered in our current metrics and algorithms

15

Q&A

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Related Work

• Researches on developing vehicular networks with infrastructure– Mainly focus on one-hop communications

• Scheduling for data access– Data access within one hop– Considers only upload/download– Fairness not considered

• Packet Scheduling at MAC layer in wireless Networks– Packet-level Qos– Trade-off between channel utilization and fairness– Focus on one-hop communications

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References• V. Bychkovsky, B. Hull, et al. A measurement study of of vehic

ular internet access using in situ wi-fi networks. In Proceedings of the 12th annual international conference on mobile computing and networking(mobicom’06),pages 50-61, 2006

• D. Hadaller, S. Keshav, T. brecht, et.al. Vehicular opportunistic communication under the microscope. In Proceedings of The 5th International Conference on Mobile Systems, Applications, and Services(MobiSys’07), 2007

• Yang Zhang, Jing Zhao and Guohong Cao. On Scheduling Vehicle-Roadside Data Access. In Proceedings of the fourth ACM international workshop on Vehicular ad hoc networks(VANET’07). Pages 9-18, 2007

• Haiyun Luo, et.al. A new model for packet scheduling in multihop wireless networks. In Proceedings of the 6th annual international conference on Mobile computing and networking(mobicom’00). Pages 76-86,2000.