on scheduling of data dissemination in vehicular networks with mesh backhaul liu zhongyi m.s....
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On Scheduling of Data Dissemination in Vehicular Networks with Mesh Backhaul
Liu Zhongyi
M.S. Candidate, Peking [email protected]
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
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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
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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
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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
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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
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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
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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
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Performance Evaluation
Simulation Scenario Simulation Parameters
The effects of reliability level should be evaluated
The effects of threshold values should also be
evaluated
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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
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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
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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.