A Stable Clustering Algorithm Using the Traffic Regularity of

Bus in the Urban VANET Scenarios

Reporter:羅婧文Advisor: Hsueh-Wen Tseng

1

2

Outline

Introduction The Importance of Cluster Stability

Related Work CATRB(Clustering Algorithm Using the Traffic Regularity of

Bus) Bus Recording Algorithm CH Election Algorithm SCH Algorithm

Experiment Result Conclusion Reference

3

Introduction

VANET(Vehicular Ad Hoc Network) MANET(Mobile Ad Hoc Network) Communication in VANET

V2I (Vehicle-to-Infrastructure) V2V (Vehicle-to-Vehicle)

Fig. 1. Application in VANETFig. 2. Communication in VANET

Real-time Traffic Condition

Emergency Warning System

Audio and Video Stream Service

Digital TV

Navigation System

Digital Broadcasting

Safety Message

Gaming and Entertainment

Telematics

RSU

(a)

(b)

OBU

4

Introduction

Clustering Role

Cluster head(CH) Cluster member(CM)

The highly dynamic topology of VANET will disturb cluster formation and maintenance, increase cluster instability

Fig. 3. Clustering

CH CM

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The Importance of Cluster Stability

Re-clustering CH leaves cluster / Excessive nodes Increase overhead

Exchange new topology information and reconfiguration of each node

Increase transmission time Frequent cluster reconfiguration

Generate tremendous communication loads Reduce available bandwidth for message dissemination

Related Work6

VANET in Urban 802.11p and LTE in Urban Clustering in 802.11p Clustering in LTE

7

VANET in Urban

Characteristics in urban environment High node density Large node density variations Numerous intersections with traffic light

Frequent cluster fragmentation

Fig. 4. Topology Fragmentation

8

802.11p Decentralized architecture

Broadcast storm Collision

LTE Centralized architecture

802.11p and LTE in Urban

LTE 802.11p

High bandwidth 、Wide coverage 、Market penetration 、High mobility support(Up to 350km/hr)

Poor reliabilityPoor scalability 、

Table 1. The Comparison of 802.11p and LTE

[1] Araniti, G.; Campolo, C.; Condoluci, M.; Iera, A; Molinaro, A, “LTE for vehicular networking: a survey,” Communications Magazine, IEEE , vol.51, no.5, pp.148,157, May 2013

Collision

Fig. 6. LTE in Urban

Fig. 5. 802.11p in Urban

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Clustering in 802.11p

VANET ID-based [2] Node degree-based [3]

Extension of MANET Mobility-based [4][5][6][7][8][9][10][11]

Velocity, position, and direction

[2] M. Gerla and J. T.C. Tsai, “Multicluster, Mobile, Multimedia Radio Network,” Wireless Networks, 1(3) 1995, pp. 255-265[3] A.K. Parekh, “Selecting routers in ad-hoc wireless networks,” ITS, 1994[5] Ucar, S., Ergen, S.C., Ozkasap, O., “VMaSC: Vehicular multi-hop algorithm for stable clustering in Vehicular Ad Hoc Networks,” Wireless Communications and Networking Conference (WCNC), 2013 IEEE[10] Minming Ni; Zhangdui Zhong; Kaimin Wu; Dongmei Zhao, “A New Stable Clustering Scheme for Highly Mobile Ad Hoc Networks,”  Wireless Communications and Networking Conference (WCNC), 2010 IEEE[11] Maglaras, L.A. ; Katsaros, D., “Clustering in Urban environments: Virtual forces applied to vehicles,” Communications Workshops (ICC), 2013 IEEE International Conference on

10

Clustering in LTE

Fig. 8. Cluster Lifetime vs Vehicles Number

Node degree-based cluster algorithm

Fig. 7. LTE4V2X Architecture

[12] Remy, G.; Senouci, S. -M; Jan, F.; Gourhant, Y., “LTE4V2X: LTE for a Centralized VANET Organization,”  Global Telecommunications Conference (GLOBECOM 2011), 2011 IEEE

CH aggregates data of cluster members before sending it to the eNodeB

LTE4V2X, a novel framework

for a centralized vehicular

network organization using

LTE [12]eNodeB

LTE

802.11p

Cluster Head

Cluster

CH

CH

CH

CH

CH

CH

CH

CATRB(Clustering Algorithm Using the Traffic Regularity of Bus)

Bus Recording Algorithm CH Election Algorithm

CH Leaves Cluster

SCH Algorithm Excessive Nodes

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12

CATRB

Vehicles distribution has a high spatial and temporal diversity that depends on the time of the day and places

Vehicle density CH leaves cluster / Excessive nodes Spatial Temporal

[13] Ait Ali, K.; Baala, O.; Caminada, A, “On the spatio-temporal traffic variation in vehicles mobility modeling,”  Vehicular Technology, IEEE Transactions on , 2014

suburbanurban DD peakoffpeak DD -

13

CATRB

[14 ] 我國汽車客運路線別概況分析 (104 年 2 月 )[Online]. Available:  http://www.motc.gov.tw/uploaddowndoc?file=public/201502041405091.pdf&filedisplay=%E6%88%91%E5%9C%8B%E6%B1%BD%E8%BB%8A%E5%AE%A2%E9%81%8B%E8%B7%AF%E7%B7%9A%E5%88%A5%E6%A6%82%E6%B3%81%E5%88%86%E6%9E%90.pdf&flag=doc

Fig. 9. Effective Bus Route Ratio in Taiwan Major Cities Fig. 10. Effective Number of Bus Routes per Area in Taiwan Major Cities

Effective bus routes ： The bus route with the complete coordinates of each stop

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CATRB

[15] 台北市交通管制工程處 ,103 年度臺北市交通流量及特性調查 )[Online]. Available: http://www.bote.gov.taipei/ct.asp?xItem=660485&CtNode=71101&mp=117031

Table 2. Intersections with Bus Flow Data

No. Road

NI035 林森北路 (Linsen N. Rd.) ~ 南京東路 (Nanjing E. Rd.)

NI036 中山北路 (Zhongshan N. Rd.) ~ 南京東西路 (Nanjing E. W. Rd.)

NI037 南京東路 (Nanjing E. Rd.) ~ 松江路 (Songjiang Rd.)

SI051 南京東路 (Nanjing E. Rd.) ~ 光復北路 (Guangfu N. Rd.)

SI053 南京東路 (Nanjing E. Rd.) ~ 復興北路 (Fuxing N. Rd.)

SI054 南京東路 (Nanjing E. Rd.) ~ 敦化北路 (Dunhua N. Rd.)

SI103 南京東路 (Nanjing E. Rd.) ~ 北寧路 (Beining Rd.)

SI137 南京東路 (Nanjing E. Rd.) ~ 寧安街 (Ning’an St.)

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CATRB

[15] 台北市交通管制工程處 ,103 年度臺北市交通流量及特性調查 )[Online]. Available: http://www.bote.gov.taipei/ct.asp?xItem=660485&CtNode=71101&mp=117031

Fig. 11. Vehicles and Buses Traffic Ratio of 8 Intersections in Taipei

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CATRB

Fig. 12. Urban VANET Scenario

Transmission Range

LTE 3 km

802.11p 250 m

LTE BSLTE BS

A1 A2 A3

A4 A5 A6

A7 A8 A9

1.5km

0.5km

Route1

Route2

Route3

BN1

BN2

BN3

CH CM

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Bus Recording Algorithm

Hour

CHDiff Time

1 2 3 4 5 6 7 ... ... ...21

22

23

24

Clu

ster

1

Hour

CHDiff Time

1 2 3 4 5 6 7 ... ... ...21

22

23

24

Clu

ster

2

Hour

CHT

1 2 3 4 5 6 7 ... ... ...21

22

23

24

Clu

ster

3

...

Cluster ID Bus ID Node IDMeet

Time(s) Departure Time(s)

6bits 2bits 11bits 12bits 12bits

Diff Time(s) 12bits

Hour

CHDiff Time

1 2 3 4 5 6 7 ... ... ...21

22

23

24

Meet Time ： The time that nodes enter the buses travel areaDeparture Time ： The time that nodes leave the buses travel areaCMT ： 55 bit * 1344 entries per hour * 24 hours * 7days = 1.55MBCMT Record Time ： Monday — Sunday (Update at Sunday 12:00)CHT ： (11+12) bit * 24 hours * 7days =0.48KB

Fig. 13. Cluster Member Table(CMT)

Fig. 14. Cluster Head Table(CHT)

Fig. 15. Total CHT

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CH Election Algorithm

Fig. 16. CH Election Algorithm

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CH Election Algorithm

Case1 ： Traffic light

Incenter, circumcenter and barycenter exactly located at the same node in equilateral triangle ()

Find the node in the area overlapped by incenter, circumcenter and barycenter act as

the next cluster head

L1L2

L3

OCH

CM1

CM2

CM3

CM5

CM6

CM4

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CH Election Algorithm

Case2 ： Turning

OCH

CM1

CM2

CM3CM5

CM6

CM4

L1

CH

CM

Case2： There are no nodes for next CH selection

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SCH Algorithm

Fig. 17. SCH Algorithm

(1)

Experiment Result Parameter Setting Average Cluster Head Changes

Peak Time Off-peak Time

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Parameter Setting

[14 ] 我國汽車客運路線別概況分析 (104 年 2 月 )[Online]. Available:  http://www.motc.gov.tw

Fig. 18. Average Kilometers per Bus Route per Time in Taiwan Major

Cities

Parameter Value

Vehicle Nodes Peak time ： 39

Off-peak time ： 20Topology Grid

Map Size 1.5km×1.5km

Speed Limit 70 km/hr

Micro Mobility Model

CarFollowing-Krauss (SUMO)[16][17]

Lane(Unidirectional)

2

Lane Width 5 m

Vmax 40,50,60 km/hr

Bmax 40 km/hr

Simulation Time 3600 secTable 3. Parameter Setting

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Average Cluster Head Changes

Fig. 19. Average Number of Cluster Head Changes at Peak Time

Fig. 20. Average Number of Cluster Head Changes at Off-peak Time

=40 km/hr =50 km/hr =60 km/hr

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Conclusion

CATRB significantly improves the cluster stability Consider the traffic flow in real world CH election algorithm

Mitigate the problem caused by CH leaves cluster SCH algorithm

Mitigate the problem caused by excessive nodes SCH reforms the cluster very quickly

Reduce the overhead needed to select new CH

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Reference

[1] Araniti, G.; Campolo, C.; Condoluci, M.; Iera, A; Molinaro, A, “LTE for vehicular networking: a survey,” Communications Magazine, IEEE , vol.51, no.5, pp.148,157, May 2013

[2] M. Gerla and J. T.C. Tsai, “Multicluster, Mobile, Multimedia Radio Network,” Wireless Networks, 1(3) 1995, pp. 255-265

[3] A.K. Parekh, “Selecting routers in ad-hoc wireless networks,” ITS, 1994

[4] Ahizoune, A., Hafid, A.,“A new stability based clustering algorithm (SBCA) for VANETs,” Local Computer Networks Workshops (LCN Workshops), 2012 IEEE 37th Conference on 

[5] Ucar, S., Ergen, S.C., Ozkasap, O., “VMaSC: Vehicular multi-hop algorithm for stable clustering in Vehicular Ad Hoc Networks,” Wireless Communications and Networking Conference (WCNC), 2013 IEEE

[6] Zhenxia Z., Azzedine B., Richard W. Pazzi, “A novel multi-hop clustering scheme for vehicular ad-hoc networks,” MobiWac '11, Proceedings of the 9th ACM international symposium on Mobility management and wireless access, Pages 19-26 

[7] Tal, I. ; Muntean, G., “User-oriented cluster based solution for multimedia content delivery over VANETs,” Broadband Multimedia Systems and Broadcasting (BMSB), 2012 IEEE International Symposium on

[8] Maglaras, L.A. ; Katsaros, D., “Distributed clustering in vehicular networks,” Wireless and Mobile Computing, Networking and Communications (WiMob), 2012 IEEE 8 th International Conference on 

[9] Sakhaee, E.; Jamalipour, A, “A New Stable Clustering Scheme for Pseudo-Linear Highly Mobile Ad Hoc Networks,”  Global Telecommunications Conference, 2007. GLOBECOM '07. IEEE

27

Reference

[10] Minming Ni; Zhangdui Zhong; Kaimin Wu; Dongmei Zhao, “A New Stable Clustering Scheme for Highly Mobile Ad Hoc Networks,”  Wireless Communications and Networking Conference (WCNC), 2010 IEEE

[11] Maglaras, L.A. ; Katsaros, D., “Clustering in Urban environments: Virtual forces applied to vehicles,” Communications Workshops (ICC), 2013 IEEE International Conference on

[12] Remy, G.; Senouci, S. -M; Jan, F.; Gourhant, Y., “LTE4V2X: LTE for a Centralized VANET Organization,”  Global Telecommunications Conference (GLOBECOM 2011), 2011 IEEE  

[13] Ait Ali, K.; Baala, O.; Caminada, A, “On the spatio-temporal traffic variation in vehicles mobility modeling,”  Vehicular Technology, IEEE Transactions on , vol.PP, no.99, pp.1,1, June 2014

[14 ]我國汽車客運路線別概況分析 (104 年2月 )[Online]. Available:  http://www.motc.gov.tw/uploaddowndoc?file=public/201502041405091.pdf&filedisplay=%E6%88%91%E5%9C%8B%E6%B1%BD%E8%BB%8A%E5%AE%A2%E9%81%8B%E8%B7%AF%E7%B7%9A%E5%88%A5%E6%A6%82%E6%B3%81%E5%88%86%E6%9E%90.pdf&flag=doc

[15]台北市交通管制工程處 , 103年度臺北市交通流量及特性調查 [Online]. Available: http://www.bote.gov.taipei/ct.asp?xItem=660485&CtNode=71101&mp=117031

[16] M. Behrisch, L. Bieker, J. Erdmann, and D. Krajzewicz, “SUMO - Simulation of Urban MObility: An Overview,” in SIMUL 2011, The Third International Conference on Advances in System Simulation, 2011

[17] S. Krauß. “Microscopic Modeling of Traffic Flow: Investigation of Collision Free Vehicle Dynamics,” PhD thesis, 1998

[18] Remy, G.; Senouci, S.-M.; Jan, F.; Gourhant, Y., “LTE4V2X - impact of high mobility in highway scenarios,”  Global Information Infrastructure Symposium (GIIS), 2011 

28

Reference

[19] Remy, G.; Senouci, S.-M.; Jan, F.; Gourhant, Y.,“LTE4V2X Collection, dissemination and multi-hop forwarding,” IEEE International Conference on Communications (ICC), 2012

[20] Acer, U.G.; Giaccone, P.; Hay, D.; Neglia, G.; Tarapiah, S., “Timely Data Delivery in a Realistic Bus Network,” Vehicular Technology, IEEE Transactions on , vol.61, no.3, pp.1251–1265, March 2012

[21] Ho, I.W.H.; Leung, K.K., “ Node Connectivity in Vehicular Ad Hoc Networks with Structured Mobility,” LCN 2007. 32nd IEEE Conference on , 2007