Using traffic flow for cluster formation in VANET


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  • 1. A cluster is a group of nodes that can communicate without disconnection and that identify themselves to be part of a cluster. 2. With the large number of nodes and the lack of routers, a flat routing scheme, where each node acts as a router, may cause serious scalability and hidden terminal problems. using clustering can lead to more node coordination and fewer nodes interfering with each other. 3. Clusterhead is a node that is selected by other nodes in the cluster to coordinate the communication among them. 4. All cluster members select a clusterhead to coordinate the communication among them. This process is carried out by each node broadcasting its information to all other neighboring nodes. After the nodes have decided on the clusterhead, the clusterhead will be able to communicate directly to all other cluster members and may act as the relay node of communications to other cluster members and other nodes in different clusters. Significant time and channel bandwidth will be consumed to complete this process.
  • Lowest-ID: in VANETs, the lowest ID clusterhead is not always the ideal selection because the movement of the vehicles is not considered. 2. Highest-Degree: it is not stable for VANETs due to the nature of the nodes movement. If the clusterhead changes its behavior at any moment, the connectivity level could change dramatically. 3. Utility Function: the closest position to the average and the closest velocity to the average of all proximal vehicles are calculated along with connectivity level to determine the most stable clusterhead.
  • Using traffic flow for cluster formation in VANET

    1. 1. Using Traffic Flow for Cluster Formation in Vehicular Ad-hoc Networks On-MOVE ‘10 By Mohammad S. Almalag Michele C. Weigle Department of Computer Science Old Dominion University Norfolk, VA 10/11/2010
    2. 2. Outline <ul><li>INTRODUCTION </li></ul><ul><li>BACKGROUND AND RELATED WORK </li></ul><ul><li>APPROACH </li></ul><ul><li>SIMULATION </li></ul><ul><li>RESULTS </li></ul><ul><li>CONCLUSION </li></ul>10/11/2010
    3. 3. INTRODUCTION <ul><li>What is clustering in VANET? </li></ul><ul><li>Why clustering in VANET? </li></ul><ul><li>What is a clusterhead? </li></ul><ul><li>How can we select the clusterhead? </li></ul>10/11/2010
    4. 4. BACKGROUND AND RELATED WORK <ul><li>Clusterhead Selection Algorithms in VANET: </li></ul><ul><ul><li>Lowest-ID </li></ul></ul><ul><ul><li>Highest-Degree </li></ul></ul><ul><ul><li>Utility Function </li></ul></ul>10/11/2010
    5. 5. APPROACH 10/11/2010
    6. 6. APPROACH <ul><li>Based on the traffic flow, using: </li></ul><ul><ul><li>Lane detection system: </li></ul></ul><ul><ul><ul><li>GPS </li></ul></ul></ul><ul><ul><ul><li>GPS/wheel odometer </li></ul></ul></ul><ul><ul><ul><li>Vision </li></ul></ul></ul><ul><ul><ul><li>Beacon network using infrastructure </li></ul></ul></ul><ul><ul><li>In-depth digital street map </li></ul></ul><ul><ul><ul><li>NAVTEQs NAVSTREETS </li></ul></ul></ul>10/11/2010
    7. 7. APPROACH <ul><li>We need to calculate: </li></ul><ul><ul><li>Lane Weight </li></ul></ul><ul><ul><li>Network Connectivity Level ( NCL ) </li></ul></ul><ul><ul><li>Average Distance Level ( ADL ) </li></ul></ul><ul><ul><li>Average Velocity Level ( AVL ) </li></ul></ul><ul><ul><li>Clusterhead Level ( CHL ): </li></ul></ul>10/11/2010
    8. 8. APPROACH-Lane Weight <ul><ul><li>Example: TNL=4, 1 LT, 1 RT, and 2 NT </li></ul></ul>10/11/2010
    9. 9. APPROACH- Network Connectivity Level 10/11/2010 Overall Traffic flow
    10. 10. APPROACH- Average Distance Level Overall Traffic flow 10/11/2010
    11. 11. APPROACH- Average Velocity Level Overall Traffic flow 10/11/2010
    12. 12. APPROACH- Clusterhead Level <ul><li>Compute CHL </li></ul><ul><li>Insert CHL in regularly scheduled beacons </li></ul>10/11/2010
    13. 13. SIMULATION <ul><li>NS-3 with Highway Mobility Modules (1) </li></ul><ul><li>Two intersections </li></ul><ul><li>Length = 3 km </li></ul><ul><li>One traffic direction </li></ul><ul><li>Traffic density = 60 vehicles per lane per km </li></ul><ul><li>Vehicle type ratio = 20% trucks & 80% sedans </li></ul><ul><li>Number of nodes = 126 </li></ul><ul><li>10 different runs </li></ul><ul><li>(1) H. Arbabi and M. C. Weigle. Highway mobility and vehicular ad-hoc networks in ns-3. In Proceedings of the Winter Simulation Conference, Baltimore, MD, Dec 2010. </li></ul>10/11/2010
    14. 14. SIMULATION First intersection. 10/11/2010
    15. 15. SIMULATION Second intersection. 10/11/2010
    16. 16. SIMULATION <ul><li>Scenarios: </li></ul><ul><ul><li>Transmission range: </li></ul></ul><ul><ul><ul><li>100 m – 150 m </li></ul></ul></ul><ul><ul><ul><li>150 m – 200 m </li></ul></ul></ul><ul><ul><ul><li>200 m – 250 m </li></ul></ul></ul><ul><ul><ul><li>250 m – 300 m </li></ul></ul></ul><ul><ul><li>Max. speed limit: </li></ul></ul><ul><ul><ul><li>40 km / h </li></ul></ul></ul><ul><ul><ul><li>80 km / h </li></ul></ul></ul><ul><ul><ul><li>120 km / h </li></ul></ul></ul>10/11/2010
    17. 17. RESULTS Clusterhead changes vs. Transmission Range at the first intersection. The maximum speed is 40 km/h (25 mph) 10/11/2010 More stable clusters
    18. 18. RESULTS Clusterhead changes vs. Transmission Range at the second intersection. The maximum speed is 40 km/h (25 mph) 10/11/2010 More stable clusters
    19. 19. CONCLUSION <ul><li>An algorithm for clusterhead selection based on the traffic flow of vehicles in the cluster is presented. </li></ul><ul><li>Using real scenarios, our algorithm performed better than other algorithms. </li></ul><ul><li>It showed longer clusterhead lifetime. </li></ul>10/11/2010
    20. 20. Thank you <ul><li>Mohammad S. Almalag </li></ul><ul><li>[email_address] </li></ul><ul><li>Old Dominion University </li></ul><ul><li> </li></ul><ul><li>Questions </li></ul>10/11/2010