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9.17 9.17 Presentation Transcript

  • Performance Comparison of Three Location Service Algorithms for Vehicular Ad Hoc Networks Wan Chih Chang
  • Outline
    • Intersection Location Service (ILS)
    • Grid Location Service (GLS)
    • Hierarchy Location Service (HLS)
  • DREAM Homezone
    • The Distance Routing Effect Algorithm for Mobility
    • Uses flooding to spread position information
    • The capacity of the network is substantially decreased as a result of message flooding, especially in situations where the nodes make frequent position changes
    • Homezone does not require flooding
    • The homezone becomes empty, and some cars may get into situations where their default location servers are temporarily unavailable.
  • Grid Location Service (GLS)
    • Divides the area of the entire ad hoc network into a hierarchy of squares forming a quad-tree.
    • Each node selects one node in each element of every levels of the quad-tree as a location server.
    • The density of location servers for a particular node is high in areas close to the node and become exponentially sparse as the distance to the node increases.
  • Hierarchy Location Service (HLS)
    • Partitions the area of the ad hoc network into cells.
    • The cells are grouped into regions level by level.
    • A node uses a hierarchy of location servers to store its location information.
    • The problem of empty cells where location updates or requests may run into is solved by temporary servers through a handover mechanism to bridge the gap.
  • Intersection Location Service (ILS)
    • Consistent Hashing
    • Query for Location
    • Dynamic Operation and Failure Recovery
    • Location Update
  • Consistent Hashing
  • Query for Location
  • Dynamic Operation and Failure Recovery
    • Leaving the network
    • Joining the network
  • Location Update
  • First Simulation
    • Table 1 : Parameters for the study of car speeds.
      • Number of cars 80
      • Area size (m2) 900x900
      • Mean velocity (m/s) 10, 20, 30,40
      • Velocity deviation (m/s) 5
      • Pause time (s) 5
  • Query success ratio (QSR)
  • Second Simulation
    • Table 2 : Parameters for the study of car speeds
      • Number of nodes (cars) 20~80
      • Area size (m2) 900x900
      • Mean velocity (m/s) 40
      • Velocity deviation (m/s) 5
      • Pause time (s) 5
  • Third Simulation
      • The pause time at intersections to be uniformly distributed in the interval [0,5] s instead of a constant of 5 s.
      • The initial position of each car is set in a way such that its distance to the nearest intersection is uniformly distributed from [0,100] m instead of a constant of 0 m.
    • All the simulation parameters are the same as those in Table 2
  • Number of cars 80 Mean velocity (m/s) 10, 20, 30,40
  • Large Scale Simulations
    • Table 3 : Parameters for the large scale simulations.
      • Number of nodes 80, 180, 320
      • Area size (m2) 900x900, 1350x1350, 1800x1800
      • Mean velocity (m/s) 40
      • Velocity deviation (m/s) 5
      • Pause time (s) [0,5]
      • The number of intersections increases from 25 to 64 and 100 as the size of areas increases.
      • Both the size of cells in HLS and the size of order-one squares in GLS increase from 112.5x112.5 m 2 to 168.75x168.75 m 2 and 225x225 m 2 .
  • The area size varying from 900x900 m 2 to 1350x1350 m 2 and 1800x1800 m 2
  • The area size of 1800*1800 m 2
  • Conclusion
    • ILS, a location service algorithm that is designed to work in the city environments with streets and intersections.
    • increased success ratios under different network topologies.
    • ILS algorithm not only remains robust at high car speeds but also demonstrates higher scalability than the other two with respect to network size.
  • ~Thank you~