Network Connectivity of VANETs in Urban Areas

1
Network Connectivity of VANETs in Urban Areas

• Wantanee Viriyasitavat, Ozan K. Tonguz, Fan Bai
• IEEE communications society conference on sensor,
  mesh and Ad hoc networks

89821006 ???
2
Outline

• Introduction
• Cellular automata-based traffic mobility model
• Network connectivity in urban traffic
• Conclusion

3
Introduction

• Vehicular Ad Hoc Networks applications
• Safety relatedapplications
• non safety-related applications
• It is essential to analyze and to have a complete
  understanding of the network topology and its
  connectivity pattern

4
Introduction

• Static characteristics
• network connectivity
• path redundancy
• Dynamic characteristics
• connection duration
• Re-healing time

5
Traffic model

• Due to the unavailability of urban vehicular
  traffic traces
• Cellular Automata (CA)-based vehicular mobility
  model
• Cellular road structure
• Vehicle movement
• Traffic light control

6
Traffic model

• Cellular Road Structure for Manhattan Grid
• evenly-spaced horizontal and vertical
• two-lane ,bi-directional streets
• each lane is modeled as N cells
• one vehicle per cell

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Traffic model

• Vehicle Movement
• 1. Vehicles state
• rn street number where Vehicle n is located
• Dn direction of travel of Vehicle n
• xn and vn the position and the speed
• dn distance to the vehicle in front of it
• In and sn are the closest intersection and the
  distance to that intersection
• Tn is the turning decision at the intersection In

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Traffic model

• 2. Algorithm for Updating Vehicles State
• Case I Go straightly
• Acceleration step
• Braking step front car
• Randomization step ???
• Vehicle movement step update
• Case II TURN
• red-light stop
• green-light right or left

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Traffic model

• Traffic Light Control
• Cycle duration green-red-yellow
• Green light ratio
• Signal offset between two consecutive
  intersections

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Network connectivity

• Two types of traffic
• Non-transit
• Transit
• Four categorized of traffic
• Morning Rush Hour traffic
• Lunch Time traffic low transit
• Evening Rush Hour traffic
• Midnight traffic high speed

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Network connectivity

• Two different network characteristics
  corresponding to two types of application
• Static characteristics
• Network connectivity reachable of safety
  messages
• Path redundancy
• Dynamic characteristics
• Connection duration
• Re-healing time

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Network connectivity

• Static characteristics of network connectivity
• Network connectivity Two vehicles can be
  connected either directly or indirectly (via a
  multi-hop route)
• Path redundancy between two vehicles the
  maximum number of (either node- or edge-)
  disjoint paths between two connected vehicles.

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Network connectivity

• network connectivity statistics averaged over 100
  simulation runs

Network type Density (veh/km2) Average network connectivity
Very sparse 40 68.12
Moderately sparse 60 97.97
Sparse 80 99.71
Moderate 160 100
Dense 240 100
Highly dense 320 100
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Network connectivity

• Average 20 neighboring vehicles gt network
  connectivity 100
• network connectivity is less than 80 in a very
  sparse network (40 veh/km2)
• Disconnected network problem may become a serious
  problem during the initial deployment of
  intelligent vehicles

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Network connectivity

• Path redundancy statistics

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Network connectivity

• number of redundant paths increases with the
  traffic density
• But does not necessarily decrease with distance
• Roughly 20 copies of the same message
• 8 more on the intersection
• In most cases, more than one path available
  between them

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Network connectivity

• Dynamic characteristics of network connectivity
• Number and duration of connected periods
• Re-healing time the duration of time during
  which two vehicles are disconnected

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Network connectivity

• Even in 80 veh/km2 dense network, the
  connectivity between two vehicles lasts for less
  than 6 minutes on average.
• These statistics become much worse when traffic
  density decreases
• 10 sec in 40 veh/km2 network

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Network connectivity

• Re-healing time

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Network connectivity

• 8 seconds of re-healing time in a very sparse
  network
• less than 3 seconds in a dense network

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Network connectivity

• The bipolar behavior connect ?
• not evenly distributed
• Broadcast storm problem becomes much more severe
  in a moderate or highly dense network
• Path redundancy
• Multi-path routing protocols

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Conclusion

• Cellular Automata (CA)-based mobility model
  analyzed the network connectivity pattern of
  urban traffic
• serious disconnected network problem
• bipolar behavior is observed where both the
  broadcast storm and the disconnected network
  problems coexist