VANET technology

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Chapter 7 Modeling of Intermittent Connectivity
in Opportunistic Networks The Case of Vehicular
Ad hoc Networks
BOOK ON ROUTING IN OPPORTUNISTIC NETWORKS

• 1Anna Maria Vegni, 2Claudia Campolo, 2Antonella
  Molinaro, and 3Thomas D.C. Little

1University of Roma Tre 2University Mediteranneaof Reggio Calabria 3Boston University
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Objectives of the Chapter

• Analyze connectivity issues in Vehicular Ad hoc
  NETworks
• Provide an overview of vehicular connectivity
  models in the literature
• Discuss hybrid and opportunistic communication
  paradigms designed to improve connectivity in
  vehicular environments

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Outline

• Opportunistic Networks
• The Case of Vehicular Ad hoc Networks
• VANETs an Introduction
• Connectivity in VANETs
• Modeling Connectivity
• Improving Connectivity
• Conclusions and Discussions

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Opportunistic Networks

• Definition Opportunistic networks are one of the
  most interesting evolutions of Mobile Ad-hoc
  NETworks (MANETs)
• The assumption of a complete path between the
  source and the destination is relaxed
• Mobile nodes are enabled to communicate with each
  other even if a route connecting them may not
  exist or may break frequently

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Opportunistic Networks Techniques

• Opportunistic networking techniques allow mobile
  nodes to exchange messages by taking advantage of
  mobility and leveraging the store-carry-and-forwar
  d approach
• A message can be stored in a node and forwarded
  over a wireless link as soon as a connection
  opportunity arises with a neighbour node
• Opportunistic networks are then considered as a
  special kind of Delay Tolerant Network (DTN) 3,
  providing connectivity despite long link delays
  or frequent link breaks

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Opportunistic Networks Types

• Opportunistic networks include
• Mobile sensor networks 5
• Packet-switched networks 6
• Vehicular Ad hoc NETworks (VANETs) 7

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VANETs

• Definition
• A VANET (Vehicular Ad hoc NETwork) is a special
  kind of MANET in which packets are exchanged
  between mobile nodes (vehicles) traveling on
  constrained paths

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VANETs

• Like MANETs
• They self-organize over an evolving topology
• They may rely on multi-hop communications
• They can work without the support of a fixed
  infrastructure
• Unlike MANETs
• They have been conceived for a different set of
  applications
• They move at higher speeds (0-40 m/s)
• They do not have battery and storage constraints

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VANETs

• Communication modes
• Vehicle-to-Vehicle (V2V) among vehicles
• Vehicle-to-Infrastructure (V2I), between vehicles
  and Road-Side Units (RSUs)
• Vehicle-to-X (V2X), mixed V2V-V2I approach

V2V
RSU
V2I
V2I
V2V
RSU
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VANETs

• Applications
• Active Road-Safety Applications
• To avoid the risk of car accidents e.g.,
  cooperative collision warning, pre-crash sensing,
  lane change, traffic violation warning
• Traffic efficiency and management applications
• To optimize flows of vehicles e.g., enhanced
  route guidance/navigation, traffic light optimal
  scheduling, lane merging assistance
• Comfort and Infotainment applications
• To provide the driver with information support
  and entertainment e.g., point of interest
  notification, media downloading, map download and
  update, parking access, media streaming, voice
  over IP, multiplayer gaming, web browsing, social
  networking

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VANETs

• VANETs applications exhibit very heterogeneous
  requirements
• Safety applications require reliable,
  low-latency, and efficient message dissemination
• Non-safety applications have very different
  communication requirements, from no special
  real-time requirements of traveler information
  support applications, to guaranteed
  Quality-of-Service needs of multimedia and
  interactive entertainment applications

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VANETs

• Enabling communication technologies
• Wi-MAX
• Long Term Evolution (LTE)
• IEEE 802.11
• IEEE 802.11p

Centralized V2I/I2V communications
Ad hoc V2V and centralized V2I/I2V communications
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Connectivity in VANETs

• There are three primary models for
  interconnecting vehicles based on
• Network infrastructure
• Inter-vehicle communications
• Hybrid configuration

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Connectivity in VANETs

• Network infrastructure
• Vehicles connect to a centralized server or a
  backbone network such as the Internet, through
  the road-side infrastructure, e.g., cellular base
  stations, IEEE 802.11 Access Points, IEEE 802.11p
  RSUs

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Connectivity in VANETs

• Inter-vehicle communications
• Use of direct ad-hoc connectivity among vehicles
  via multihop for applications requiring
  long-range communications (e.g., traffic
  monitoring), as well as short-range
  communications (e.g., lane merging)

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Connectivity in VANETs

• Hybrid configuration
• Use of a combination of V2V and V2I. Vehicles in
  range directly connect to the road-side
  infrastructure, while exploit multi-hop
  connectivity otherwise

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Connectivity in VANETs

• Vehicles connectivity is determined by a
  combination of several factors, like
• Space and time dynamics of moving vehicles (i.e.,
  vehicle density and speed)
• Density of RSUs
• Radio communication range

RSU
Vehicle density/speed
Connectivity
Communication range
Time of day

• Vehicular scenario
• Urban
• Highway

Market penetration
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Modeling V2V Connectivity in VANETs

• Most of existing literature in VANET focuses on
  modeling the V2V connectivity probability
• Common assumption a vehicular network is
  partitioned into a number of clusters
• Vehicles within a partition communicate either
  directly or through multiple hops, but no
  direct connection exists among partitions

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Modeling V2V Connectivity in VANETs

• In a fragmented vehicular ad hoc network, under
  the DTN assumption and exponentially distributed
  inter-vehicle distances, the probability that two
  consecutive vehicles are disconnected is 28
• where X m is the inter-vehicle distance, ?
  veh/m is the distribution parameter for
  inter-vehicle distances and R m is the radio
  range

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Modeling V2V Connectivity in VANETs

• Accurate predictions of the network connectivity
  can be made using percolation theory, describing
  the behavior of connected clusters in a random
  graph
• In the stationary regime, assuming the spatial
  vehicles distribution as a Poisson process, the
  upper bound on the average fraction of vehicles
  that are connected to no other vehicles is 14
• The vehicular network is at a state that the rate
  of vehicles entering the network is the same as
  the rate of vehicle leaving it

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Modeling V2V Connectivity in VANETs

• The platoon size (i.e., the number of vehicles in
  each connected cluster), and the connectivity
  distance (i.e., the length of a connected path
  from any vehicle) are two metrics used to model
  V2V connectivity in VANETs 22
• When the traffics speed increases, the
  connectivity metrics decrease
• If the variance of the speeds distribution is
  increased, then, provided that the average speed
  remains fixed, the connectivity is improved

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Modeling V2I Connectivity in VANETs

• More challenging w.r.t. V2V case
• As vehicles move, connectivity is both fleeting,
  usually lasting only a few seconds at urban
  speeds, and intermittent, with gaps between a
  connection and the subsequent one
• Different vehicle placement conditions influence
  the overall connectivity, while RSUs do not
  significantly improve connectivity in all
  scenarios
• E.g., RSUs at intersections do not reduce the
  proportion of isolated vehicles, which are more
  likely to be in the middle of the road 14

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Modeling V2I Connectivity in VANETs

• The notion of intermittent coverage for mobile
  users provides the worst-case guarantees on the
  interconnection gap, while using significantly
  fewer RSUs
• The interconnection gap is defined as the maximum
  distance, or expected travel time, between two
  consecutive vehicle-RSU contacts.
• Such a metric is chosen because the delay due to
  mobility and disconnection affects messages
  delivery more than channel congestion 25

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Modeling V2V-V2I Connectivity

• List of the main common assumptions in
  connectivity models for VANET

Assumption Assumption Type
Vehicle distribution Poisson
Topology 1D w/o traffic lights / intersections
Underlying model Connectivity graph
Propagation model Unit disk model
RSUs distribution Uniform
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Improving Connectivity in VANETs

• Opportunistic approaches for connectivity support
  in VANETs
• Opportunistic contacts, both among vehicles and
  from vehicles to available RSUs, can be used to
  instantiate and sustain both safety and
  non-safety applications
• Opportunistic forwarding is the main technique
  adopted in DTN 55
• In VANETs, bridging technique links the
  partitioning that exists between clusters
  traveling in the same direction of the roadway

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Improving Connectivity in VANETs

• The use of a vehicular grid together with an
  opportunistic infrastructure placed on the roads
  guarantees seamless connectivity in dynamic
  vehicular scenarios 59-61
• Hybrid communication paradigms for vehicular
  networking are used to limit intermittent
  connectivity
• Vehicle-to-X (V2X) works in heterogeneous
  scenarios, where overlapping wireless networks
  partially cover the vehicular grid. It relies on
  the concept of multi-hop communication path

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Improving Connectivity in VANETs

• In V2X approach, there is the vehicular
  partitioning with different connectivity phases
• Phase 1 (No connectivity)
• A vehicle is traveling alone in the vehicular
  grid (totally-disconnected traffic scenario). The
  vehicles are completely disconnected
• Phase 2 (Short-range connectivity)
• A vehicle is traveling in the vehicular grid and
  forming a cluster with other vehicles. Only V2V
  connectivity is available
• Phase 3 (Long-range connectivity)
• A vehicle is traveling in the vehicular grid with
  available neighboring RSUs. Only V2I connectivity
  is assumed to be available

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Improving Connectivity in VANETs

• The probability that a vehicle lays in one of the
  three phases is expressed as the probability that
  a vehicle is
• Not connected (Phase 1)
• Connected with neighbours (Phase 2)
• Connected with RSUs (Phase 3)

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Improving Connectivity in VANETs

• (a)
  (b)
• Probability of connected vehicles (a) vs. the
  vehicle traffic density (Phases 13), and (b) vs.
  the vehicle traffic density and the connectivity
  range (Phase 1).

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Improving Connectivity in VANETs

• Satellite connectivity is used in VANETs for
  outdoor navigation and positioning services
• As an opportunistic link, it is intended to
  augment short and medium-range communications to
  bridge isolated vehicles or clusters of vehicles,
  when no other mechanism is available

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Conclusions and Discussions

• Connectivity issues in VANETs have been
  investigated
• Road topology, traffic density, vehicle speed,
  market penetration of the VANET technology and
  transmission range strongly affect the network
  connectivity behavior

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Conclusions and Discussions

• Analytical models deriving connectivity
  performance in VANETs have been discussed
• They differ into the underlying assumptions and
  the considered connectivity metrics
• Solutions improving connectivity in VANETs have
  been reviewed
• Exploiting infrastructure nodes, relay-based
  techniques and even satellite communications to
  bridge isolated vehicles when no other mechanism
  is available

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Conclusions and Discussions

• Analytical models play an important role in
  performance evaluation of VANETs and need to be
  significantly improved in terms of accurateness
  and realism
• Further efforts are required to design solutions
  enabling V2V and V2I connectivity in different
  network conditions to sustain both safety and
  non-safety applications

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Thanks for your attention!