1 Chapter 7: Modeling of Intermittent Connectivity in Opportunistic Networks: The Case of Vehicular Ad hoc Networks 1 Anna Maria Vegni, 2 Claudia Campolo, 2 Antonella Molinaro, and 3 Thomas D.C. Little BOOK ON ROUTING IN OPPORTUNISTIC NETWORKS 1 University of Roma Tre 2 University Mediterannea of Reggio Calabria 3 Boston University

2 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

3 Outline  Opportunistic Networks  The Case of Vehicular Ad hoc Networks  VANETs: an Introduction  Connectivity in VANETs  Modeling Connectivity  Improving Connectivity  Conclusions and Discussions

4 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

5 Opportunistic Networks – Techniques  Opportunistic networking techniques allow mobile nodes to exchange messages by taking advantage of mobility and leveraging the store- carry-and-forward 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

6 Opportunistic Networks – Types  Opportunistic networks include:  Mobile sensor networks [5]  Packet-switched networks [6]  Vehicular Ad hoc NETworks (VANETs) [7]

7 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

8 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

9 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 V2I V2V V2I RSU

10 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

11 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

12 VANETs  Enabling communication technologies  Wi-MAX  Long Term Evolution (LTE)  IEEE  IEEE p Centralized V2I/I2V communications Ad hoc V2V and centralized V2I/I2V communications

13 Connectivity in VANETs  There are three primary models for interconnecting vehicles based on: 1.Network infrastructure 2.Inter-vehicle communications 3.Hybrid configuration

14 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 Access Points, IEEE p RSUs

15 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)

16 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

17 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 Connectivity Communication range RSU Vehicular scenario Urban Highway Market penetration Vehicle density/speed Time of day

18 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

19 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, λ [veh/m] is the distribution parameter for inter-vehicle distances and R [m] is the radio range

20 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

21 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 traffic’s speed increases, the connectivity metrics decrease  If the variance of the speed’s distribution is increased, then, provided that the average speed remains fixed, the connectivity is improved

22 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]

23 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]

24 Modeling V2V-V2I Connectivity  List of the main common assumptions in connectivity models for VANET AssumptionAssumption Type Vehicle distributionPoisson Topology1D w/o traffic lights / intersections Underlying modelConnectivity graph Propagation modelUnit disk model RSUs’ distributionUniform

25 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

26 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

27 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

28 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)

29 Improving Connectivity in VANETs (a) (b)  Probability of connected vehicles (a) vs. the vehicle traffic density (Phases 1–3), and (b) vs. the vehicle traffic density and the connectivity range (Phase 1).

30 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

31 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

32 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

33 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

34 Thanks for your attention!