Using Delay Tolerant Networks for Car2Car

communications

Laurent FranckENST, site of Toulouse

10 av. Edouard Belin, BP 44004F-31028 Toulouse Cedex, France, ETEmail: Laurent.Franck@enst.fr

Abstract- In this paper we identify and discuss the main issuesand challenges to implement a Delay Tolerant Network (DTN) toallow multi-hop Car2Car (C2C) -also known as Vehicle2Vehicle(V2V)- and car2infrastructure (C21) communications. C2C com-munications are designed to increase automobile security andcomfort, but a single hop is not enough [1]. Efficient networklayers are necessary to overcome these limitations'.

I. INTRODUCTION

New automobiles use increasingly higher electronic contentfor engine control systems, safety and entertainment. TheEuropean Union directives [2] and the automotive industry [3]are trying to incorporate new telematics capabilities in orderto:

. Reduce the number of accidents and reduce their impact.

. Share valuable information among cars (e.g. unexpectedtraffic jams).

. Distribute information among the vehicles when nobroadcast infrastructure is available (e.g. weather fore-casts). Conversely, it may be used to gather informationcollected by each vehicle (e.g. pollution data, road pave-ment defects, etc. ).

The Car2Car Communication Consortium [3] develops anEuropean industrial standard to enable inter-vehicle com-munications. The 802.1 lp working group discusses DSRC(Dedicated Short Range Communications) specific adaptationsof 802.11a to support operations in roadside to vehicle andvehicle communication environments [4]. In this context,multi-hopping must be considered raising the following issues:

. The nodes (cars) move in an unpredictable way.

. The links may be short lived.

. The network density (i.e. the average number of neigh-bors) is variable and may even be sparse with frequentlosses of connex property.

An adequate network layer is necessary to address thesechallenges: in this view, the popular TCP/IP based approachfails. Indeed, an end-to-end path may not always be availableand link outages have to be considered as normal events. TheDelay Tolerant Network (DTN) architecture is designed towork in such environments.

'This work is supported by the SatNEx-II European Network of Excellence.

Felipe Gil-CastineiraDepartamento de Enxefieria Telemaitica

Universidade de Vigo'SE Telecomunicacion, Campus, 36310 Vigo, Spain

Email: xil@det.uvigo.es

In section III we start by describing the DTN architectureand the main protocols. Section IV compares the DTN ap-proach with the one of vehicular ad-hoc networks (VANETs)from a packet loss and end-to-end delay standpoints. SectionV describes the automotive DTN platform currently developedin our laboratory.

II. BACKGROUND

The use of sensor networks for monitoring has recentlybecome a hot-topic. For example, ZebraNet [7] is a sensornetwork with wireless connectivity developed to track longterm animal migrations. TrafficLab [9] uses inter-vehicular adhoc networks to collect and disseminate traffic information ina road.The FleetNet [8] and the NoW [10] projects study the multi-

hop wireless networks to improve the drivers and passengersecurity and comfort making use of the inter-vehicular com-munication.

III. DELAY TOLERANT NETWORKS (DTN)

The Delay Tolerant Network (DTN) research grouphas defined an architecture based on a store and forwardparadigm [5] to interconnect networks, even without end-to-end connectivity. Each DTN node may store packets and, whenappropriate, forward them towards the destination throughintermediate nodes. As far as Car2Car communications areconcerned, a specific application of DTN is of interest: datamules. A data mule is a DTN node making use of the nodemotion to extend the network coverage and/or the number ofcommunication opportunities.

DTN is still work in progress. Current DTN researchtopics considered as "hot" are: routing, unreliable and reliablemulticasting and security. These issues are also present inCar2Car networks.

The core protocol of the DTN architecture is the bundleprotocol [6]. It spans over layer 3 and 4, providing reliablebundle (message) switching with an optional custody(storage) capability. DTN nodes have addresses calledEndpoint IDentifiers. Because a DTN is meant to provideinternetworking among different heterogeneous networks, it

1-4244-0755-9/07/$20.00 (C2007 IEEE 2573

is organised as an overlay network: DTN nodes are layedout in an arbitrary topology, however a link between twoDTN nodes may pass transparently through several non-DTNnodes. Figure 1 shows an example of overlay network.

PC

Earth st

Internet region

Small sat

Lation BBS

)LE BUNDLE

xc X-CV

Packet ri AX.25

Packet radio region

Fig. 1. DTN stack and overlay network

IV. DTNs AND VEHICULAR AD-HOC NETWORKS(VANETs)

Vehicular networks can be categorized into three groups[1 1].

. Pure wireless vehicle-to-vehicle ad-hoc network (C2C).

. Wired backbone with wireless last-hop (C21).

. Hybrid architecture combining the two.

Here we consider VANET networks, because the existenceof a wired backbone system is not a realistic approach (atleast in the next years), due to the expensive cost of awired backbone deployment. We evaluate the exchange ofinformation among vehicles, or between a vehicle and a fixedstation, within radio range.A VANET is a special Mobile ad-hoc Network (MANET)

with some differentiating characteristics. Before discussingthem, it is convenient to mention MANET attributes andrequirements [12]:

. Self-organization: A MANET does not depend on apreexisting infrastructure, it creates a infrastructure withinthe wireless network itself: each node has to determineits address, neighbors, position, power control, etc.

. Mobility: This attribute is the main difference betweena MANET and a sensor network. The network andapplication level protocols have to be designed accordingto the mobility pattern.

. Multi-hopping: Certain nodes can be reached only rout-ing over other units.

. Energy conservation: Common MANETs are composedof small devices with limited power supply.

. Scalability: Certain MANET applications can grow atany moment. This attribute is very complex, jointly withthe mobility.

. Security: Due to its wireless nature, the security is acomplex problem in MANETs. Moreover, the complexityof the protocols makes it harder to detect attacks.

The special characteristics of a VANET are [11]:

. Predictable mobility: The vehicles can not follow anydirection, as they have to stay in the roadway, and theycan not change their direction of motion suddenly.

. High mobility: The network topology changes rapidlybecause of the the vehicle speed.

. Large scale: The large amount of vehicles in the roadsare potentially nodes in a VANET.

. Partitioned networks: The range of the wireless com-munications used in C2C networks is near 1000 meters[4], so it is very probable that a vehicle may be out ofrange of another vehicle.

. No significant power or computation constraints: Avehicle can generate sufficient electric power to feed acommunications system and a powerful computer.

As we stated before, the network and application levelprotocols have to be designed according to the MANETcharacteristics. The DTN model solves part of the problemsin a VANET, specially the partition issue, thanks to thestore and forward paradigm. This will be demonstrated bymeans of simulations in the next sections. We compare theperformance of DTN enabled VANETs (DTNs for short) andpure VANETs (VANETs for short).

A. Scenario for comparing DTN and VANETs

The major objective of these simulations is to comparehow pure VANETs and DTN enabled VANETs performunder different network conditions. The simulation modelis organised in several modules: network topology, trafficgeneration, routing protocol and performance metrics.Except where explicitly stated and in order to ensure a faircomparison, all modules are identical for the VANET andDTN. The simulator is of discreet event type, developed inC language for this study. Simulations last for 500.103 TU(time units) which is sufficient to achieve stable results.

1) Network topology: The network is made of 10 nodesrandomly scattered in a 2000 x 2000 point square space.The node motion model is a step by step ray trace modeloccurring every 10 TU. The initial position and directionof motion is chosen randomly. Each step can span up to40 points on the x and/or y axis with possible bounces onthe space boundaries. This motion model albeit simplisticgenerates some randomness while keeping the results general.More specific models will be investigated in the future.

Two nodes can communicate provided they are withinEuclidean distance d. d represents the RF range of theemitter. Within this footprint, the experienced EB/NOmakes demodulation feasible. Several values of d areconsidered yielding an RF footprint from 0.2% to 64% of theroom surface. These variations will be reflected through aparameter called average number of RF neighbors. Figure 2shows the average number of RF neighbors as a function of d.

2574

4

3.5 _

3 _

2.5 _

2 k

1.5 _

0.5 _

n0 100 200 300 400 500 600 700 800

RF range

Fig. 2. Average number of RF neighbors as a function of Euclidean distance d (RF range).

2) Traffic generation: Each node acts as a traffic source

(and sink). Every 50 TU, each source issues a packet to a

random destination for a total of 10.103 packets per source

during the complete simulation.

3) Routing protocol: Routing is based on controlled flood-ing. Upon reception of a packet, a node will broadcast thispacket to its RF neighbors. Transmitting a packet from one

node to another consumes 1 TU, hence for VANETs end-to-end delay and number of hops are equal. For DTNs, the end-to-end delay comprises the storage (custody) time plus thetransmission delay. Several cases may arise during flooding:

1) The node has previously received the same packet. Upto n duplicates are accepted, further duplicates beingdestroyed. In our simulations, n is arbitrarily set to 4.Fixed networks would set the limit to 2, however inmobile networks, duplicates may get a another chanceto reach the destination depending on the network con-

ditions.2) The node receiving the packet sees the destination. The

packet is therefore delivered with further flooding.3) The node receiving the packet has no RF neighbors save

the one the packet was received from. If such a case

happens in the VANET, the packet is destroyed. In theDTN, the packet is stored and retransmitted (if possible)once the node has moved. This is the only differencebetween the VANET and DTN.

4) In all other cases, the node floods RF neighbors withthe packet.

Selecting flooding based routing may seem unrealistic,however this guarantees a fair comparison between VANETsand DTNs. Indeed, it is likely that the performance of a

routing protocol such as Ad-hoc On-demand Distance Vector

(AODV) [13] would have been poor considering the possiblenetwork partitions. Moreover, nothing guarantees that AODVfits to DTNs. The drawback of flooding based routing is thesignificant overhead in terms of duplicate data packets. Thisissue is not relevant considering the performance metricswhich are considered.

4) Performance metrics: The network performance is mea-sured according to two metrics: packet loss ratio: when a

packet sent by a source never reaches the destination (i.e. whenall duplicated were lost) and end-to-end delay. These metricswill be evaluated for VANETs and DTNs as a function of thenetwork density which relates to the average number of RFneighbors, the latter being impacted by the parameter d as

mentioned before.

B. Results

This section covers the results achieved through varioussimulation experiments. VANETs and DTNs are comparedfrom packet loss and end-to-end delay standpoints. Severalnetwork configurations are evaluated by varying the networkdensity.

1) Packet loss comparison: Figure 3 shows the evolutionof the packet loss ratio as a function of the average numberof RF neighbors (i.e. the network density). Two trends can

be isolated: (a) increasing the network density decreases thepacket loss ratio and (b) whatever the network density, packetloss occurs more frequently in the VANET (still the differenceis least as the network density increases). As a reminder, a

packet is considered lost when none of its duplicates reachesthe destination.

2575

"neighbors"

0n

a3a)

a)

a:

900

1

0.9 - A

0.8

0.7 _ Pyy

0.6 _000 'V

0.5~~~~~~~~~~~S

4 _ <

.2

0 0.5 1 1.5 2 2.5 3 3.5Average number of neighbors

Fig. 3. Packet loss ratio as a function of the number of RF neighbors (VANET and DTN).

In the case of VANETs, nodes with at most one RF neighborare likely to experience high packet losses. Increasing thenetwork density therefore limits such cases. DTNs shouldnot be affected thanks to their storage capability, this isthe reason why VANETs always experience a higher packetloss. Surprisingly, packet losses occur in the DTN as well.They are caused by routing loops inside isolated clusters ofnodes (a cluster is a set of interconnected nodes isolatedfrom the rest of the network). These clusters capture packets,increasing their duplicate counters as they are forwarded backand forth, eventually ending in their dismissal (and loss). Fornetwork densities less than 0.1, there are almost no clusters,hence routing loops, hence packet losses. The next sectionwill show that a low packet loss turns into high end-to-enddelay. When the network density increases, clusters are

created which increases the packet loss ratio. Duplicates are

dismissed without the opportunity to reach the destination.When the network is sufficiently dense (larger than 1), some

of the duplicates eventually reach the destination. In suchcases, destroying the other duplicates is not harmful andcould even be considered as a valuable self-cleaning behaviorof the network.

For a fair comparison, it is necessary to consider end-to-enddelay as well.

2) End-to-end delay comparison: Figures 4 to 6 showsthe end-to-end delay distribution for VANETs and DTNsconsidering different network densities. For sparse network(density=0.07), the VANET exhibits an all or nothingbehavior: either the source node is close to the destination (insuch case, the end-to-end delay equals one hop) or all packetsare lost. For the DTN, although the packet loss ratio is one

tenth of the VANET, the end-to-end delays are prohibitive(up to 200.103 TU). This unrealistic case shows the actualtradeoff: reliability against end-to-end delay.

For moderately sparse networks (density=1.01) DTNs may

still experience higher end-to-end delay (up to 3051 TU)however (a) such cases have a low probability (below 0.001)and (b) this the price to pay to order to have the packetloss ratio decreasing from 84% to 38%. A closer look at thesimulation traces reveals that the DTN packets experiencinga higher delay are those lost in the VANET.

Finally, for dense networks (density=3.13), DTNs approachthe end-to-end delay performance of VANETs (at a lowerPLR).

Table I summarizes the distribution characteristics.

V. AUTOMOTIVE DTN PLATFORM

In order to study the issues with a DTN implementation over

C2C networks, we have studied modern automotive electronicdevices and we have developed an automotive-grade hardwareplatform. This platform allows the transmission of CAN datafrom a vehicle to another one or a fixed infrastructure througha wireless interface, following the DTN paradigm.

A. Platform requirementsThe automotive platform may collect information from

different sensors in the vehicle and send this informationthrough a DTN, so it requires:

. An interface with vehicle sensors (CAN bus integration).

. A LAN or WAN interface: GPRS and Wireless LANintegration.

2576

0

a)0)

4

11

0.009

0.9

0.8

0.7

0.6

n2 0.5

050.4

0.3

0.2

0.1

0.008

0.007

0.006

0.005

0.004 _

0.003

0.002

0.001

1 1.5 2 2.5 3 0 5000 10000 15000 20000 25000 30000 35000

E2D Delay (TU) E2D Delay (TU)

Fig. 4. End-to-end delay distribution for a sparse network (density=0.07). Left column: VANET (PLR=0.99), right column: DTN (PLR=0.08).

0.7

0.6

0.18

0.16

0.14

0.50.12

. 04

n

0 0.3

0.1

F 0.08

0.060.2

0.04

0.10.02

0 2 4 6 8 10 12E2D Delay (TU)

Fig. 5. End-to-end delay distribution for a moderately sparse network (density=

0.5

0 500 1000 1500 2000 2500 3000 3500

E2D Delay (TU)

=1.01). Left column: VANET (PLR=0.84), right column: DTN (PLR=0.36).

045

0.4k0.4

0.35

0.350.3

0.3

025n2 0.25I)

020.2

0.15

0.1

0.05

0.25

0.15 [0.1

0.05

0 2 4 6 8 10 12 14 0 100 200 300 400 500 600 700 800E2D Delay (TU) E2D Delay (TU)

Fig. 6. End-to-end delay distribution for a dense network (density=3.13). Left column: VANET (PLR=0.24), right column: DTN (PLR=0.12).

TABLE I

DISTRIBUTION CHARACTERISTICS FOR END-TO-END DELAY (TU).

2577

Scenario Min Max Mean Std. dev. Percentile 0.90Sparse 1.0 3.0 1.029 0.2 1.0

VANET Mod. sparse 1.0 12.0 1.43 0.75 2.0Dense 1.0 13.0 1.83 0.98 3.0Sparse 1.0 32681.0 3218.13 3154.04 7391.0

DTN Mod. sparse 1.0 3051.0 257.27 306.72 671.2Dense 1.0 702.0 16.72 47.85 52.0

0 11-i

O ,,

LI)

.2

2nLI

Fig. 7. Automotive DTN Platform

* Enough computational power.Another requirement is the usage of automotive-grade elec-

tronics and common devices in the automotive market. Bydoing so, the results can be easily adopted by car manufactur-ers.

Although there exists products (such as Freescale Me-dia5200) that fulfill the requirements, we have developed acustom platform with commercial modules. We have chosenthe PC/104 computer standard because it is a well-knownembedded specification. We have added different devices toa PC/104 stack to meet our requirements:

* Vehicle power source.* 32-bit Cardbus WiFi card.* CPU Board (Men mikro elektronic PPO1)

- PowerPC MPC5200/B 384 Mhz, designed for auto-motive applications.

- 1 Fast Ethernet,- Dual UART and dual CAN.

VI. CONCLUSIONS

In this paper, we have presented the attributes and require-ments of a C2C network and how a DTN can help to overcomethe limitations to create an end-to-end communication. Asimulator was created to compare how pure VANETs and DTNenabled VANETs perform under different network conditions:pure VANETs experience a higher packet loss, but contraryto expected, DTN enabled VANETs also lose packets due tothe routing loops inside isolated clusters of nodes. For sparsenetworks DTNs suffer from very high delays, but in this caseVANETs lose most of the packets. We have also presented aprototype developed to create a test-bed for future C2C andDTN studies.

REFERENCES

[1] Sascha Schnaufer, Holger FIBler, Matthias Transier and Wolfgang Effels-berg. Vehicular Ad-Hoc Networks: Single-Hop Broadcast is not enough.Proc. of the 3rd International Workshop on Intelligent Transportation (WIT2006).

[2] European Commission eSafety Initiative [Online], November 2006.http://europa.eu.int/information_society/activities/esafety.

[3] Car2Car Communication Consortium [Online], November 2006.http://www.car-to-car.org

[4] ASTM International. ASTM E2213-03: Standard Specification forTelecommunications and Information Exchange Between Roadside andVehicle Systems -5 GHz Band Dedicated Short Range Communications(DSRC) Medium Access Control (MAC) and Physical Layer (PHY) Spec-ifications. 2003.

[5] K. Fall. A Delay Tolerant Networking Architecture for Challenged Inter-nets. Proc. SIGCOMM 2003, August 2003.

[6] K. Scott and S. Burleigh. Bundle Protocol Specification. draft-irtf-dtnrg-bundle-spec-05 .txt.

[7] P. Juang, H. Oki, Y. Wang, M. Martonos, L. Peh and D. Rubenstein,Energy-efficient computingfor wildlife tracking: Design tradeoffs and earlyexperiences with Zebranet. Proc. ASPLOS 2002.

[8] Martin Mauve, Joerg Widmer and Hannes Hartenstein. A survey onposition-based routing in mobile ad hoc networks. IEEE Network Maga-zine, pp. 30-39, November/December 2001.

[9] M. D. Dikaiakos, S. Iqbal, T. Nadeem and L. Iftode. VITP: an informationtransfer protocol for vehicular computing. Workshop on Vehicular Ad HocNetworks, 2005.

[10] Network-on-Wheels [Online], November 2006.http://www.informatik.uni-mannheim.de/pi4/projects/now/

[11] Hao Wu, R. Fujimoto and G. Riley. Analytical Models for InformationPropagation in Vehicle-to-Vehicle Networks. Vehicular Technology Con-ference, 2004. VTC2004-Fall. 2004 IEEE 60th.

[12] M. Gerla. From battlefields to urban grids: new research challengesin ad hoc wireless networks. Pervasive Mob. Comput. 1, 1 (Mar. 2005),77-93.

[13] C. Perkins, E. Belding-Royer and S. Das. Ad hoc On-Demand DistanceVector (AODV) Routing. Internet Engineering Task Force, RFC 3561, 2003.

2578