IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 5, NO. 4, DECEMBER 2004 347

Challenges of Intervehicle Ad Hoc Networks

Jeremy J. Blum, Azim Eskandarian, and Lance J. Hoffman

Abstract—Intervehicle communication (IVC) networks, a subclass ofmobile ad hoc networks (MANETs), have no fixed infrastructure andinstead rely on the nodes themselves to provide network functionality.However, due to mobility constraints, driver behavior, and high mobility,IVC networks exhibit characteristics that are dramatically different frommany generic MANETs. This paper elicits these differences throughsimulations and mathematical models and then explores the impact of thedifferences on the IVC communication architecture, including importantsecurity implications.

Index Terms—Intelligent transportation systems (ITSs), intervehiclecommunication (IVC), mobile ad hoc networks (MANETs).

I. INTRODUCTION

In the future, vehicles will likely be equipped with communicationcapabilities that allow for intervehicle communication (IVC). IVCwould perform crucial functions in collision avoidance, road-hazardnotification, and coordinated driving systems. IVC networks are aninstantiation of a mobile ad hoc network (MANET). MANETs haveno fixed infrastructure and instead rely on ordinary nodes to performrouting of messages and network management functions.

However, automotive ad hoc networks will behave in fundamentallydifferent ways than the models that predominate MANET research.Driver behavior, constraints on mobility, and high speeds create uniquecharacteristics in IVC networks. These characteristics have importantimplications for design decisions in these networks.

In particular, IVC networks differ from typical MANET models infour key ways. They are characterized by rapid but somewhat pre-dictable topology changes, with frequent fragmentation, a small effec-tive network diameter, and redundancy that is limited temporally andfunctionally. This paper quantifies these characteristics through simu-lation and explores their implication for the functionality and securityof the IVC network architecture.

II. RELATED WORK

Related work in MANETs has focused on many of the layers of thecommunications architecture. This section reviews some of the relevantMANET research results from the various architectural layers. How-ever, as shown in Section III, these results have limited applicabilityfor the IVC network.

A. MANET Link Layer

Two issues that have been extensively studied at the link layer arethe complementary problems of hidden and exposed nodes, and theireffect on throughput [1].

Manuscript received December 1, 2003; revised July 16, 2004 and July31, 2004. This work was supported in part by Cooperative AgreementDTFH61-99-X-00038 between the U.S. Department of Transportation, Fed-eral Highway Administration, and The George Washington University. TheAssociate Editor for this paper was F.-Y. Wang.

J. J. Blum and A. Eskandarian are with the Center for Intelligent SystemsResearch, The George Washington University, Washington, DC 20052 USA(e-mail: blumj@gwu.edu).

L. J. Hoffman is with the Computer Science Department and the Cyber Se-curity Policy and Research Institute, The GeorgeWashington University, Wash-ington, DC 20052 USA.

Digital Object Identifier 10.1109/TITS.2004.838218

Fig. 1. Hidden and exposed nodes.

Hidden nodes are two nodes that, although they are outside the in-terference range of one another, share a set of nodes that are within thetransmission range of both. As shown in the left-hand side of Fig. 1,nodes A and C are outside the transmission range of each other. If bothattempt to transmit at the same time, they will cause a collision at B.Exposed nodes, on the other hand, are nodes that are within interferencerange of each other. As shown in the right-hand side of Fig. 1, althoughA and C are within interference range of each other, A could transmit toB and C could transmit to Dwithout causing a collision at either B or D.However, since they are within interference range of each other, only Aor Cwould transmit at a time. The effect of hidden nodes on throughputis handled by request-to-send/clear-to-send (RTS/CTS) handshaking.However, exposed nodes are difficult to address and present one of themost important factors in limiting network throughput.One way to increase network throughput is to increase the number

of nodes in the network. One study with random mobility noted thatan increase in network size while holding traffic load constant yieldsincreased throughput [2].

B. MANET Routing Layer

At the routing layer, MANET research has focused on the develop-ment of three broad classes of routing protocols, analysis of these ap-proaches under various mobility models, and attempts to manage mo-bility-related routing issues.MANET routing protocols, which do not use nodal position data,

can be classified as table- or source-driven [3]. Table-driven proto-cols, DSDV for example, are proactive in the sense that each node at-tempts to maintain a current representation of the network topology.Source-driven protocols, on the other hand, are reactive in the sense thatroutes are requested by source nodes only when needed. Table-drivenprotocols provide lower message latency because routes are imme-diately available. However, the overhead required to maintain theseroutes consumes bandwidth and restricts the scalability of these pro-tocols.Another class of routing protocols uses position-based information

for routing decisions [4]. A location service may then be necessary tofind the location of a destination node. These protocols also naturallysupport geocasting, i.e., location-based multicast [5]. In location-basedmulticast, the set of recipients is defined as nodes located in some targetregion of space.A number of mobility models have been used to analyze routing

protocols. The most commonly used is the random waypoint model,for example [6]. In this model, nodes move in a random direction for arandom amount of time, pause for some period of time, and then choosea different direction.This random waypoint model conjures up a “a world where people

constantly try to pass through walls and cars suddenly leave the roadsand drive into rivers” [7, p. 309]. To provide a more realistic model,they devise a graph-based mobility scheme for their analysis of peoplewalking in a city.

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348 IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 5, NO. 4, DECEMBER 2004

Another approach at a more realistic mobility model is scenario-based mobility, which considered scenarios of people moving at asporting event, in a disaster area, and at a conference [8]. Interestingly,the authors found that the analysis from the random waypoint modelcorresponded to their scenario-based analysis well.

Mobility presents a number of problems for MANETs, includingshort-lived paths between nodes and network partitioning. Flow-ori-ented routing protocol attempts to manage short-lived paths by usingnodal mobility information to predict the stability of routes in a source-driven protocol [9]. Epidemic routing attempts to gracefully handlesituations in which no path exists between the source and destinationnodes [10]. Each node contains a queue of messages to be delivered.When a node encounters another node, the nodes exchange the identifi-cations of messages in their queues. Messages that have not been seenby a node will be exchanged.

C. MANET Security

Because MANETs lack a fixed infrastructure and rely on untrust-worthy nodes for the propagation of control and data messages, se-curing a MANET is very difficult. Research for security controls forMANETs have included secure routing protocols, secure transport pro-tocols, and intrusion-detection systems.

Secure routing proposals have included cryptographic techniques,including hash chains and digital signatures, to ensure the validity ofrouting messages [11], [12]. By increasing message size, these proto-cols limit available bandwidth. However, for stable routes, this addi-tional load may not be significant.

Since the transport of messages relies on possibly untrustworthynodes, not only are routing messages subject to corruption, but datamessages also are. Secure message transport (SMT) attempts to ad-dress this problem by utilizing the redundancy in the network [11].SMT cryptographically splits a message into n parts and sends eachpart over a distinct path. As long as k pieces are received, the messagecan be decoded. SMT, therefore, requires multiple independent pathsbetween a source and a destination and spare bandwidth.

Intrusion-detection systems for MANETs attempt to identify nodesthat are acting maliciously by fabricating, dropping, or altering con-trol or data messages [13], [14]. In these systems, nodes overhear theirneighbors’ broadcasts in order to ensure that these neighbors are actingappropriately. In order for this eavesdropping technique to be effective,the models assume omnidirectional antennas.

III. SIMULATION OF THE IVC NETWORK

In order to assess the applicability of the observations in the relatedresearch, an IVC network was simulated. This section describes thepackages used to conduct the simulation, the scenarios that were sim-ulated, and the simulation results.

A. Simulation Packages

The simulation of an IVC network was done using two widely usedsimulation packages. CORSIM was used to generate realistic vehiclemobility data and NS2 was used to generate realistic wireless networkbehavior.

CORSIM is the most widely used microscopic vehicle trafficsimulation program in the United States [15]. As a microscopic trafficsimulation, it tracks each individual vehicle. The vehicle’s mobility isdetermined by driver behavior, vehicle performance characteristics, andconstraints imposedby the roadwaygeometryand surroundingvehicles.

The network simulator (NS) is a widely used computer network sim-ulator developed by the University of California, Berkeley, and the vir-tual internetwork testbed (VINT) project [16]. This study used the mul-tihop ad hoc wireless extensions provided by the Monarch researchgroup at Carnegie Mellon University, Pittsburgh, PA.

B. Simulation Scenarios

The vehicle simulation simulates traffic on a section of I-880 in Hay-ward, CA [17]. Data for traffic flows on various dates in 1993 wascollected by the Freeway Service Patrol Evaluation Project, Universityof California, Berkeley. The author modeled the roadway geometry inCORSIM to roughly correspond to the 9.2-mi section of road, with tenexits and ten on-ramps.Based on traffic data that was collected for March 13, 1993, a sce-

nario was created for this roadway that models average traffic withouthigh-occupancy vehicle (HOV) lanes. In this scenario, 20% of the ve-hicles were assumed to be equipped with IVC equipment. This highdeployment rate was chosen to give a conservative picture of the dif-ficulties that will be encountered in this network. The analysis in thefollowing sections was done with radio ranges ranging from 25–500 ft.

C. Results

The results of these simulations indicate that the IVC network isfundamentally different from the networks studied in other MANETresearch. The major results of the following sections are as follows.

1) Rapid changes in the IVC network topology are difficult tomanage.

2) The IVC network is subject to frequent fragmentation, even ata high rate of IVC deployment.

3) The IVC network has an even smaller effective network diam-eter under source-generated routing.

4) Unlike the redundancy in other MANETs, the redundancy inIVC networks are severely limited both in time and in function.

1) Rapid Topology Changes: Despite the severe constraints on themovement of vehicles (i.e., they must stay on the roadways), the IVCnetwork experiences very rapid changes in topology. These changesare due to the high relative speed of vehicles, even when moving inthe same direction. The direction of vehicle movement, though, haspredictive value for the stability of these links.Fig. 2 shows that the link life is affected by the direction of the ve-

hicles and the radio range. The longer the radio range, the longer thelinks last. Links between vehicles traveling in opposite directions arevery short lived when compared to links between vehicles traveling inthe same direction.A striking result, though, is the extremely limited nature of links,

even for vehicles traveling the same direction with long transmissionranges. Even with a long transmission range of 500 ft, these links lastapproximately 1 min on average. As shown later, the effect of this shorttime is further exacerbated if a message must traverse several hops.Unfortunately, as shown in the next sections, the approaches to in-

creasing link life suggested by this analysis have an adverse affect onother desirable attributes. Discarding vehicles traveling in an oppositedirection increases network fragmentation. Increasing the radio rangehas a dramatic adverse affect on network throughput.

2) Frequent Fragmentation: The IVC network will be subject tofrequent fragmentation, in which chunks of the network are unable toreach nodes in nearby regions. This analysis is based on the optimisticgoal of having IVC in 20% of vehicles. Due to slow introduction andadoption, deployment is likely to be lower for quite some time. Withlower and more immediately realizable deployment ratios, the frag-mentation would increase.Fig. 3 shows this fragmentation when all nodes with IVC versus only

those nodes traveling in the same direction. The connectivity fell inthe checkered regions. Although the connectivity increased as radiorange increases, at 500 ft, a node could often reach only 37% of theother nodes on this section of highway. Asmentioned earlier, increasingradio range comes at a heavy price. If routes containing nodes travelingin opposite directions are discarded, the connectivity between nodestraveling the same direction is sharply reduced to as little as 16% at the500-ft transmission range.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 5, NO. 4, DECEMBER 2004 349

Fig. 2. Link life for various radio ranges.

Fig. 3. Network connectivity by radio range.

3) Small Effective Network Diameter: As poor as the nodal con-nectivity is, the effective network diameter is actually worse. Rapidchanges in link connectivity causemany paths to disconnect before theycan be utilized.

Proactive routing is only suitable for small networks with limitedmobility due to the overhead ofmaintaining the data on the full networktopology at each node. Reactive routing was designed to improve thisby initiating route discovery only when a path is needed. However, forIVC, a path may cease to exist almost as quickly as it was discovered.

Fig. 4 shows the expected path lifetime using only nodes travelingin the same direction versus the path setup time for a communicationrange of 250 ft. In NS, an ftp connection in a wireless network wassimulated. There was no other network traffic at the time so, in reality,the response time would actually be worse. As shown in this figure, atapproximately nine hops, before the first packet can be acknowledged,the path has disappeared. Furthermore, the precipitous drop in routelifetime indicates that sending even a relatively small message overthree or four hops is likely to suffer a route error. Therefore, protocolsthat find routes before sending messages are likely to perform poorlyin IVC networks.

4) Limited Redundancy: The redundancy in MANETs is crucialto providing additional bandwidth and security features. If additionalbandwidth is desired, more nodes can be added. Security schemesuse independent redundant paths to provide secure message transport.However, in IVC, the redundancy is limited both temporally andfunctionally.

The limited route lifetime becomes even more acute if multipleroutes are needed simultaneously. The effective lifetime of this bundleof routes is the lifetime of shortest lived route. Clearly, this is prob-lematic for schemes whose robustness requires multiple routes.

As noted by earlier research, one of the most critical factors lim-iting the bandwidth in a generic MANET is the number of exposed

nodes. Furthermore, there is a relationship between radio range andthe number of exposed nodes. This relationship is quadratic for a com-pletely random mobility model. Because of constraints on movement,the number of exposed nodes for IVC only grows linearly. This linearrelationship might present hope for increased throughput in IVC. How-ever, the available transmissionmedium is also saturated linearly, so theslower growth in the number of exposed nodes does not yield betterthroughput.Themaximum for vehicles traveling on a given section of highway is

a function of the bit rate and the interference radius. Since a vehicle willonly transmit data if it hears no transmissions in its interference radius,only one vehicle will transmit within this neighborhood. Consequently,the maximum throughput is given by (1), where Tmax is the maximumthroughput, Br is the bit rate, L is the highway length, and Ri is theinterference radius.

Tmax = Br � L=(2 �Ri): (1)

Since the interference radius is proportional to the radio range, in-creasing the radio range to increase link stability, path life, or networkconnectivity will decrease the network throughput. Furthermore, sincethe network throughput is severely limited, adding redundant nodes tothe network will not increase bandwidth as it did for other MANETs.

IV. DESIGN IMPLICATIONS

These differences between IVC networks and other MANETs haveimplications for the design of IVC communications architecture. TheIVC physical, link, and network layers must address the limited band-width as well as the unstable and fragmented network topology. Secu-rity mechanisms in the IVC network must also work within the con-straints of the limited bandwidth and cannot rely on the redundancynormally present in MANETs.

A. Physical Layer Implications

One of the most acute challenges that will be faced by the IVC net-work is the high demand for limited bandwidth. There are two typesof safety-critical messages that will likely be transmitted over the net-work. A-periodic messages will contain information about roadwayand environmental hazards and will be transmitted only occasionally,but with a requirement of fast and guaranteed delivery. Periodic mes-sages containing the vehicle position, dynamics, and driver intentionswill likely be transmitted at a very high frequency—between 10–20times per second for each vehicle.The limited bandwidth in the IVC network can be partially addressed

at the physical layer. Different frequency bands could be devoted tothe different types of messages, with varying transmission powers for

350 IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 5, NO. 4, DECEMBER 2004

Fig. 4. Route lifetime versus route setup time.

each. For example, one approach uses a combination of low-frequencylong-range infrastructure-based communications and high-frequencyvehicle–vehicle communication in order to accommodate the varyingdelivery requirements for each message type [18].

The transmission power can be adaptively lowered to the point whereit is just enough so that it is enough to reach a recipient. This reduces theinterference range and, thus, linearly increases the network throughput,as seen in (1). Initially, with low levels of IVC equipment deployment,longer transmission ranges have been proposed as a way to realize mul-tihop communication [19].

Another way to reduce the interference range is to use directional-ized antennae. In this way, a transmission interferes only with nodesin the direction of the transmission. However, directionalized antennasincrease the number of hidden nodes and, as shown later, have an ad-verse affect on intrusion-detection systems.

B. Link Layer Implications

The link layer must address a number of important issues related tobandwidth utilization. For example, it must address congestion control,latency, throughput, fairness, and scalability with respect to the numberof equipped vehicles.

The 802.11 Distributed Coordination Function has been proposedfor use for the IVC link layer [20]. Unfortunately, given the high de-mand for bandwidth, this approach is likely to result in a large numberof collisions. Explicit allocation of timeslots, frequencies, or codes isproblematic because of the highly dynamic topology of the IVC net-work. When vehicles encounter congestion, the number of vehicleswithin radio range sharply increases, necessitating a reallocation of thecodes. High relative velocities also contribute to a need for reallocation.

In other MANETs, the addition of nodes provided additional band-width andexposednodes are aprimary factor in limitingbandwidth.Duetoconstraintsonmobility, inanIVCnetwork, the limitonavailableband-width is reachedmorequickly.Addingadditionalnodeswill not increasebandwidth. Furthermore, the slower growth in the number of exposednodes with respect to radio range fails to represent this situation.

Congestion control at this layer must organize access to the lim-ited media in an equitable and efficient manner. Safety-critical mes-sages must have guarantees on their delivery. This guarantee couldbe provided through the separation in time or space of these trans-missions. For example, time slots or spectrum could be reserved. Al-ternatively, additional radio operating on a different frequency couldbe added to completely separate these messages. This additional radiowould allow for the simultaneous transmission and reception of safety-critical messages.

One approach to distributed reservation scheme extends theR-ALOHA protocol [21]. In this protocol, vehicles rely on their neigh-

bors to determine if their request for a slot has succeeded. However,given the volatility of neighbor sets under vehicular mobility, it isunclear if this approach will yield an unacceptably high number ofcollisions.Other decentralized schemes that avoid collisions altogether allocate

time slots based on the location of the vehicles [22], [23]. The roadwayis discretized into cells such that only one vehicle may occupy a cell at atime. Each cell is associated with a time slot or channel that is assignedin such a way to prevent collisions while promoting special reuse.

C. Routing Layer Implications

The IVC routing layer must efficiently handle rapid topologychanges and a fragmented network. Current MANET routing proto-cols fail to fully address these specific needs.Neither proactive nor reactive routing protocols are suitable for

the IVC network. Proactive protocols will be overwhelmed by theextremely rapid rate of change in the topology. Reactive protocols areproblematic in that they attempt to discover a route before sendinga message. Unfortunately, the routes discovered have an expectedlifetime that precludes all but the routing of the shortest of messages.The alternative then is to use location-based routing. Briesemeister

et al. argue that this should be used because messages will likely bedelivered to vehicles in a zone of relevance for a given message [24].More importantly, it is shown here that is no other feasible way to de-liver messages. There is a problem with zone-of-relevance approach isthat it may be difficult to discern the location of vehicles that are inter-ested in a message. So, for more generic delivery protocol, a locationservice or equivalent mechanism is needed for vehicles to obtain loca-tion data used for routing decisions.However, location-based routing, in and of itself, does not address the

frequent fragmentation of the network. For this, IVC routingwill need toutilize othermeans, such as epidemic routing protocols and hybrid com-munication strategies. Epidemic routing protocols require the prioriti-zation of messages in the transmission queue; this prioritization shouldreflect the time- and distance-varying importance of the IVC messages[25], [26]. The reliable transmission ofmessages to distant vehiclesmayalso require out-of-band means; for example, via cellular network.Specific adaptations of location-based routing for IVCs propose the

routing of packets along the road network [27]. Due to the constraintson vehicle movement imposed by the roadway, greedy location-basedforwarding algorithms may result in suboptimal routes.

D. Security Implications

Security mechanisms developed for otherMANETs have limited ap-plicability for the IVC network. The need for additional bandwidth, re-liance of nodal overhearing, and redundancy requirements render themlargely unsuitable.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 5, NO. 4, DECEMBER 2004 351

Wireless media is particularly susceptible to denial-of-serviceattacks, including resource exhaustion and jamming. The protocolsshould be developed so that deliberate resource-exhaustion attackscan be detected easily. The mitigation of jamming threats withspread-spectrum techniques heightens scalability issues due to itsincreased bandwidth requirements.

Current MANET intrusion-detection systems will not work if direc-tionalized antennas are used. The intrusion-detection techniques relyon eavesdropping on both upstream and downstream messages. Usingdirectionalized antennas will prevent the nodal overhearing of down-stream messages. One approach to utilize these systems would be todeploy a network of fixed receivers on the roadside. However, this in-volves overcoming the barrier of significant infrastructure investment.

Secure message-transport techniques require the utilization of mul-tiple routes. This is problematic due to the limited temporal availabilityof routes.Moreover, in addition to limiting the ability to employ spread-spectrum techniques, limited bandwidth also limits the availability ofredundant paths for security purposes.

This limited bandwidth also restricts the frequent use of crypto-graphic techniques, including digital signatures and the distributionof public key certificates and certificate revocation lists, which in-crease message size. Increasing the size of periodic messages in otherMANETs is a more readily acceptable technique, since routes andassociations between nodes are more stable. However, in the IVCnetwork, where routes and nodal associations are short lived, thistradeoff of bandwidth for security may not be satisfactory.

V. CONCLUSION AND FUTURE WORK

In conclusion, the IVC network exhibits very different characteris-tics from otherMANETs. Specifically, the constraints on vehiclemove-ments, varying driver behavior, and high mobility cause rapid topologychanges, frequent fragmentation of the network, a small effective net-work diameter, and limited utility from network redundancy. Thesechanges have implications for the IVC architecture at the physical, link,network, and application layers. At these layers, adjustments must bemade to effectively use the limited bandwidth and efficiently functionin the rapidly changing network.

Future analysis, which the authors intend to perform, will examinethe IVC network under a variety of traffic and roadway situations. Fur-thermore, the authors intend to tightly couple CORSIM and NS2 to-gether to allow the content of IVC messages to alter driver behavior.The ultimate goal will be to use this analysis to design effective andsecure protocols for the IVC network.

ACKNOWLEDGMENT

The authors would like to thank the students and faculty membersat the University of California, Berkeley, for making available theNS simulator and the students and faculty members of the MonarchProject, Carnegie Mellon University, Pittsburgh, PA, for their adhoc network extensions to NS. The authors would also like to thankG.McHale of the Federal Highway Administration for his assistance inusing the CORSIM simulator. Finally, they would like to acknowledgethe assistance of the Partners for Advanced Transit and Highways(PATH) program at the University of California for making availablethe traffic-flow data used in this paper.

REFERENCES

[1] S. Xu and T. Saadawi, “Does the IEEE 802.11 MAC protocol work wellin multihop wireless ad hoc networks?,” IEEE Commun. Mag., vol. 39,pp. 130–137, Mar. 2001.

[2] D. D. Perkins, H. D. Hughes, and C. B. Owen, “Factors affecting theperformance of ad hoc networks,” presented at the IEEE Int. Conf. Com-munications, New York, 2002.

[3] E.M. Royer and C.-K. Toh, “A review of current routing protocols for adhoc mobile wireless networks,” IEEE Pers. Commun., vol. 6, pp. 46–55,Apr. 1999.

[4] M. Mauve, J. Widmer, and H. Hartenstein, “A survey on position-basedrouting in mobile ad hoc networks,” IEEE Network, vol. 15, pp. 30–39,Jan./Feb. 2001.

[5] Y.-B. Ko and N. H. Vaidya, “GeoTORA: A protocol for geocasting inmobile ad hoc networks,” presented at the International Conf. NetworkProtocols, Osaka, Japan, Nov. 2000.

[6] S. R. Das, R. Castañeda, and J. Yan, “Simulation-based performanceevaluation of routing protocols for mobile ad hoc networks,” MobileNetworks Applicat., vol. 5, pp. 179–189, 2000.

[7] J. Tian, J. Hähner, C. Becker, I. Stepanov, and K. Rothermel, “Graph-based mobility model for mobile ad hoc network simulation,” presentedat the 35th Annual Simulation Symp., San Diego, CA, Apr. 2002.

[8] P. Johansson, T. Larsson, N. Hedman, B. Mielczarek, and M.Degermark, “Scenario-based performance analysis for routing protocolsfor mobile ad-hoc networks,” presented at the Annu. Int. Conf. MobileComputing and Networking, Seattle, WA, Aug. 1999.

[9] W. Su, S.-J. Lee, and M. Gerla, “Mobility prediction and routing in adhocwireless networks,” Int. J. Network Manag., vol. 11, pp. 3–30, 2001.

[10] A. Vahdat and D. Becker, “Epidemic routing for partially-connected adhoc networks,” Tech. Rep. CS-200 006, Duke Univ., Durham, NC, Apr.2000.

[11] P. Papadimitratos and Z. J. Haas, “Secure routing for mobile ad hoc net-works,” presented at the SCS Communication Networks and DistributedSystems Modeling and Simulation Conf., San Antonio, TX, Jan. 2002.

[12] Y.-C. Hu, A. Perrig, and D. B. Johnson, “Ariadne: A secure on-demandrouting protocol for ad hoc networks,” presented at the Working SessionSecurity ad hoc Networks, Lausanne, Switzerland, 2002.

[13] Y. Zhang andW. Lee, “Intrusion detection in wireless ad-hoc networks,”presented at the Annu. Int. Conf. Mobile Computing and Networking,Boston, MA, Aug. 2000.

[14] S. Marti, T. J. Giuli, K. Lai, and M. Baker, “Mitigating routing misbe-havior in mobile ad hoc networks,” presented at the Annu. Int. Conf.Mobile Computing and Networking, Boston, MA, Aug. 2000.

[15] L. E. Owen, Y. Zhang, L. Rao, and G. McHale, “Traffic flow simula-tion using CORSIM,” presented at the 2000 Winter Simulation Conf.,Orlando, FL, Dec. 2000.

[16] J. Broch, D. A. Maltz, D. B. Johnson, Y.-C. Hu, and J. Jetcheva, “A per-formance comparison of multi-hop wireless ad hoc network routing pro-tocols,” presented at the 4th Annu. ACM/IEEE Int. Conf. Mobile Com-puting and Networking, Dallas, TX, 1998.

[17] K. Petty, FSP 1.1: The Analysis Software for the FSP Project.Berkeley: Univ. California Press, 1994.

[18] K. A. Redmill, M. P. Fitz, S. Nakabayashi, T. Ohyama, F. Ozguner, U.Ozguner, O. Takeshita, K. Tokuda, and W. Zhu, “An incident warningsystem with dual frequency communications capability,” presented atthe IEEE Intelligent Vehicles Symp., Columbus, OH, June 2003.

[19] A. Ebner, H. Rohling, L. Wischoff, R. Halfmann, and M. Lott, “Perfor-mance of UTRA TDD ad hoc and IEEE 802.11b in vehicular environ-ments,” presented at the 57th IEEE Vehicular Technology Conf., Jeju,South Korea, Apr. 2003.

[20] J. Zhu and S. Roy, “MAC for dedicated short range communications inintelligent transport system,” IEEE Commun. Mag., vol. 41, pp. 60–67,Jan. 2003.

[21] F. Borgonovo, A. Capone, M. Cesana, and L. Fratta, “ADHOC: A new,flexible and reliable MAC architecture for ad-hoc networks,” presentedat the Wireless Communications and Networking Conf., Mar. 2003.

[22] S. V. Bana and P. Varaiya, “Space division multiple access (SDMA) forrobust ad hoc vehicle communication networks,” presented at the IEEEInt. Conf. Intelligent Transportation Systems, Oakland, CA, Aug. 2001.

[23] S. Katragadda, G. Murthy, R. Rao, M. Kumar, and R. Sachin, “A decen-tralized location-based channel access protocol for inter-vehicle com-munication,” presented at the 57th IEEE Vehicular Technology Conf.,Jeju, South Korea, Apr. 2003.

[24] L. Briesemeister, L. Schafers, and G. Hommel, “Disseminating mes-sages among highly mobile hosts based on inter-vehicle communica-tion,” presented at the IEEE Intelligent Vehicles Symp., Dearborn, MI,Oct. 2000.

[25] B. Xu, A. Ouksel, and O. Wolfson, “Opportunistic resource exchange ininter-vehicle ad-hoc networks,” presented at the IEEE Int. Conf. MobileData Management, Berkeley, CA, Jan. 2004.

[26] L. Wischhof, A. Ebner, H. Rohling, M. Lott, and R. Halfmann, “Adap-tive broadcast for travel and traffic information distribution based oninter-vehicle communication,” presented at the IEEE Intelligent Vehi-cles Symp., Columbus, OH, June 2003.

[27] J. Tian, L. Han, K. Rothermel, and C. Cseh, “Spatially aware packetrouting for mobile ad hoc inter-vehicle radio networks,” presented at theIntelligent Transportation Systems Conf., Shanghai, China, Oct. 2003.