ROUTING PROTOCOL PERFORMANCE OVER INTERMITTENT LINKS

Diane Kiwior and Lucas LamThe MITRE Corporation

Bedford, MA

ABSTRACT1

Communications among mobile, tactical nodes presentsa major military challenge. The use ofMANET (MobileAd Hoc Network) protocols provides a possible solutionfor military nodes, including those in an airbornenetwork. However MANET research has primarilyfocused on ground-based studies, using vehicular speedsand in many cases random mobility patterns. Nodes ofan airborne network travel at speeds significantly fasterthan ground vehicles, and fly in coordinated paths notmodeled by random mobility. In addition, the quality ofthe radio links for airborne nodes varies with time, dueto interference, range, or antenna occlusion whenbanking. These characteristics make it impossible toextrapolate existing MANET research results to theairborne network. In this paper we present a simulationevaluation of MANET protocol performance for anairborne environment, with the intent to identify arouting protocol that can best deal with the dynamics ofan airborne network.

A scenario involving widebody aircraft trajectories wasmodeled in OPNET. Intermittent link outages due toaircraft banking were modeled by use of a notionalradio link, antenna model, and modified OPNET sourcecode that reflects positional antenna gain, includingantenna occlusion when an aircraft banks. Within thisscenario environment, four MANET protocols (AODV,TORA, OLSR, OSPFv3-MANET) were run on theairborne nodes with metric collection of protocoloverhead, packet delivery ratio, and packet delay.Simulation results and analysis of the protocolperformance for an airborne network are presentedhere. Additional issues andfuture areas ofresearch arealso identified.

1. INTRODUCTION

1 This technical data was produced for the U.S. Government underContract No. FA8721-07-C-0001, and is subject to the Rights inTechnical Data-Noncommercial Items Clause at DFARS 252.227-7013 (NOV 1995). C 2007 The MITRE Corporation. All RightsReserved. Approved for Public Release; Distribution Unlimited.Public Release Case Number 07-0778.

This paper presents an evaluation of MANET protocolperformance for an Airborne Network. There have beennumerous studies evaluating the performance ofMANET protocols, but for the most part the mobilitymodels of these studies consist of random waypointmobility at ground-based vehicular speeds, no more than20 m/sec with focus on the scalability of MANETnetworks, up to 1000s of nodes. Characteristics of anairborne environment are very different. Aircraft speedis significantly faster than ground vehicles; militaryaircraft fly in coordinated paths not modeled by randommobility and the number of nodes in an AirborneNetwork at one time will be much less than 1000.Airborne radio link quality is time-varying due tointerference, range, jamming, or antenna occlusionduring banking. This simulation study focuses onmodeling these characteristics in a realistic airbornescenario in which MANET protocol performance can beevaluated. In addition to incorporating realistic speedsand flight paths of widebody military aircraft, thephysical link performance includes an antenna modelthat accounts for antenna occlusion during aircraftbanking.

Routing protocols require connectivity among nodes.For wirelined networks, this connectivity is stable withoccasional disruptions, but for airborne networks,disruptions are the norm. Connectivity is interrupteddue to inter-aircraft distances beyond radio range andoutages from multiple causes as noted above. This studyexplores the performance of MANET protocols in thepresence of connectivity lapses that would beexperienced in a realistic scenario. One specific scenariois used to gain insight into the issues facing an airbornenetwork as well as to characterize a baseline MANETperformance as a point of comparison for future studies.This does not imply that the scenario used in this studyrepresents the only realistic airborne network scenario.Future work will require modeling of additional realisticscenarios with a goal of development of generalized linkmodels for airborne network studies.

It is important for simulation studies to recognize issuesrelated to the validity of Modeling & Simulation studiesfor MANET protocols and these concerns are discussed

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in Section 2. Section 3 presents specifics of the OPNETMANET protocol models and Section 4 describes indetail the simulation scenario used in these studies.Simulation results are presented in Section 5. Finally,conclusions and areas of future research are presented inSection 6.

2. MANET SIMULATIONS

Journals and conferences have been filled withperformance evaluations of MANET protocols, but nosingle protocol has emerged as the optimal solution forall cases. For practical reasons, many of the evaluationshave been done via simulation rather than experimentsand recently, questions have been raised about thecredibility of simulations used to evaluate MANETprotocol behavior. Reference [1] reviewed 114published MANET simulation papers and identifiedissues leading to lack of reliability in MANETsimulation-based studies. The shortfalls included lack ofdetail to support repeatability, lack of model validationand verification, and lack of recognition of initializationbias. The lack of reality in mobility models and the needfor simulation validation is pointed out in [2] while [3]compares the inaccuracies of simulations to actualexperiment results. This study seeks to address theissues reflected in these papers by incorporating areality-based scenario that includes a physical layermodel that has been measured against live exercises inan attempt to bridge the gap between simulations andreality.

Legacy MANET simulations have focused on general-purpose evaluation of protocol performance across acontinuum of scenarios, based on the premise cited in[1], i.e. that protocol performance results should not bespecific to the scenario used in the experiment. Whilethis approach provides a general-purpose evaluation ofMANET performance across a continuum of scenarios,these scenarios lack realism and have not led todevelopment of a ubiquitous solution for MANETnetworking. [4] and [5] argue that successful MANETsolutions can be found when they are designed tosupport a set of specific applications in a specializednetwork. It is our goal to characterize a specializedAirborne Network with realistic scenarios and to identifya working solution that may not address all possibleconcerns but could provide communication functionalitythat is currently unavailable. To manage the study, theproblem space is limited to a realistic number of nodeswith mobility and connectivity modeled as accurately aspossible

A network consisting of military widebody aircraft isconsidered in this study. The widely used randomwaypoint mobility models of published MANET studiesdefine movement of a node in terms of moving betweenrandomly chosen points, with user-defined pausesbetween movements. In contrast, military aircraft oftenfly well-defined orbits that can support fairly consistentRF connectivity within radio range. Neighbor changerate will be minimal but banking and the resultingantenna occlusion can cause perturbations of the routingpath. Link outages are not as frequent as might occurin random waypoint studies, but can be long-term (orderof minutes) due to lack of radio range or short-term(order of seconds) due to banking. With only one radiolink and a sparse number of nodes, there are noopportunities to re-route when out of radio range.Differences among MANET protocol performance inthese conditions are identified.

3. MANET MODELS IN OPNET

Identification of Standard MANET protocols has beenpursued by the IETF, in particular the IETF Mobile Ad-hoc NETwork (MANET) Working Group [6], since1996. This Working Group has been chartered todevelop two standards track routing protocolspecifications, one for a Reactive MANET Protocol andone for a Proactive MANET protocol. Reactiveprotocols discover routing paths only when trafficdemands it, and as a result, when there are routechanges, trade off longer packet delays in the interest oflower protocol overhead. Proactive protocols maintainand regularly update full sets of routing information,with a tradeoff of greater protocol overhead in theinterest of smaller packet delays.

Despite years of research, no Internet Standards forMANET protocols have yet been specified. However,since 2003, several Experimental RFCs have beenidentified. Experimental status indicates that there areunanswered questions in implementing or deploying theprotocol but identifies them as a technology forexperimenting that might develop into standards-trackprotocol. Specifications for two of the MANETprotocols in this study, Ad-hoc On-Demand DistanceVector (AODV)[7], and Optimized Link State RoutingProtocol (OLSR)[8], have been released as ExperimentalRFCs.

The OPNET [9] v 12.0 simulation tool is used for thisstudy. Multiple MANET protocols have beenimplemented in OPNET and previous work detailed in[10] has validated an OPNET antenna model that reflectsaircraft banking effects. The protocols under study in

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the M&S effort include the reactive protocols, AODV,and Temporally Ordered Routing Algorithm(TORA)[11] and the proactive protocols, OLSR andOSPFv3 with MANET extensions [12].

Each protocol has specific mechanisms to providerouting, including neighbor discovery, route discovery,and route maintenance which includes response toroute/link failures as well as route/link restorations.These mechanisms need to be efficient in terms of timeto minimize packet delay, as well as efficient in terms ofbandwidth usage, to maximize available RF resourcesfor data. Summaries of each protocol's mechanisms, asimplemented in OPNET, follow.

Reactive (On-Demand)ProtocolsThe reactive protocols discover routes only when trafficneeds to be routed and do not identify routes within theentire network. In general reactive protocols may havelarger end-to-end delays but require less overhead sincethey do not require network-wide information.

AODVAODV is implemented in OPNET according to theExperimental RFC 3561. [7]Neighbor/Route Discovery: AODV does not focus onlearning about all reachable neighbors, but only thoseneighbors that are useful in order to transmit the data.When data needs to be transmitted to a new destination,a Route Request (RREQ) is broadcast within a specifiedarea, initially set at 1 hop. With each failed RouteRequest, the broadcast area is increased. When theRREQ reaches a node that has information to therequired destination, it responds with a Route Replymessage. When a route fails, a Route Error is sent fromthe node that has noted the failed link and a new RREQis initiated.Route Maintenance: Active routes in AODV aremaintained via periodic Hello messages; the OPNETimplementation uses Hello messages at a defaultfrequency of 1 sec, as defined in RFC 3561. If a Hellofrom an active node is not received within 2 seconds, theroute is considered unreachable, a Route Error messageis broadcast to all nodes, and another series of RouteRequests are broadcast. Although only active routes canbe used to forward data packets, the route table can alsostore invalid routes (previously valid route information)for an extended period of time. These invalid routes canprovide information for route repairs and for futureRREQ messages and could expedite route repairs. Thelifetime of invalid routes is bounded by a 15 secondtimer, after which a route that is marked invalid isdeleted.

TORATORA can operate in either On-Demand or Proactivemode. The default OPNET setting and the one used inthis study, is On-Demand mode. TORA[11] specifiesthe routing mechanism and uses the Internet MANETEncapsulation Protocol (IMEP) [13] for monitoring linkstatus. As with AODV, TORA routers do not maintainroutes to every node in the network.Neighbor/Route Discovery IMEP handles neighbordiscovery through Beacons, with responding Echo orACK packets confirming bidirectional connectivity.IMEP also supports Multipoint Relays but these are notimplemented in OPNET. TORA broadcasts a Querymessage when traffic needs to be transmitted and there isno known route to the destination. Update packets arereturned to the source by an intermediate node with aroute to the destination.Route Maintenance TORA can provide multiple routesto a destination and minimizes protocol overhead bylocalizing reaction to topological changes when possible.Changes in link status are determined by periodic IMEPBeacon/Echo/ACK packets used for neighbor discovery.A Beacon message without a replying Echo or ACKidentifies a route failure and triggers another round ofQuery messages. Although TORA/IMEP incorporatesperiodic link status Beacon packets, the default timers inOPNET are large and the frequency does not impact theoverhead.

ProactiveProtocolsProactive protocols are designed to maintain knowledgeof routes to all nodes in a MANET. In general, thisresults in higher overhead but lower end-to-end delay.

OLSROLSR is implemented according to Experimental RFC3626. [8]Neighbor/Route Discovery: Periodic UELLO messagesare used to establish neighbor links and to distributeMultiPoint Relays (MPRs), determined by algorithm.Route Maintenance: Hello messages track linkconnectivity. Topology Control (TC) messages,distributed by MPRs, propagate link state informationthroughout the network, and are broadcast periodicallyas well as when there is a change to the topology.Control traffic consists of periodic hellos and TCmessages. Overhead is controlled by MPR broadcastand redistribution of TC messages throughout thenetwork, rather than broadcasts of link state from eachrouter.

OSPFv3-MANET.OPNET implements a December 2005 Internet draftversion of OSPFv3 with MANET extensions [12].

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Neighbor/Route Discovery: Hello messages are usedfor neighbor discovery. MANET Designated Routers(MDRs) are chosen based on 2-hop neighborinformation learned from Hellos and are distributed insubsequent Hello messages.

Route Maintenance: As in OLSR, Hello messages

track link connectivity. If a Hello has not been receivedwithin 6 seconds, the link is declared down and a new

Link State Advertisement is distributed. DatabaseDescription and Link State Advertisements (LSAs) are

distributed by MDRs to share the network's completepicture. OSPFv3-MANET uses MANET DesignatedRouters (MDRs) to control overhead, similar to OLSR'suse of MPRs. A range of overhead control is availablein the choice of LSAFullness parameter. LSA floodingcan range from minimal flooding by MDRs only, to fullLSA flooding by all routers, similar to that of theOSPFv2 protocol. The default setting of LSAFullness,which is implemented in OPNET, calls for full LSAflooding from MDRs and minimal LSAs from otherrouters.

Table 3.1 lists the pertinent MANET timers, as

implemented in OPNET, that can affect performanceresults. A protocol's ability to recognize link outages or

link restorations is controlled by these timers and theireffects can be seen in Packet Delivery Ratio metric.TORA/IMEP's beacon timer is the largest timer andindicates that this protocol will not be able to recognizelink outages as quickly as the other protocols. AODV'sshort timer should provide the fastest reaction to linkoutages.

Table 3.1: OPNET MANET Protocol Timer Settings(sec)

as needed

Protocol overhead is determined largely by the periodicmessages. Table 3.2 lists each protocol's controlmessages and their sizes. It is clear thatOSPFv3MANET control messages will consume more

bandwidth than the control messages of the otherprotocols.

Table 3.2 MANET Overhead Messages

4. SIMULATION SETUP

As noted previously, it is important to realistically modelair mobility characteristics, including distances betweennodes resulting from aircraft speeds and intermittentoutages. This study models radio range effects andoutages resulting from antenna occlusion while banking.

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MANET protocol

Route Requests (24 bytes),Route Replies (20 bytes),Route Errors (20 bytes).

AODV Periodic MessagesHello messages (4-6 bytes)broadcast by nodes on anactive route to confirmcontinued connectivity.Query (8 bytes),Update (36 bytes) messageswhen traffic is to be sent.Periodic MessagesIMEP Beacon message (3

TORA/IMEP bytes)IMEP Responding Echo (4bytes + 4 bytes per address)orACK (4 bytes + 4 bytes perACK)Periodic MessagesHello (8 bytes + 4 bytes for

OLSR each neighbor interface)Topology Control (4 bytes +4 bytes per advertisedneighbor)Periodic MessagesHello (36 bytes + 4 bytes

OSPFv3 MANET per neighbor)Router-LSAs (20 bytes + 40bytes per neighbor)

MANET Route/Neighbor Identificationprotocol Discovery Change

Route Request

AODV Route Reply No Hello withinHello for active 2 secnodes (1 sec)Query MessageUpdate Message No IMEP

TORA/IMEP IMEP Beacon (20 Beacon withinsec) and 60 sec

responding EchoHello (2 sec) No Hello within

OLSR Topology Control 6 seconds(5 sec)

OSPFv3 Hello (2 sec) No hello withinMANET LSA Distribution 6 seconds

The scenario used for this study consists of a

representative laydown of 5 widebody aircraft and a

land-based Tactical Operations Center (TOC), applied tothe Caspian Sea Scenario over an area of 750 n mi x 350n mi. Each aircraft's flight path is specified by a centerpoint and a rounded rectangle about this center point.The specifics of the rounded rectangle flight path includelength, width, and radius of the circle used at thecorners. In addition, the aircraft movement is defined bythe speed, direction and the rotation of the patternaround the centerpoint of the node. In all simulations,each aircraft flew in a counter-clockwise direction at a

speed of 400 knots at altitudes of approximately 20,000ft. The rounded rectangle flight paths were 20 n mi wideand 110-145 n mi in length with banking angle set at 30degrees for each aircraft. The position in which eachaircraft begins its trajectory is determined by a randomseed value applied to the simulation. Thirty randomseed values were chosen. The random seeds determinedistances between aircraft and possibilities forconnectivity.

Each aircraft was represented by a typical widebodywith a tactical common data link (TCDL) antennaattached. In order to accurately model the bankingeffects, an OPNET model of a TCDL radio link withbehavior that reflects antenna occlusion during bankingthat had been previously been validated [10] against liveexercises was used. The OPNET model includesmodifications to the OPNET 802.11 MAC layer todisable RTS/CTS. The OPNET TCDL antenna gainpipeline stages were also modified to include aircraftattitude data in calculations of the antenna pointingdirection and the resulting antenna gain. The radiopower was set to 200 watts power and the data rate at 10

Mbps, as noted for the TCDL link in JEFX02 exercises[14]. Point to point links are set up between each node.

A variety of simulation cases with various numbers ofnodes were used within this scenario, ranging from 2nodes to all 6. The scenario cases are listed in Table 4.1.

Table 4.1: Simulated Cases

Traffic from source to destination in all cases was set to1 KB UDP packets with 10 packets sent per second for a

net bandwidth usage of 80 kbps. The goal was toprovide a constant stream of traffic that would notgenerate congestion effects in this study but wouldrequire routing throughout the simulation. To ensure thatinitialization of the protocols had been completed, trafficwas not started until 200 seconds into the simulation,and metric collection began at that point. Eachsimulation was run for a total of 5400 seconds, whichcorresponds to 2 flight path rotations for each trajectory.

Metrics collected to evaluate MANET performanceinclude:* Packet Delivery Ratio (PDR): The ratio of the

number of data packets received to the number ofdata packets transmitted;

* End-to-End Delay: The time needed to deliver a

packet from the data source to the data destination;* Routing Overhead: The total amount of routing

protocol traffic transmitted during the simulation.Averages for each metric were calculated over the last5200 seconds of each simulation run, allowing the first200 seconds time for the protocols to initialize andstabilize.

5. SIMULATION RESULTS

The varying starting points result in different distancesbetween nodes (and different amounts of time for radiorange) as well as different times for banking (andpotential link outages) for each run. MANET protocolperformance results are presented in the simulationstatistics in Figures 5.1-5.3. The figure for each metricdisplays the average value as a symbol identified in thelegend, and the range of the average value, which variedwith seed value, is represented by the extended linesfrom the symbols.

Figure 5.1 displays the average Packet Delivery Ratio(PDR), i.e. the ratio of packets received to packets sent.As can be seen, when there are few nodes and limitedconnectivity, as in the 2A, 2B, and 3 node scenarios, thespecific protocol has little effect and PDR isunacceptable, no more than 40%. This emphasizes thelack of connectivity between these nodes, irrespective ofthe starting position. TORA's PDR is the smallest,reflecting the effects of the slow timers that identify linkoutages.

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Case Scenario Nodes TrafficSrc Dest

2A ACI, TOC ACI TOC2B ACI, AC4 ACI AC43 ACI, TOC, ACI AC4

C4__

6 All (AC1, AC2, ACI AC4AC3, AC4,AC5, TOC)

Packet Delivery Ratio (PDR)

OSPF\3-M *OLSR ,AODV E TORA

100

90

80

70

60

50

40 -ITV -T

30 AT TT120 111 1110 --

2A 2B

30.00

25.00

20.00U,

>, 15.00a)

10.00

5.00

0.003

Scenario Case

Figure 5.1 MANET Protocol Performance:Packet Delivery Ratio

End-to-End Delay

* OSPFv3-M * OLSR AAODV * TORA

1Ep i0 * i ,- i *z a 9i i

2A 2B 3 6Scenario Case

Figure 5.2 MANET Protocol Performance:End-to-End Delay

Case 2A, one mobile node transmitting to a fixed node,has a minimal range of PDR. No matter where themobile node starts on the trajectory, there is a minimalcontiguous period of connectivity due to range betweenthe source and destination, with no advantage for any ofthe MANET protocols. There is connectivity only about30% of the time.

Cases 2B and 3, involving a mobile source node and a

mobile destination node, show the effects of minimallyconnected locations of the mobile nodes. The amount oftime when both nodes are within radio range depends on

the scenario seed, and can be seen by the variation ofPDR. The least optimal starting positions result in only8-13% PDR depending on the protocol. The differencebetween the MANET protocols' performance in PDR isnot statistically significant in these cases whereconnectivity is minimal.

The advantage of greater node density is apparent in the6 node case, with an average PDR, in the 85-92% rangefor all protocols. Some seed values set aircraft positionsin which the performance is significantly worse at 65-790o PDR. OSPFv3-MANET, OLSR and AODV havecomparable performance but TORA's PDR is the lowest,reflecting the 20 second Beacon Messages which limitits agility in reacting to changing link conditions.Although it would be reasonable to expect that thereactive AODV protocol would have a lower PDR,AODV's storage of invalid routes for 15 seconds to beused for repairs of Route Errors allows its performanceto match the proactive results.

Figure 5.2 displays the average end-to-end delay foreach of the MANET protocols in the different scenariocases. In general, as the number of nodes in the scenarioincreases, the delay increases, but the proactiveprotocols, OSPFv3-MANET and OLSR, show the leastincrease in latency with number of nodes. The proactiveprotocols also show the least variation among thevarious seed values due to their maintenance of networkrouting. These protocols would be useful for time-sensitive applications.

As expected, the reactive protocols result in longer end-to-end delays reflecting the delay in finding a route tothe destination, when the traffic demands it. In addition,the range of delay depending on the scenario startingpositions is highly variable for AODV and TORA.

Protocol Overhead*OSPF\3-M * OLSR AAODV * TORA

1800

1600

1400

U 1200

1000

° 800

> 6000

400

200

n X_

o *

2A 2B 3Scenario Case

D:

6

Figure 5.3 MANET Protocol Performance:Routing Overhead Traffic

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0a-

u

The routing protocol overhead shown in Figure 5.3shows a sharp increase in overhead traffic as the numberof nodes increase for all protocols. The proactiveprotocols, OSPFv3-MANET and OLSR, have minimalvariation in protocol overhead for the 2A, 2B and 3scenarios. Their overhead, which consists of periodicHello messages that track link connectivity and link statemessages that maintain routing, shows more variation inScenario 6, as both protocols react to the varyingconnectivity among the six nodes. Despite the samefrequency of Hello messages in both proactive protocols,OLSR overhead is less than that of OSPFv3-MANETdue to the larger packet sizes for OSPFv3-MANET'sHello and Link State Advertisement packets.

Of all the protocols, TORA requires the least overheadreflecting the 20 second timers for Beacon messages ascompared to the 1 and 2 second Hello messages for theother protocols tested.

Overall, OSPFv3-MANET and OLSR provided the bestperformance results, with high PDR and consistent lowend-to-end delays. In terms of protocol overhead, OLSRshows some advantage but further study is needed toevaluate the tradeoffs of faster link outage recognitionversus increased overhead resulting from proactiveprotocols' shorter timer settings. In addition, OSPFv3-MANET and OLSR need to be studied in extendedscenarios that include additional radio links on eachnode and more extensive traffic. Additional traffic flowsamong nodes can incapacitate MANET protocolperformance, as presented in [15]. The addition of aBeyond Line Of Sight (BLOS) link in addition to a LineOf Sight (LOS) link may provide increased connectivityfor airborne nodes, but protocol performance may benegatively affected by the characteristically longerlatencies ofBLOS links.

6. CONCLUSIONS AND FUTURE PLANS

These results provide a baseline performance evaluationof MANET protocols for a widebody aircraft scenariowith a single minimal traffic source and limited stressesof aeronautic dynamics. The proactive protocols providemore consistent performance in terms of delay, whichmakes them more appropriate for real time applications.In addition, the overhead costs of proactive protocolsmay be reduced by optimizing timer settings. It remainsto be seen if these protocols provide an advantage whenthe scenario becomes more complex with additionalradio link(s), traffic and nodes. This will be the focus ofour future work.

Future work will need to examine performance when aBLOS link for the aircraft is added. It is clear thatcomplete connectivity for an airborne network willrequire this for coverage and it is important tounderstand the impact of a longer-latency link onrouting. It remains an area of future study to identifyMANET protocol performance in the presence of LOSand BLOS links. It will be necessary to study whichprotocol can switch to an alternate link most efficientlyand to identify parameters that govern the switchover.

Efforts to ensure the model and scenario are realisticallyportrayed will continue. As additional live flight databecomes available, calibration of models against actualresults will improve the realism of the models for futuresimulations. More extensive simulations involving atleast dozens of aircraft are needed to understand thescalability of the MANET protocols in an Airborneenvironment. Performance metrics obtained from aminimal scenario do not expose potential issues to befaced in a larger scenario.

ACKNOWLEDGMENTSThe authors would like to thank Lucien Teig andDavid Choi of MITRE's Applied ElectromagneticSystem Department for their work in developing theTCDL antenna pattern and MIT Lincoln Lab'sSteve McGarry, who shared details of a widebodyaircraft laydown in the Caspian Sea Scenario withthe Airborne Network Special Interest Group.

7. REFERENCES

[1] S. Kurkowski, T. Camp, and M. Colagrosso,"MANET Simulation Studies: The Incredibles," ACMSIGMOBILE Mobile Computing and CommunicationReview, Vol. 9, Issue 4, October 2005.[2] T. Andel and A. Yasinsac, "On the Credibility ofManet Simulations", Computer, Vol. 39, Issue 7, July2006.[3] J. Liu, Y. Yuan, D. Nicol, et al, "SimulationValidation Using Direct Execution of Wireless Ad-Hoc Routing Protocols". 18th Workshop on Paralleland Distributed Simulation (PADS'04), 2004.[4] M. Conti and S. Giordana, "Multihop Ad HocNetworking: The Reality," IEEE CommunicationsMagazine, April 2007.[5] C. Tschudin, P. Gunningberg, H. Lundgren, and E.Nordstrom, "Lessons from Experimental MANETResearch," Elsevier Ad Hoc Networks Journal, Vol. 3,Issue 3, March 2005.

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[6] IETF Mobile Ad-hoc Networks website.

[7] C. Perkins, S. Das, " Ad hoc On-Demand DistanceVector (AODV) Routing", IETF RFC 3561, July 2003.[8] T. Clausen, P. Jacquet, "Optimized Link StateRouting Protocol", IETF RFC 3626, October 2003.[9] OPNET. Site: http://www.opnet.com[10] R. Preston, J. Doane, and D. Kiwior, "ModelingAntenna Blockage in Airborne Networks",OPNETWORK 2005.[11] V. Park and M.S. Corson, "Temporally-OrderedRouting Algorithm (TORA) Version 1 FunctionalSpecification", draft-ietf-manet-tora-spec-04.txt, July2001.[12] R Ogier, P. Spagnolo, "MANET Extension ofOSPF using CDS Flooding, draft-ogier-manet-ospf-extension-06.txt, December 2005.[13] M. S. Corson, V. Park, "An Internet MANETEncapsulation Protocol (IMEP) Specification", draft-ietf-manet-imep-spec-00.txt, November 1997.[14] J. Cooley, 0. Huang, L. Veytser, and S. McGarry,"Mobile Airborne Networking Experience with PaulRevere," MILCOM 2005.[15] J. Broch, D. Maltz, D. B. Johnson, Y. Hu, and J.Jetcheva, "A Performance Comparison of Multi-HopWireless Ad Hoc Network Routing Protocols," In Proc.of Fourth Annual ACM/IEEE Intl Conference on MobileComputing and Networking (Mobicom '98), October1998.

Approved for Public Release; Distribution Unlimited.Case Number: 07-0778.C)2007 The MITRE Corporation. All rights reserved.

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