ADAPTIVE FORWARDING RATE CONTROL FOR NETWORK CODING IN TACTICAL MANETS

Soon Y. OhUtopiaCompression

11150 Olympic Blvd. Suite 820Los Angeles, CA 90064

soon@utopiacompression.com

Eun-Kyu Lee, and Mario GerlaComputer Science Department

University of California, Los AngelesLos Angeles, CA 90095

{eklee, gerla}@cs.ucla.edu

Abstract—In this paper, we propose a novel packet forwardingscheme based on network coding that is resilient to jammingattack in a tactical area. Wireless communication is necessaryin a battlefield, but it is fragile to jamming attacks from anadversary because of the wireless shared medium. Jammingattack is easily achieved by emitting continuous radio signalsand it can interfere with other radio communications. Channelswitching over multiple channels or route detouring have beenproposed to restore communication from jamming attacks, butthey require a special radio system or knowledge of the networktopology. Our new scheme exploits packet redundancy of networkcoding. It dynamically changes the level of redundancy adaptingto local jamming conditions and thus injects redundant encodedpackets when and where a jamming attack occurs. In absenceof jamming, it decreases forwarding rate to save resources sothat our protocol efficiently manages the network resources. Weprovide performance evaluations of resiliency and efficiency ofthe new scheme via simulation study.

I. INTRODUCTION

Wireless mobile ad hoc networks (MANETs) are self-organizing wireless networks composed of a set of mobile par-ticipants without any infrastructure support. They are promis-ing solutions to today’s network centric warfare. However,radio communications in the tactical MANET face severalformidable security and reliability challenges due to the sharedmedium. One challenge is jamming.

A jamming attack is easily delivered by emitting continuoussignal or injecting dummy packets into the shared mediumcausing interference with existing communications or in somecases abusing the MAC layer of other nodes within a range.Consequently, jamming attacks can seriously impede wirelesscommunications. For example, it is known that severe disrup-tion can occur to all Wi-Fi traffic within 100 meter range ifa standard PDA with 802.11 [1] is turned on to transmit. Insuch a jamming situation, conventional links, networks, andtransport protocols fail to operate properly.

Previous jamming attack solutions exploit spatial or spec-trum diversity [2]–[8]. If nodes detect jamming, they switchthe communication channel [3], [4], [6]–[8] or send packetson a detour [2]. However, channel switching or detouringaround the jamming area requires a special radio system or theknowledge of the network topology, respectively. Moreover,these methods cannot handle multicast communications eventhough they are critical in a tactical field where nodes move asgroups and must communicate to accomplish their missions.Thus, spatial and spectrum diversity are, for different reasons,not practical solutions to protect from jamming attacks in thetactical MANET.

In this paper, we propose a novel MANET protocol that

protects existing uni and multicast communications from jam-ming. The new protocol exploits temporal diversity usingnetwork coding: each intermediate node dynamically adjuststhe encoding and forwarding rate based on local channelconditions. Say, if the channel conditions become worse dueto jamming, a node generates and forwards more packetsafter encoding; otherwise, it tries to reduce the number ofrelayed packets. The main contributions of this paper areas follows. First, we develop a novel and simple scheme,Adaptive Forwarding scheme for network coding that cancope with jamming attacks. Our scheme does not require aspecial radio system or the knowledge of a whole networktopology. Second, we produce the first protocol that protectsmulticast from jamming attacks. Third, the protocol enablesnodes to respond independently to jamming without requiringinformation exchanging or synchronization with other nodes.Next, the protocol provides localized protection in which onlynodes in the jammed area exercise dynamic and redundantforwarding so that resources in other areas can be saved.Lastly, extensive simulation-based experiments enable us toaccurately evaluate robustness and efficiency of performance.

The remainder of this paper is organized as follows:Section II introduces various jamming attack strategies inMANET; Section III describes the proposed Adaptive For-warding scheme in details; Section IV presents simulationresults; Section V illustrates related work, and the paper isconcluded in section VI.

II. JAMMING ATTACK MODELS

There are various jamming attack strategies. They interferewith other wireless communications by generating a contin-uous high power noise (or dummy regular messages) acrossthe entire spectrum in a given area. We call a node generatingsuch interference a “jammer” and proceed to classify jammingattack strategies based on jammer’s behavior. We introduce afew representative classes below.

• Continuous jamming: A jammer continually emits radiosignal once it starts jamming. The jammer sends outrandom bits or regular blank messages. It continues toemit radio signal as long as its battery permits eventhough there are no wireless communications to interferewith. Thus, power usage is not efficient even thoughthe effectiveness of the jamming attack (when victimsare present in the spectrum) is high. The jammer canbe easily detected by channel monitoring, making himan easy artillery target. The continuous jamming can be

The 2010 Military Communications Conference - Unclassified Program - Networking Protocols and Performance Track

978-1-4244-8180-4/10/$26.00 ©2010 IEEE 1381

turned into intermittent jamming (in a single channel) bysimply switching communication channels.

• Periodic jamming: Instead of continuously emitting jam-ming signal, a periodic jammer switches between sleepingand jamming mode periodically. It tries to fill one channelor multiple channels by round-robin method with randombits or regular packets. Further, it sends out signal toone area or multiple areas in round-robin mode as well.Periodic jamming is harder to detect than continuousjamming, but it can still be predicted and detected viachannel monitoring.

• Random jamming: Like the periodic jammer, a randomjammer alternates sleeping; but jamming intervals arerandom. The jammer may move around or (if it usesa directional antenna) it may change the direction ofan antenna to change the jammed area. Since randomjamming occurs at unexpected time points and lasts forunpredictable duration, it is more difficult to detect thanthe previous two methods. However, jamming effective-ness is degraded.

• Intelligent jamming: An intelligent jammer achieveshigh jamming effectiveness with very low energy re-quirements and low probability of detection by others.For example, it can specifically target interfering criticalcontrol messages, e.g., CTS or ACK packets in 802.11.If the sender (the victim) misses a CTS (or ACK), itkeeps retransmitting a RTS (or data) and finally, it givesup all packet transmissions. Thus, the intelligent jammercan easily accomplish its goal of session disruptionwithout being distinguished from normal interferers ina congested situation. However, intelligent jamming canonly be applied to particularly vulnerable protocols suchas 802.11 unicast.

We can expect jamming attacks at any time during ourdaily life. For example, the jammer can disrupt the wirelessnetwork of a business competitor. However, the most commonMANET jamming attacks occur in tactical scenarios. Tacticalarea jamming can have significant effects on combat outcome.The jammer wants to disrupt communications without beingdetected. Continuous jamming is not suitable. Intelligent jam-ming is not effective neither since it cannot handle multicast;it uses UDP and broadcast mode (no RTC, CTS, and ACK).Thus, random jamming with signal monitoring will be usedin this study as it is more difficult to detect than periodicjamming. In our simulation model, the jammer injects radiosignal for a random duration after a random time interval.

III. ADAPTIVE FORWARDING SCHEME

In this section, we introduce the proposed Adaptive For-warding scheme.

A. overviewNetwork coding is known to be robust to channel error.

However, its performance rapidly degrades in the presence ofhigh packet error rates caused by jamming or congestion [9].Namely, a destination node cannot collect enough encodedpackets. Adaptive Forwarding counteracts jamming attacks by

exploiting redundant packet generation in network coding.Unlike end-to-end source coding, network coding allows eachintermediate node along the path to participate in the encodingprocess. Thus, each node can generate an unlimited numberof encoded packets individually from packets received fromupstream nodes. If a node detects jamming attacks at down-stream nodes, it generates/forwards more encoded packets.When channel conditions become stable again, the node de-creases the number of forwarded packets.

The main purpose of Adaptive Forwarding in networkcoding is the efficient use of resources namely wirelesschannel bandwidth and processing power. A node keeps lowforwarding rate in stable channel conditions and boosts the rateonly during jamming attacks. Adaptive Forwarding is a localphenomenon. It is possible that only a small fraction of nodesincrease the forwarding rate in the area exposed to jamming.This is in contrast to end-to-end coding, say Fountain Codingor Raptor Coding that in case of attack, must increase theredundancy along the entire path, with loss of efficiency.

A critical challenge in jamming control is the ability todiscriminate between jamming and congestion. Both eventscause high packet collision and delays. We propose the fol-lowing “probing” strategy. Each intermediate node periodicallyprobes the channel by marginally increasing the forwardingrate. If it detects improved (shorter) delay and packet delivery,it assumes that the channel is jammed. If instead the rateincrease causes degradation in delay and packet delivery, itconcludes that the channel is congested. A detailed discussionand evaluation of this discrimination strategy is beyond thescope of this paper. In our simulation, for simplicity we onlyassume exposure to jamming.

B. Network Coding

Unlike conventional store and forwarding, network cod-ing allows intermediate nodes to encode packets and tosend/forward the encoded packet instead of the original packet.Since the seminal work by Ahlswede et al. [10], network cod-ing has been extensively studied to improve the performanceof wireless networks [11], [12].

To implement network coding, we use the “Random LinearNetwork Coding” scheme [13]. A source node divides adata stream into equally sized packets p1,p2,p3, . . ., wheresubscripts represent consecutive and unique sequence num-bers. Note that we use lowercase boldface letters to denotevectors or packets and uppercase boldface letters to denotematrices. Those packets are grouped into k packets calledgeneration, e.g., k = 8 in our simulation. The generationsdo not overlap, and only packets in the same generationare encoded together. For random linear coding, a coefficientfor encoding is randomly drawn from a finite field, e.g.,GF(28) in our simulations. A set of coefficients, called globalencoding vector, e = [e1 . . . ek], is recorded in the packetheader and sent along with the encoded packet for the purposeof later decoding at the receivers. A coded packet cj is alinear combination of packets in the same generation, and the

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subscript j is generation id. That is,

cj =k−1∑i=0

eipjk+i (1)

Upon receiving an encoded packet, intermediate nodes storeit into their local buffer1 if its encoding vector is innovativethat is linearly independent to other buffered encoding vectorsin the same generation. Intermediate nodes re-encode andforward packets when they receive k innovative packets in thesame generation or a certain period has passed since the firstpacket in that generation arrived. Re-encoding is through thesame process that the data source has undergone to generatea coded packet. Note that the packets in the buffer are codedat least once and thus the re-encoded packet cj is generatedby,

cj =k−1∑i=0

eici. (2)

Moreover, the global encoding vector is attached at the headerof re-encoded packet after linearly combined. That is,

ej =k−1∑i=0

eiei (3)

If a receiver collects enough encoded packets, k innovativepackets in the generation, original packets are recoveredby Gaussian elimination calculation with a global encodingvector. Now cj is the received coded packets, ej is theglobal encoding vector, and pj is the original packet. LetE = [e1 . . . ek],C = [c1 . . . ck], and P = [p1 . . .pk]. Then,the receiver can obtain original data P using,

P = E−1C (4)

C. Multicast RoutesConventional MANET multicast routing protocols first cre-

ate a multicast tree or a mesh before they start packettransmissions. Most of them aim to build a Steiner treewhich is known to provide the optimal multicast route and tominimize the total link cost. However, generating the Steinertree is an NP-Complete problem. In practice most protocolsestablish a rooted tree or a mesh (i.e., a redundant multiplepath structure). Properly speaking, tree structure protocolssuch as MAODV [14] and E-ODMRP [15], are not wellsuited to run network coding since they do not provide pathredundancy, an important complement of network coding [9],[16]. Mesh structure multicast protocols, e.g., ODMRP [17],are more appropriate for network coding as well as AdaptiveForwarding, and will be used in our experiments. We notethat Adaptive Forwarding does not have a route establishingmechanism of its own - rather, it builds on an existing routingalgorithm.

Besides multicast, Adaptive Forwarding can also workwith pure broadcast (i.e., flooding). In this case, Adaptive

1We simply assume that buffer on each node is large enough to store allthe data for a limited amount of time

Forwarding is applied to broadcast mode without route es-tablishment. Broadcast is quite effective in extreme mobilitysituations where a multicast mesh is hardly and inefficientlymaintained. Adaptive Forwarding is helpful in that it reducesthe uncontrolled packet relaying induced by flooding.

D. Channel Monitoring and Data ForwardingAdaptive Forwarding monitors channel condition via the

promiscuous listening mode. Nodes detect jamming attacksby monitoring the successful forwarding by down-streamneighbors. Say, if the channel is heavily occupied and packetdelivery at down-stream neighbors starts decreasing, jammingis assumed. To monitor successful packet delivery, each nodestamps the rank, r, of the generation as well as the encodingvector in the packet header. The rank indicates the numberof received innovative packets in the generation. If r is lessthan generation size k, the node needs more innovative packetin the generation; otherwise, the node has received enoughencoded packets.

A node can overhear transmissions of down-stream neigh-bors because of the wireless shared medium. If a down-streamneighbor has not completed the generation, e.g., r < k,the node in question forwards more encoded packets to thatneighbor to help it complete the generation. The number ofpacket retransmissions is larger than 1 and less than k− r. Ifthe node fails to hear down-stream node transmissions, it doesnot retransmit since the link may be broken due to mobility (orthe down-stream node is a leaf node). If the packet deliveryat the down-stream node does not improve, a node suspectscongestion. It thus starts decreasing the forwarding rate.

Intermediate nodes must relay received packets, but areceiver does not if it is a leaf node. Thus, the receivercannot “implicitly” solicit packet retransmissions by up-streamnodes. To solve this problem, we use the timer function.Once a certain interval has passed since the first packet inthat generation arrived, receiver nodes (leaf nodes) send outdummy packets recording the rank r in the header. Oncethe generation is completed, a receiver skips dummy packettransmission.

E. Adaptive Forwarding Rate ControlForwarding rate, c, is the “fraction of the packets in a

generation” transmitted by an intermediate node defined by,

c =m

k(5)

where m is the number of packet forwarded and k is thegeneration size. Nodes adjust c after reading down-streamnode’s r value. The higher the fraction c, the higher theredundancy. In fact, informally, the product of the fraction andthe “min cut” in the pathway to the receiver(s) determines theredundancy. If a node overhears that the down-stream neighborhas failed to complete the generation, r < k, it increases theforwarding rate c; otherwise, it decreases c. More precisely,the value is linearly increased/decreased as follows,

cnew =

{cold + αk if r < k,cold − αk otherwise

(6)

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where α is a constant value, e.g., α = 1k in our simulation.

We assume the jammer cannot completely fill the channels sothat nodes in the jammed area still receive some packets fromup-stream nodes and manage to transmit some of their ownpackets to downstream. Thus up-stream nodes overhear packettransmission from nodes in the jammed area and read r <k. They linearly increase the forwarding rate squeezing morepackets through until the nodes in the jammed area collect afull generation. When the jamming attack is terminated, nodeslinearly decrease the rate since redundant packet transmissionis no longer necessary.

Adaptive Forwarding employs the maximum and the mini-mum forwarding rate thresholds to prevent unlimited increas-ing and decreasing and thus c value is bound cmin ≤ c ≤cmax. In our simulation, we use cmax = 2k and cmin = k

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IV. SIMULATION

In this section, we validate our Adaptive Forwarding schemeusing QualNet [18], a packet level network simulator. Weuse IEEE 802.11 MAC and PHY layer with two-way groundpath-loss propagation model and 2Mbps channel bandwidth.A source node transmits 1Kbps constant bit rate traffic. Eachsimulation run lasts 500 seconds. All results are averaged over100 simulation runs. Two topologies are designed: a grid topol-ogy and a random topology. The simulation settings aboveare applied to both topologies unless otherwise specified. Theanalytic model is applied only to the grid topology.

As shown in Figure 1, the grid topology has a single sourceand multiple receivers. Every node except the first hop nodeshas n multiple upstream nodes. That is, a node is able toreceive n packets from n parent nodes. In the grid topology,n is a fixed value, e.g., 3 in our simulations. The numberof hops from a source to receivers is defined as h (h=5 inFigure 1). In the random topology, 50 nodes including a singlesource and 10 multicast receivers are randomly distributed ina square field. The Adaptive Forwarding scheme works withany MANET routing protocol, uni or multicast. However, inthese simulation experiments, we use broadcast without anynetwork layer routing protocol to isolate the performance ofthe Adaptive Forwarding scheme excluding the impact of otherprotocols.

We use two metrics: Packet Delivery Ratio (PDR) thefraction of recovered packets averaged over all receivers; andNormalized Packet Overhead(OH) the total number of packettransmissions by the network divided by the total number ofdata packets actually recovered. We evaluate and compareAdaptive Forwarding performance with fixed rate networkcoding in which fixed forwarding rate c = 1.

A. Grid TopologyWe inject a random jamming attack in the grid topology. At

random time, jamming attack starts, which affects the secondhop nodes, node 5, 6, and 7 in Figure 1. In our simulation, theylose 50∼90% of packets that previous hop nodes have trans-mitted. Jamming attack lasts a few seconds to several tens ofseconds. Figure 2 shows the PDR of Adaptive Forwarding andfixed forwarding rate network coding in the grid topology withrandom jamming attack. The Adaptive Forwarding schemewith network coding delivers 100% packets under seriousjamming. Fixed forwarding rate network coding maintainsover 99% packet delivery ratio up to 60% of jamming lossat the second hop nodes, but performance rapidly degradesabove 60% jamming loss. Finally, PDR drops 50% with 90%jamming loss while Adaptive Forwarding keeps 100% packetdelivery.

Figure 3 presents the OH of adaptive and fixed forwardingrate network coding. In normal situation (no or low jamming),Adaptive Forwarding features lower overhead than fixed for-warding. Adaptive Forwarding OH increases as a functionof jamming loss since up-stream nodes must increase theirforwarding rate to compensate the loss. At 90% jamming loss,the Adaptive Forwarding OH is higher than fixed forwardingrate network coding. While the jamming loss increases, thenumber of received packets at destinations decreases so thatfixed rate network coding OH increases, too.

Figure 4 describes the forwarding rate change in the gridtopology. Y axis is the number of forwarded packets at onenode, and X-axis is simulation time. Grey area represents thejamming attack period. In Figure 4, the black line representsthe number of forwarded packets m in the generation k (wherek = 8 in our case) at node 3 which is the up-stream nodeof the second hop where jamming occurs. The dotted line isthe number of forwarded packets in the generation at node 9which is the down-stream node of the second hop nodes (seeFigure 1). We expect that node 3 will do most of the workto combat jamming, by increasing the forwarding rate; whilenode 9 is far enough from jamming to be less affected. Bothnodes forward the same number of packets at the beginning,but within the second jamming period (the first period is tooshort), the two lines in Figure 4 become separated. Node3 increases forwarding rate up to the maximum value =16i.e., cmax = 2k

k during the jamming period, and it reducesthe rate once jamming ends. During the jamming period,initially node 9 fails to overhear the complete generation (fromits downstream nodes) since up-stream nodes cannot sendenough packets due to jamming. So, node 9’s forwarding rateincreases. However, once the first hop nodes, i.e., node 2,

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3 and 4, react to jamming and transmit enough redundantpackets, this problem is resolved and node 9’s forwardingrate decreases. This confirms our conjecture that AdaptiveForwarding tends to keep the retransmissions localized in thejamming area. In Figure 4, we can clearly see how AdaptiveForwarding dynamically adjusts the forwarding rate againstjamming.

B. Random Network TopologyIn a network topology, 50 nodes are randomly distributed

in a 1500m by 1500m field, and one source node broadcastspackets to 10 multicast receivers. Nodes move around based onRandom Waypoint mobility model in which the maximum andthe minimum node speeds are 20m/s and 1m/s, respectively,with no pause time. Figure 5 shows an example of topology.Grey area is the jamming area where the jammer appliesrandom jamming scheme at random times and with randomintervals.

Figure 6 and 7 show the PDR and the OH of both for-warding schemes in the random network topology. Like thegrid topology case, Adaptive Forwarding outperforms fixedrate network coding in terms of packet delivery ratio. Curvesin Figure 6 show the same patterns to those in Figure 2, butPDRs are degraded in Figure 6 due to random distributionand mobility. Nodes in the grid topology are completelyconnected all the time; yielding 100% PDR with AdaptiveForwarding. On the other hand, nodes may be temporarilyseparated or partitioned due to randomness and mobility in therandom topology, thus 100% delivery cannot be guaranteed.In Figure 6, degradation of PDR in fixed forwarding ratescheme is not as severe as one of Figure 2 since the jammingattack affects only a portion in the field. Thus, there are fewreceivers in the jamming area which can also escape fromthe area due to high mobility. We can observe only onereceiver in the jamming area in the snapshot in Figure 5. TheOHs of two schemes cross over each other at 70% of packetloss and Adaptive Forwarding overhead keeps growing as theforwarding rate increases in the attempt to maintain a highpacket delivery ratio. In the fixed forwarding rate case, both thenumbers of forwarded packets and received packets decreasein terms of channel/link error, and thus overhead change is notsignificant.

V. RELATED WORK

Navda et al. [4] explored a channel hopping technique with802.11 MAC and PHY layer to achieve resiliency to jammingattacks. Each communication, in the proposed system, proac-tively hops channels according to a pseudo-random sequenceregardless of existence of a jammer. Xu et al. [6] proposedreactive channel hopping where each communication jumpsto other available channels only when communicating nodeshave detected jamming in the current channel. The authorsinvestigate jamming attack detection strategies both in MACand PHY layers. In the MAC layer, a sensing-time thresholdmechanism detects abnormal failures due to attacks. A sendingnode monitors the duration of carrier-sensing time, and if it isabove the threshold, the node declares occurrence of jammingattack. The PHY layer detects jamming attack by monitoringthe level of ambient noise and comparing it with own statisticalmodel which has been built from noise levels gathered priorto the jamming attack.

Jiang and Xue [2] showed global and local restorationmethods that reroute flows and/or re-assign the flows tonew channels in response to jamming attacks. In the globalrestoration, all the flows in the network are rerouted in theway of maximizing the minimum network throughput. Thelocal restoration, on the other hand, reroutes and/or assignsnew channels to flows on the intermediate paths affected byjamming attacks. Liu et al. [3] proposed cylinder architecture,a layered networking stack that implements multiple protocolsfor each layer. For example, the MAC layer may implementALOHA, CSMA/CA, and TDMA. Then, each pair of thesender and the receiver selects one combination of layeredprotocols, namely mechanism, for their communication. Byhopping between multiple mechanisms dynamically, the paircan avoid jamming. Noubir et al. [5] addressed feasibilityof a low-power jamming attack where corrupting a smallnumber of data bits leads to the loss of the entire packetand proposed a combination of an error control code andinterleavers. The control code encodes the data bits, and theencoded packet bits are interleaved in a secret way. As a result,the proposed mechanism forces jammers to do more effort andto consume more energy to corrupt the same amount of bitsin the communication channel.

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Fig. 6. PDRs in random network topology. Onesource and 10 receivers. Maximum node speedis 20m/s and minimum node speed is 1m/s.

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Fig. 7. OHs in random network topology. Onesource and 10 receivers. Maximum node speedis 20m/s and minimum node speed is 1m/s.

Channel hopping is good ammunition for jamming attack,but it requires re-design of MAC and PHY layer that enablechannel scanning and hopping. Global and local path restora-tion also requires a centralized architecture and algorithm thatknows the whole network topology and channel assignments.Thus it is not a practical solution for the ad hoc network.Moreover, for the cylinder architecture, we must implement allprotocol for each layer in the interface. Noubir et al. proposedtemporal redundancy, but it only handles low-power jammingattack.

VI. CONCLUSIONJamming attack in the MANET can cause widespread

disruption and have significant effects on existing communica-tions. Previous research has introduced several remedies, butmost proposed schemes are not practical in tactical scenarios.In particular, they do not mention solutions that work withmulticast. In this paper, we propose a novel scheme, AdaptiveForwarding, based on network coding that dynamically adjustsforwarding rate locally reacting to channel condition so thatnodes inject redundant encoded packets only when and wherejamming occurs. In normal situation, Adaptive Forwardingdecreases the forwarding rate to save resources. We reportsignificant performance gains (with respect to fixed forward-ing) through the simulation study. In future work, we plan tostudy the performance of the proposed algorithm in congestedscenarios, to test the ability to distinguish jamming attack fromnormal congestion. In addition, we plan to implement and testAdaptive Forwarding in our MANET testbed.

ACKNOWLEDGEMENTThe work presented in this paper was sponsored in part by

the US Navy under a Small Business Technology Transfer(STTR) Phase II program (contract number N00039-09-C-0041). This program is managed by the Joint Program Ex-ecutive Office Joint Tactical Radio System (JPEO JTRS); andsome of the Network Coding work was done through partici-pation in the International Technology Alliance sponsored bythe U.S. Army Research Laboratory and the U.K. Ministry ofDefense under Agreement Number W911NF-06-3-0001.

REFERENCES

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