Multi-path Routing with Load-aware Metricfor Tactical Ad Hoc Networks

Ji Yong Choi and Young-Bae KoDepartment of Computer Engineering, Graduate School of Ajou University,

Suwon, Republic of Koreagchoi@uns.ajou.ac.kr, youngko@ajou.ac.kr

Abstract—To support reliable communication in tacticalarea networks, multi-path routing protocols can be utilized.Multipath routing protocol makes decisions to selectprimary route and alternative path by using routingmetrics. Link quality routing metrics are popularly usedfor route selection but it may cause bottleneck andcongestion problems. To overcome these problems, we canconsider the traffic loads or congestion level into routingmetric. In this paper we propose a load-aware routingmetric which is based on Airtime link cost metric andcombines traffic loads measured from MAC layer. Tomaximize load balancing effect, we utilize our proposedload-aware routing metric into a multipath routingprotocol. The performance of the proposed metric isevaluated with the OPNET simulator and compared withother routing metrics.

Keywords-Tactical Ad Hoc Networks, Multi-path Routing,Load-aware Routing, Load-balancing, Airtime link cost

I. INTRODUCTION

The Network-Centric Warfare (NCW) paradigmrepresents the future military vision. In this paradigm,ubiquitous network access to enabling “anytime,anywhere” communications is necessary on thebattlefield. This potentiality will be provided by theGlobal Information Grid (GIG), a collection of variousnetworks and more particularly the tactical networks. Forthe tactical networks, Mobile Ad hoc Network (MANET)technology is very attractive. In order to complete anassigned mission, a MANET is constructed from adifferent set of participants who must interact. InMANET, a group of mobile nodes is able tocommunicate with each other through multi-hop wirelesscommunications without any predefined infrastructure,therefore, establishing and connectivity autonomously.The characteristics of MANET are very interest for a lotof situations which are needs of communications withoutinfrastructure or may be used in disaster recovery,automated battlefield and etc. The challenges related tothe use of MANET in the field of military tacticalnetwork has been described [1].

The tactical networks are designed to support militarymissions in the battlefield. In this paper, we focus ontactical wireless network which has no wired connectionsbetween the network members likely tactical MANETs.Tactical wireless networks may experience difficulties ofcommunication in mission-critical applications becauseof many different types of environmental conditions,such as obstacles and severe weathers, low signalstrength, node mobility, interference, jamming attacks,etc. Considering these environments, reliablecommunications are actively discussed amongresearchers and have become one of the most prominentissues in tactical ad hoc networks.

To enhance the reliability of a routing protocol, multi-path routing protocols can be utilized. In single pathrouting, the discovered routes may have problems in thatthey could be easily broken due to node mobility orunpredictable link conditions. This problem may causetransmission failures and delay in the network, whichmakes the protocol unreliable. Also, the single pathrouting takes time to recover or re-discover the brokenroutes. To overcome the limitation of the single pathroutes, methods that discover multiple multi-hop routesbetween the source node and destination node have beensuggested instead.

The multipath routing protocols can use multiplepaths simultaneously on a communication. Also, it canuse one route at a time. Utilizing alternative paths, amultipath routing protocol makes the decision of whichpath will be the primary path or alternative route by usingrouting metrics. When a link quality routing metric isused for route selection, it may cause bottleneck problemwhich means that many routes pass through a particularlink while the link has good quality. To solve thisproblem, we can consider traffic loads or congestionlevel into the routing metric. Load-balancing in this caseis important in determining the amount of traffic on eachpath while minimizing the cost function. In this paper, wepropose a load-aware routing metric that combines thelink quality and load balancing features.

"This research was supported by the MKE(The Ministry of Knowledge Economy), Korea, under the ITRC(Information Technology Research Center) supportprogram supervised by the NIPA(National IT Industry Promotion Agency (NIPA-2010-(C1090-1021-0011)) and the Basic Science Research Program through theNational Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2010-0016189)"

978-1-4244-9807-9/10/$26.00 ©2010 IEEE ICTC 2010370

The remainder of this paper is organized as follows.In Section 2, we discuss the related works on routingmetrics, load-aware routing and multipath routingprotocols. We present our proposed load-aware routingmetric in Section 3 and give a brief introduction of theRHMR [2] protocol. In Section 4, we discuss thesimulation experiments that the comparison of theproposed metric and other metrics. We conclude ourpaper and discuss the potential future works in Section 5.

II. RELATED WORKS

Routing metrics are an important method in routingprotocols because routes are discovered or selected byrouting metrics. It means that routes are depending onrouting metrics. Therefore, routing metrics are verycritical for determining the performance of the networks.A good routing metric should find paths with links thathave high data rate, low loss ratio, low level ofinterference and less congestion. Recently many routingmetrics have been proposed for multi-hop mobile ad hocnetworks (MANETs) and wireless mesh networks(WMNs). Some of them include: (1) Hop-count, (2)Expected Transmission Count (ETX), (3) ExpectedTransmission Time (ETT), (4) Weighted CumulativeExpected Transmission Time (WCETT), (5) Metric ofInterference and Channel switching (MIC), (6)Interference Aware routing metric (iAWARE), and (7)Airtime link cost. Comprehensive surveys on routingmetrics can be found in [3] and details of airtime linkcost metric can be found in [4]. (2) ~ (7) are consideredthe link quality for routing metrics and widely use. Linkquality routing metrics are popularly used for routeselection but it may cause bottleneck and congestionproblems. To overcome these problems, we can considerthe traffic loads or congestion level into routing metric.

Various load-aware routing protocols and metricshave already been proposed for both MANETs andWMNs. These load-aware routing protocols incorporatethe load factor into their routing metrics. The dynamicload-aware routing (DLAR) [5] uses the number ofpackets buffered at an interface as the load metric.However, the interface queue length by itself does notreflect the correct status of the actual load in 802.11MAC-based protocols. The load-balanced ad hoc routing(LBAR) [6] also uses the queue length at an interface asthe load metric, which sums up node’s average queuelength and the neighbor node’s average queue length.This load metric can be considered more accurate thanthe one used in DLAR. Both the DLAR and LBAR aredesigned for the mobile ad hoc network, and aim toreduce the packet delay and the packet loss ratio.However, those protocols do not consider link quality.Link quality metrics help to find the route that has lowloss ratio and stable links.

LAETT [7] provides a path satisfying the bandwidthrequest of the flow and combines wireless accesscharacteristics and load estimates. LAETT depends onthe estimation of the effective bit rate (EBR). For a node,the EBR of its access link represents the amount of trafficthat can be successfully delivered over the access link inunit time. WCETT load balancing (WCETT-LB) [8] isthe WCETT augmented by the load factor consisting ofthe average queue length and the degree of trafficconcentration. LARM [9] captures not only differences indata rate, link loss ratio, intra/inter-flow interference butalso traffic load. Specifically, it captures traffic loadwhich is the sum of the node’s average queue length andthe neighbor node’s average queue length. LARM isincorporated into load balancing routing protocol LBM toprovide load balancing in multi-radio wireless meshnetwork. LAETT, WCETT-LB and LARM capture linkquality and traffic load features unlike DLAR, LBAR.However, existing load-aware routing metrics, whichcombined with link quality features, are highly complexto measure such as LAETT, WCETT-LB, etc.

In order to balance load in Tactical Ad Hoc Networks,routing metrics need to accurately capture the load invarious locations of the network. Furthermore, routingprotocol needs to distribute traffic among mobile nodesto avoid creating congested areas. Different from existingrouting metrics, our routing metric, Load-aware AirtimeLink Cost captures traffic load which is the maximumvalue of the node’s average queue length and the numberof neighbor nodes which shares a same channel.

Utilizing multipath routing is one of the ways toprovide load balancing because multipath routing candistribute traffic from a source to a destination by usingmultiple paths. Numerous multipath routing protocolshave been proposed based on the popular reactive routingprotocols, such as Dynamic Source Routing (DSR) andAODV (Ad hoc On-demand Distance Vector). MP-DSRand Split Multipath Routing (SMR) are based on DSR.AODVM is a multipath design over the AODV that candiscover multiple node-disjoint paths. The AODVM-PSPprotocol is an extension of AODVM protocol. Thedifference between AODVM-PSP and AODVM is thatAODVM-PSP considers delays along a path whilemaking a routing decision. Since the route discoveryprocess of AODVM-PSP is not as frequent as that ofAODVM, there is always a probability of not finding aroute, but this reduces the overhead. The detailed surveyson aforementioned multipath routing protocols and othermultipath routing protocols can be found in [10].

Recently, as the proactive mechanism for multipathrouting, MP-OLSR [11] was proposed over the OLSRprotocol. In MP-OLSR, the node uses the Multi-pathDijkstra algorithm to find the multiple paths with node-

371

disjoint or path-disjoint properties based on the entiretopology information. If a link or node failure occurs, thenode detecting the failure re-computes the alternativepath based on the topology information in the node andthen forwards the packet through the new route. In [12],the authors propose Adaptive State-based Multi-pathRouting Protocol (ASMRP) to increase reliability of datatransmission, allowing adequate fault tolerance in WMNs.The ASMRP is opportunistically exploits multiple pathsto synergistically improve the overall performance ofWMNs. This algorithm is effectively discovers multiplepaths and employs an elegant traffic splitting algorithmfor balancing traffic over these multiple paths.

For a tactical environment where reliability and real-time data service is essential, these works may have someproblems such as frequent control message exchanges,high node mobility, etc. However, hybrid multipathrouting protocols by fusing the characteristics of reactiverouting and proactive routing can alleviate some of theproblems that these protocols may have. In [2], theauthors proposed hybrid routing that called ReliableHybrid Multipath Routing (RHMR). The hybrid routingdesigns can reduce data transmission delay and also bemore resilient to node mobility and errors. In order to this,we utilize our proposed routing metric into RHMR toprovide and maximize load balancing in tactical mobilead hoc networks.

III. MULTI-PATH ROUTING WITH LOAD-AWAREMETRIC FOR TACTICAL AD HOC NETWORKS

The proposed routing metric, load-aware airtime linkcost, is based on calculation of airtime link cost specifiedin the IEEE 802.11s standardization [4]. Load-awareAirtime Link Cost introduces load factor measured fromMAC Layer at the mobile nodes and supports load-awarerouting. The integration of the load balancing feature tothe airtime link cost calculation and the congestion awarerouting scheme can provide reliable communications atthe view point of the entire network.

A. Load-aware Airtime Link Cost MetricAs mentioned before, we utilize airtime link cost as

the link quality feature in Load-aware Airtime Link Cost.Instead of well-known link quality metrics such as ETT

(Expected Transmission Time), we utilize airtime linkcost because it can support multiple radio environments.In tactical ad hoc networks, they may use multiple radiosto communicate between various types of devices.

The airtime link cost metric defines the amount ofchannel resources consumed by transmitting the frameover a particular link. This measure is approximate anddesigned for ease of implementation and interoperability.The airtime link cost for each link is calculated as:

f

ta er

BOC−

+=

11

(1)

where O and Bt are constants listed in Table 1 (airtimelink cost constants), and the input parameters r and ef arethe data rate in Mbps and the frame error rate for the testframe size Bt respectively. The rate r represents the datarate at which the mobile node would transmit a frame ofstandard size Bt based on current conditions and itsestimation is dependent on local implementation of rateadaptation. The frame error rate ef is the probability whena frame of standard size Bt is transmitted at the currenttransmission bit rate r, the frame is corrupted due totransmission error. The details of airtime link cost can befound in [4].

The load balancing feature in Load-aware AirtimeLink Cost which we define as traffic load (TL) ismeasured by the node’s average queue length and thenumber of neighbor nodes which shares same channel.The traffic load for each interface at a node is calculatedas:

rNQCaTL x

l×

×= (2)

where Cal is the existing airtime link cost thatmeasured at a node in a particular link l. Qx is the averagequeue length which represents the average number of bitsin the queue that measured at the interface x in a node. ris the data rate in Mbps which is similar to the usage inairtime link cost calculation. We take the fraction of theaverage queue length over the data rate to get the actualtime needed for transmission. We consider the trafficconcentration of each node by using N which representsthe number of nodes that shares same channel. So, ifmore neighbor nodes choose l as their next-hop forpacket transmission, the traffic at the node increases.Therefore, such a node has higher probability to becomecongested in the network.

In the proposed approach, we integrate load balancingcomponent which we called traffic load into Airtime link

TABLE I. AIRTIME COST CNSTANTS

Parameters RecommendedValue Description

Ovaries

depending onPHY

Channel access overhead, whichincludes frame headers, trainingsequences, access protocol frames,etc.

Bt 8192 Number of bits in test frame

372

cost metric. The proposed Load-aware Airtime Link Costmetric calculated as:

)(max)1(11

jkj

k

ii TLCaMetric

≤≤=

×+×−= ∑ αα (3)

where TLj is the calculated value of traffic load onnode j. We consider the maximum value of traffic loadon a route because the bottleneck node may have hightraffic load. The total path throughput will be dominatedby the congested node or link, which has the largest valueof TLj. k is the number of hops in a route.

Therefore, α (alpha) is a tunable parameter subject to0 ≤ α ≤ 1. The proposed metric is incorporated into loadbalancing routing protocol RHMR to provide loadbalancing in tactical mobile ad hoc networks.

B. RHMR Protocol and Simple ModificationThe Reliable Hybrid Multi-path Routing (RHMR) [2]

is a hybrid routing protocol which has both proactive andreactive routing characteristics. RHMR basicallyprovides proactive-like routing with route discovery andmaintenance mechanism of the reactive routing protocols.In order to tactical wireless networks have characteristicof long-distance, RHMR periodically discovers multipleroutes toward every node in the network with long timeintervals by Periodic Route Discovery Message (PRDM).The interval can be dynamically re-configured dependingon the node mobility or the link quality. Then, itmaintains routing table with multiple routes for entirenetwork like traditional proactive routing protocol andselects the best route among them. This route will bedefined as the master route.

To avoid route loop, RHMR finds node-channel-disjoint routes. The node-channel-disjoint routes can bediscovered by PRDM forwarding rule. The PRDM isonly processed if the sequence number is new or there isno entry in the routing table which has the routeinformation such as the previous hop and the channelindex toward the source node. In other cases, the nodejust updates the route information about the source nodeand previous node without forwarding PRDM. When themaster route failure detected, RHMR firstly switchesmaster route to second highest alternative route. However,if no route to switch or new route request occurs (newdestination that has not been discovered yet), thisprotocol re-discovers or finds new route with reactiverouting manner that using On-demand Route RecoveryMessage (ORRM).

In RHMR, route selection is depending on multiplerouting metrics which are Link Quality (LQ) and ChannelTrigger Count (CTC). The LQ is the accumulative value

that the link quality of every hop in a path. The CTC isthe number of channel changes between the current hopand previous hop. This protocol compares theaccumulative LQ of existing master route in the routingtable with the newly updated route and marks the routewith better LQ as the master route. If the link quality ofcomparing routes is equal, the hop count and CTC will beconsidered respectively. The priority among the metricsselects the route with less accumulative link quality andfewer hop count as the master route.

In this paper, we have modified control messages ofRHMR to utilize our proposed load-aware routingmetric. We simply add traffic load field to the controlmessages. To find the maximum value of TL on a route,it compares with TL value of current node. Only if thevalue on a current node is higher than the value containedin TL field, the node changes the value in TL field to thevalue of current node. This process has been added tomessage handling process of PRDM and ORRM inRHMR. With this process, each node can calculate theproposed load-aware airtime link cost metricindependently.

IV. SIMULATION AND RESULTS

Using OPNET simulator [13], we compare theperformance of the proposed metric and WCETT-LB,LARM, and airtime link cost defined in IEEE 802.11s.These metrics are utilized on RHMR.

A. Simulation EnvironmentsWe use two evaluation metrics: packet delivery ratio

and average end-to-end delay. The packet delivery ratio(PDR) represents the count of successful data receptioncompared to the total number of generated data. Theaverage end-to-end delay is defined as average value ofthe delay between the time which the data packetgenerated at the source and the time of the data packetreaches the destination. Otherwise, it includes the queue

TABLE II. SIMULATION PARAMETERS

Environment Parameters Values

Medium Access Control Protocol IEEE 802.11g

Area Size of Environment 12.5 Kmｘ 12.5 Km

Number of Nodes (N) 10

Number of Traffic (T) 100 per 1 second(each 100 Kbps, 200 Kbps)

Interval of PRDM 50 seconds

Node Transmission Range 5 Km

Mobility Speed (M) 0, 10, 20, 30 m/s

Mobility Model Random Waypoint

Simulation Time 300 seconds

373

delay in every node and the propagation delay from thesource to the destination.

A wide variety of system parameters is used forevaluation in tactical MANET. The detailed networkparameters are as shown in Table 2. In our simulation,the node has three IEEE 802.11g interfaces withorthogonal channels in each interface, such as channel 1,7, and 13. The data traffic generates a packet with thepayload size of 1 Kbits at every 10 millisecond (100Kbps) and 2 Kbits at every 10 millisecond (200 Kbps)after 10 seconds have elapsed in the simulation. Theamount of data traffic will be various. The PRDMinterval of 50 seconds has been configured as a defaultvalue in RHMR. Therefore, the tunable parameter α is setto 0.5 as generally used in most routing metrics [3]. Intactical wireless networks, the transmission range isgenerally considered between 5~10 Km. IEEE 802.11links are being used in long-distance setting that is up toseveral tens of kilometers [14].

B. Simulation ResultsThe simulations are carried out more than 10 times

and simulation results are calculated to average values ofall the combined results. Two types of simulation wereconducted. First case is 100 Kbps of data packetsgenerated per node. The other case is 200 Kbps of datapackets generated on each node. Also, the simulations arecarried out with different mobility speeds that are nomobility (0 m/s), 10 m/s, 20 m/s and 30 m/s.

Fig. 1 and Fig. 2 show the simulation results with 100Kbps data traffic scenario. Fig. 1 shows the simulationresults of average end-to-end delay in 100 Kbps scenario.As we can see from the figure, compared with the othermetrics, proposed metric reduces end-to-end delay byconsidering traffic load feature even though nodes havehigh mobility speed. In the static case (no mobility), theproposed metric reduces more than 30% compared withairtime link cost. This result came from avoidingcongested node. Fig. 2 shows the packet delivery ratio of

Figure 1. Average End-to-End Delay (mili-seconds) Figure 2. Packet Delivery Ratio (%)

Simulation results with 100 Kbps of data packets per node

Figure 3. Average End-to-End Delay (mili-seconds) Figure 4. Packet Delivery Ratio (%)

Simulation results with 200 Kbps of data packets per node

374

the simulation results. In the figure, we can see littleimprovement of proposed metric in PDR results.

The simulation results of 200 Kbps data packetsscenario are shown in Fig. 3 and Fig. 4. In Fig. 3, we cansee the average end-to-end delay of simulation results.Although, there were more traffic loads than 100 Kbpsscenarios, Fig. 3 shows the similar simulation results withFig. 1 that the proposed metric has better performancethan the other metrics. Fig. 4 shows the packet deliveryratio of this scenario. In this figure, we can see differentresult with Fig. 2. This result shows that the proposedmetric has better packet delivery ratio than other routingmetrics specially compared with airtime link costimproved 2 ~ 6 %. It looks a small enhancement butthroughput results tell us that improved 5 ~ 34 Mbps. Wedidn’t put the throughput results in this paper because ofnot enough space.

In the figures, proposed metric improves theperformance of packet delivery ratio and reduces theaverage end-to-end delay. As a result, proposed metriccan be thought superior compared to its counterparts. Theproposed metric is able to discover routes that avoidingbottleneck links by considering traffic load. This is whythe proposed metric has better performance than airtimelink cost. Therefore, the proposed metric has enhancedperformance comparing with WCETT-LB, LARM byconsidering number of neighboring nodes.

V. CONCLUSION AND FUTURE WORKS

In tactical ad hoc networks, reliability and real-timedata service is essential. With this tactical characteristic,the load-aware routing metric is able to be an effectivemethod to support the load balancing and the reliablecommunication with redundant paths in tactical wirelessnetworks. In this paper, we propose a Load-awareAirtime Link Cost metric and utilize it to RHMR forsupporting load balancing and reliable communicationsin tactical mobile ad hoc networks. Simulation resultsfrom OPNET simulator have shown performanceenhancement in packet delivery ratio and end-to-end

delay. We will focus on the researches that the variousdata traffic type with load balancing. This parametereffects by more comprehensive simulation study andanalysis to enhance the reliability of tacticalcommunication. Also, our simulation includes variousenvironments, such as node density, multiple radios,different network sizes. Therefore, one another study, thismetric with other routing protocols will be carried out.

REFERENCES

[1] J. L. Burbank, P. F. Chimento, B. K. Haberman, and W. T. Kasch, “KeyChallenges of Military Tactical Networking and the Elusive Promise ofMANET Technology”, IEEE Communications Magazine, vol. 44, 2006.

[2] S. W. Lee, J. Y. Choi, K. W. Lim, Y. B. Ko, and B. H. Roh, “A Reliableand Hybrid Multi-path Routing Protocol for Multi-Interface Tactical AdHoc Networks”, in Proc. IEEE MILCOM 2010.

[3] M. Campista, P. Esposito, I. Moraes, L. H. Costa, O. C. Duarte, D.Passos, C. V. de Albuquerque, D. C. Saade, and M. Rubinstein,“Routing Metrics and Protocols for Wireless Mesh Networks”, IEEENetwork, vol. 22, no. 1, 2008.

[4] IEEE P802.11s™/D7.0, Draft amendment to standard IEEE 802.11™:Mesh Networking. IEEE, July. 2010, work in progress.

[5] S. J. Lee and M. Gerla, “Dynamic load-aware routing in ad hocnetworks”, in Proc. IEEE ICC 2001.

[6] H. Hassanein and A. Zhou, “Routing with load balancing in wireless adhoc networks”, in Proc. ACM MSWiM 2001.

[7] H. Aiache, L. Lebrun, V. Conan, and S. Rousseau, “A load dependentmetric for balancing Internet traffic in Wireless Mesh Networks”, inProc. IEEE MeshTech 2008.

[8] L. Ma and M. K. Denko, “A routing metric for load-balancing inwireless mesh networks”, in Proc. AINAW 2007.

[9] A. N. Le, D. W. Kum, Y. Z. Cho, and C. K. Toh, “Routing with load-balancing in Multi-radio Wireless Mesh Networks”, IEICE Transactionson Communications, vol. E92-B, no.3, 2009.

[10] M. Tarique, K. E. Tepe, S. Adibi, and S. Erfani, “Survey of multipathrouting protocols for mobile ad hocnetworks”, Journal of Network andComputer Applications, vol. 32, no. 6, 2009.

[11] J. Yi, E. Cizeron, S. Hamma, and B. Parrein, “Simulation andPerformance Analysis of MP-OLSR for Mobile Ad Hoc Networks”, inProc. IEEE WCNC 2008.

[12] D. Nandiraju, N. Nandiraju, and D. P. Agrawal, “Adaptive State-basedMulti-radio Multichannel Multi-path Routing in Wireless MeshNetworks”, Pervasive and Mobile Computing, vol. 5, no. 1, 2009.

[13] http://www.opnet.com/, version 14.5[14] S. Sen, and B. Raman, “Long Distance Wireless Mesh Network

Planning: Problem Formulation and Solution”, in Proc. ACM WWW2007.

375