J. Parallel Distrib. Comput. 63 (2003) 154–165

Ad hoc QoS on-demand routing (AQOR) in mobile ad hoc networks

Qi Xue and Aura Ganz�

Multimedia Networks Laboratory, ECE Department, University of Massachusetts, Amherst, MA 01002, USA

Received 17 October 2002

Abstract

We introduce a resource reservation-based routing and signaling algorithm, Ad hoc Qos on-demand routing (AQOR), that

provides end-to-end quality of service (QoS) support, in terms of bandwidth and end-to-end delay, in mobile ad hoc networks

(MANETs). The increasing use of MANETs for transferring multimedia applications such as voice, video and data, leads to the

need to provide QoS support. To perform accurate admission control and resource reservation in AQOR, we have developed

detailed computations that allow us to estimate the available bandwidth and end-to-end delay in unsynchronized wireless

environment. AQOR also includes efficient mechanisms for QoS maintenance, including temporary reservation and destination-

initiated recovery processes. The performance of AQOR is studied in detail by simulation using OPNET Modeler. The results

validate that AQOR provides QoS support in ad hoc wireless networks with high reliability and low overhead.

r 2003 Elsevier Science (USA). All rights reserved.

Keywords: Ad hoc; QoS; Routing; Admission control; Bandwidth reservation

1. Introduction

Future wireless networks will carry diverse multi-media applications such as voice, video and data. Inorder to provide quality delivery to delay sensitiveapplications such as voice and video it is imperative thatmobile ad hoc networks (MANETs) [11] provide qualityof service (QoS) support in terms of bandwidth anddelay [6]. QoS provision in MANETs is a challengingtask since in addition to obeying QoS constraints wemust account also for a dynamic topology and sharedwireless medium.Existing routing protocols in MANET are generally

categorized as: (a) table-driven (proactive) [20], (b)source-initiated on-demand (reactive) [12,21] and (c)hybrid protocols [9]. The table-driven routing protocolsattempt to maintain consistent and up-to-date routinginformation from each node to every other node in thenetwork. This kind of approach has the propertyof lower latency and higher overhead. Source-initiatedon-demand routing creates routes only when desired bythe source node. When a node requires a route to a

destination, it initiates a route discovery process withinthe network. In general, on-demand routing protocolsare characterized as higher latency and lower overhead.In the literature, some researchers have proposed table-driven routing protocols for QoS support [7,22].However, existing studies [3,5,8] show that table-drivenprotocols are more liable to suffer performance degra-dation than on-demand protocols, due to stale routeinformation. Among the on-demand QoS routingprotocols proposed [10,15–17], a CDMA/TDMAMAC layer is commonly used to eliminate the inter-ference between different transmissions. However, it isdifficult to realize such centralized MAC schemes in adynamic wireless environment. Due to network mobi-lity, distributed MAC protocols are widely used inMANET, e.g., IEEE 802.11 DCF [1]. Thus, it isdesirable to have an on-demand QoS routing protocolbased on a distributed MAC layer.Algorithms that provide QoS support in MANETs

should include the following features: (1) accuratemeasurement of bandwidth availability in the sharedwireless channel and accurate measurement of effectiveend-to-end delay in an unsynchronized environment, (2)distributed routing algorithm that adapts with thedynamic environment, (3) resource reservation thatguarantees the available resources, (4) efficient resourcerelease upon route adjustment, (5) instant QoS violation

�Corresponding author. Tel: +1-413-545-4847; fax: +1-413-545-

1993.

E-mail addresses: qxue@ecs.umass.edu (Q. Xue), ganz@ecs.umass.

edu (A. Ganz).

0743-7315/03/$ - see front matter r 2003 Elsevier Science (USA). All rights reserved.

doi:10.1016/S0743-7315(02)00061-8

detection and (6) fast and efficient route recovery. Wepropose a novel ad hoc routing protocol, named Ad hocQoS on-demand routing (AQOR), which includes all thefeatures listed above. To the best of our knowledge,none of the previous published papers incorporate allthese features. AQOR integrates signaling functions forresource reservation and QoS maintenance at per-flowgranularity. We introduce a detailed computation ofavailable bandwidth and end-to-end delay assumingthat access control to the shared wireless channel obeysa distributed collision-based MAC protocol and MAN-ET is an unsynchronized system. These QoS metrics areused by AQOR to make admission and resourcereservation decisions. The computation does not assumea specific MAC protocol, fact that makes AQORcompatible with existing best-effort MAC protocols(e.g., IEEE 802.11 DCF) while in the future it will beable to work with distributed QoS-aware MAC proto-cols (e.g., IEEE 802.11e [18]).The rest of the paper is organized as follows. In

Section 2 we introduce the proposed AQOR algorithm.The performance of AQOR is studied in Section 3, andSection 4 concludes the paper.

2. Ad hoc QoS on-demand routing

To provide QoS, AQOR integrates (1) on-demandroute discovery between the source and destination, (2)signaling functions for resource reservation and main-tenance, and (3) hop-by-hop routing. In general,signaling protocols for resource reservation-basedapproaches, like RSVP [4], contain the following threesteps: connection establishment, connection mainte-nance and connection tear-down. Due to the dynamicfeature of MANET, the connection maintenance over-head (which includes violation detection, recovery andconnection tear-down of the old path) usually outweighsthe initial cost of connection establishment. Because ofthe limited bandwidth in wireless networks, end-to-endsignaling should be kept at a minimum. To reducesignaling overhead, an in-band signaling approach isproposed in [14].In AQOR, we made the following design decisions

that reduce the connection maintenance overhead:(1) AQOR facilitates QoS violation detection at thedestination of the connection who can detect the flow’sactual QoS, without the need of additional signaling; (2)the routing adjustment overhead due to QoS violations,is reduced by employing destination-initiated recovery;(3) the requirement for connection tear-down process,along the old path before route adjustment, is eliminatedby the temporary reservation mechanism.We assume a contention-based medium access me-

chanism such as the IEEE 802.11 DCF. However, sinceDCF does not differentiate between flows, best effort

traffic (which does not use AQOR) can interfere andcause QoS violations. In this case, we use route recoveryto bypass the resulting QoS violations. Future deploy-ment of QoS-aware MAC protocols, e.g., IEEE 802.11e,will reduce the number of such violations.

2.1. Neighborhood maintenance

Neighborhood information is very important inAQOR since it provides the local topology, traffic andmobility information. This information is critical fortraffic measurement, QoS violation detection andrecovery.To maintain the neighborhood information, every

node in the network is required to periodically send outa ‘‘Hello’’ packet, announcing its existence and trafficinformation to its neighbors. Each node I will include inthe Hello packet its self-traffic BselfðIÞ: The definitionand computation of BselfðIÞ is provided in Section 2.3.The Hello packet is sent at a default rate of onceper second, with time to live (TTL ) set to 1. Every nodein the network receives the Hello packets from itsneighbors and maintains a neighbors list NðIÞ whichincludes all its neighbors with their corresponding self-traffic. Failure to receive any packet from a neighbor forTlost period is taken as an indication that the link to theneighbor in question is down.

2.2. Route discovery

In AQOR, the route is discovered on-demand bypropagating the route request and route reply packetsbetween the source and the destination. Our routediscovery algorithm is implemented by route explora-tion from source to destination and route registration inthe reverse path.

2.2.1. Route exploration

AQOR’s route establishment is done on-demandusing limited flooding. When we need to establish aroute and the destination is not in the source’sneighborhood list, the source broadcasts a route requestpacket, which includes the requested bandwidth Bminand end-to-end delay Tmax: Upon receiving the routerequest packet, a bandwidth admission decision is madeat each node as described in Section 2.3.1. If the requestis accepted, the node will add a route entry in its routingtable with status explored and rebroadcast the request tothe next hop. The node will only remain in explored

status for a short period of 2Tmax: If no reply arrives atthe explored node in time, the route entry will be deletedat the node and late coming reply packets will beignored. Thus, we reduce the control overhead as well asexclude invalid information from the node’s routingtable.

Q. Xue, A. Ganz / J. Parallel Distrib. Comput. 63 (2003) 154–165 155

To check the node bandwidth availability as well asgather the end-to-end delay information of eachcandidate route, the route request packets need to travelthrough all the nodes from the source to destination, i.e.,no route caching is used. If priority queueing isimplemented at any node, the route request and thecorresponding reply packets should be transmitted withthe same priority of the requesting flow in order tomeasure the exact queueing delay that will be experi-enced by the flow. To prevent the request packet fromtraveling unnecessarily throughout the network we usethe packet’s TTL. To further reduce the control over-head caused by flooding of route request packets,AQOR can work with some location aided routingprotocols [13].

2.2.2. Route registration

During route exploration there maybe multiple routerequest packets that arrive at destination from differentcandidate routes. Upon receiving each request packet,the destination will send back a reply packet to thesource along the reverse route.When receiving the reply packet, each explored

intermediate node will check its bandwidth availabilityagain to reduce the possibility of transient routes. If thepacket is accepted, the node will update the route statusto registered. After registration, the nodes are ready toaccept the real data packets of the flow. However, thebandwidth reservation for the flow is only activated bythe arrival of the first data packet.The node will only stay in registered status for a short

period of 2Tmax; where Tmax is the maximum end-to-enddelay of the requesting flow. If no data packet arrives atthe registered node in time, it means that the route wasnot chosen by the source. Then the route entry will bedeleted at the node.

2.2.3. Loop-free routing

To avoid possible loops during route exploration,AQOR uses a route sequence number to indicatethe freshness of the control packets for each flow. Thesequence number is maintained at each mobile nodeaware of the flow. The initial sequence number of anyflow is 0. When sending out a route control packet for aflow (e.g., route request, route reply or route error), theinitial node will increase its current sequence number by1 and attach the value to the packet.When control packets are propagated through the

network, only nodes with lower sequence value of theflow will receive it. Upon accepting the route controlpackets, each node will update its own sequence numberwith the sequence number of the control packet.Therefore each node will only forward the first acceptedcontrol packet for a certain flow during one round ofcontrol packet propagation.

Using this mechanism, we guarantee that along theroute discovered no three relaying nodes will be withinthe same neighborhood area of each other because ofthe triangle inequality. This route property reduces thetraffic aggregation effect of the multi-hop flow andminimizes the control overhead by reducing thetransmission of unnecessary control packets. In addi-tion, the route discovered is locally optimal ateach intermediate node, in terms of minimum partialdelay.

2.3. Admission control

For the route discovered that obeys QoS require-ments, the admission control policy should guaranteefor each flow the requested minimum flow bandwidthBmin and the maximum end-to-end delay Tmax: Band-width admission control decision is made at every nodein the exploration and registration phases, based on thedetailed analysis of the traffic in shared channel wirelessnetworks as discussed in Section 2.3.1. In AQOR wechoose the route with the shortest end-to-enddelay given it satisfies the bandwidth requirement. InSection 2.3.2 we introduce a method of measuring theend-to-end delay at the source node assuming anunsynchronized wireless environment.

2.3.1. Bandwidth control

To determine whether there is enough bandwidthavailable for a new flow, all we need to know is theavailable link capacity and the bandwidth to beconsumed by the requesting flow. In wired networksthis is a trivial task since the underlying medium is adedicated point-to-point link with fixed capability.However, in wireless networks the radio channel ofeach node is shared with all its neighbors. Because of theshared medium, a node can successfully use the channelonly when all its neighbors do not transmit and receivepackets at the same time. We call this the aggregation

effect, which results in the following challenges:

1. The available channel bandwidth BavailableðIÞ of nodeI is determined by the aggregated traffic in thechannel and the raw data rate of the node; this valueis time-varying due to node position change.

2. The bandwidth to be consumed by the requestingflow j in the channel of relaying node I ;BconsumedðI ; jÞ; is different from Bmin of flow j becauseof the interference of its relaying neighbor.

To address these two challenges, neighborhood trafficand topology information become indispensable foreach node. To calculate BavailableðIÞ and BconsumedðI ; jÞ;we first define the following symbols:

* B; the raw data rate of the node.

Q. Xue, A. Ganz / J. Parallel Distrib. Comput. 63 (2003) 154–165156

* BaggðIÞ; the total amount of traffic in node I ’swireless channel due to traffic aggregation.

* BI ðjÞ; the amount of bandwidth that should bereserved for a certain flow j at node I :

* LIJ ; the bi-directional link traffic between nodes I

and J:

For these computations we make the followingassumptions: the wireless channel is half-duplex andall the nodes have identical data rate and transmissionrange.

2.3.1.1. Bavailable estimation. In order to estimateBavailable for any node I ; we need to calculate the existingtotal channel traffic load BaggðIÞ: There are three typesof traffic that contribute to BaggðIÞ:* Self-traffic BselfðIÞ; total traffic between node I andits neighbors, i.e., the bandwidth consumed by thetraffic transmitted or received by node I :

* Neighborhood traffic BneighborhoodðIÞ; total trafficbetween I ’s neighbors.

* Boundary traffic BboundaryðIÞ; total traffic between I ’sneighbors and nodes that are outside I ’s range,whose connection crosses the boundary of node I ’saccessible range.

So BaggðIÞ can be given as the sum of these three typesof traffic:

BaggðIÞ ¼ BselfðIÞ þ BneighborhoodðIÞ þ BboundaryðIÞ: ð1Þ

Fig. 1 shows a sample scenario of traffic aggregation.Node I has four neighbors (A;B;C and D) and node E

is outside of I ’s range. There is self-traffic between I andnode A which equals to LIA; neighborhood trafficbetween nodes B and C which equals to LBC ; andboundary traffic between nodes D and E which equals toLDE : For the example in Fig. 1, we have

BaggðIÞ ¼ LIA þ LBC þ LDE : ð2aÞ

We observe that by using BaggðIÞ as the existing traffic ofI ; we can implicitly avoid the hidden-node effect

between I ;D and E: Since in some cases the neighbor-hood traffic and boundary traffic can transmit at thesame time without interference (e.g., LBC and LDE inFig. 1), BaggðIÞ imposes a tight upper bound of theexisting traffic in I ’s channel.However, node I cannot directly measure its neigh-

borhood traffic BneighborhoodðIÞ and boundary trafficBboundaryðIÞ: For example the boundary traffic in Fig. 1,LDE ; may be underestimated if node I listens to thechannel. Fortunately, the following observations can bemade:

BselfðIÞ ¼ BselfðAÞ ¼ LAI ; BselfðBÞ ¼ BselfðCÞ ¼ LBC ;

BselfðDÞ ¼ LDE ; ð2bÞX

JANðIÞBselfðJÞ ¼BselfðAÞ þ BselfðBÞ þ BselfðCÞ

þ BselfðDÞ ¼ BaggðIÞ þ LBC : ð2cÞ

Thus, we denote B0aggðIÞ the estimated value of BaggðIÞ;

given as the sum of I ’s neighbors’ self-traffic:

B0aggðIÞ ¼

XJANðIÞ

BselfðJÞ; ð3Þ

for all nodes J in the neighborhood of node I : Ingeneral, BselfðIÞ can be given by the total reservedbandwidth of all the existing flows at node I :

BselfðIÞ ¼X

k

BIðkÞ: ð4Þ

From (1), (2) and (3) we have

B0aggðIÞ ¼ BaggðIÞ þ BneighborhoodðIÞ: ð5Þ

We observe that B0aggðIÞ overestimates BaggðIÞ by the

amount of the neighborhood traffic, which equals toLBC in the example. Thus, B0

aggðIÞ imposes a stringentbandwidth admission control threshold, which is adap-tive to the amount of the neighborhood traffic. Giventhe maximum transmission bandwidth B; the availablebandwidth at node I can be given by

BavailableðIÞ ¼ B �X

JANðIÞBselfðJÞ: ð6Þ

We observe that BavailableðIÞ is the adaptive lower boundof the real available bandwidth. The tightness of thebound is proportional to the existing neighborhoodtraffic and boundary traffic, i.e., the more interferencetraffic in the channel the more conservative theestimation will be. To keep the freshness of Bavailable ateach node, each node I includes its current total reservedbandwidth BselfðIÞ in the periodic Hello message whichare received by its neighbors.

2.3.1.2. Bconsumed estimation. As shown in Fig. 2, thedashed arrows stand for a possible path for therequesting flow j: Given the requested bandwidth Bmin;Fig. 1. Traffic aggregations of existing flows.

Q. Xue, A. Ganz / J. Parallel Distrib. Comput. 63 (2003) 154–165 157

the bandwidth to be reserved for the flow at any node I ;BI ðjÞ; is given by

BI ðjÞ ¼Bmin if source or destination;

2Bmin else:

(ð7Þ

Since the intermediate nodes need to receive andforward flow j:However, BI ðjÞ only stands for the additional self-

traffic the requesting flow brings to node I : Therequesting flow may also add additional boundarytraffic to node I ; e.g., LAB and LCD shown by thedashed arrows that cross node I ’s access range in Fig. 2.Due to traffic aggregation, we must include both thenew self-traffic and new boundary traffic introduced bythe requesting flow in computing BconsumedðI ; jÞ: Thus,we observe in Fig. 2 that

BconsumedðI ; jÞ ¼ LAB þ LBI þ LIC þ LCD

¼ BBðjÞ þ BCðjÞ: ð8ÞIn general terms we can call node B as the uplinkneighbor of node I ; uplink(I), and node C is thedownlink neighbor of node I ; downlink(I). Using thesedefinitions we obtain

BconsumedðI ; jÞ ¼ BuplinkðIÞðjÞ þ BdownlinkðIÞðjÞ; ð9Þwhere BuplinkðIÞðjÞ and BdownlinkðIÞðjÞ can either equal toBmin or 2Bmin as shown in Eq. (7).From the above analysis, we observe that

BconsumedðI ; jÞ varies along the path, depending on theposition of node I in the path. Because of the pipelineeffect, the boundary traffic can transmit at the same timewithout interference since they are two hops away fromeach other, e.g., LAB and LCD (see Fig. 2) can be activeat the same time. Thus BconsumedðI ; jÞ puts an upperbound on the actual consumed bandwidth at inter-mediate nodes along the path, which are most seriouslyeffected by traffic interference. By comparing the valueof BavailableðIÞ andBconsumedðI ; jÞ; each node can nowdecide whether to accept the flow or not.

2.3.2. End-to-end delay control

Due to the unsynchronized nature of MANETs, it isdifficult to directly measure the one way end-to-end

delay. In AQOR, we estimate the one way end-to-enddelay by the round trip delay Tround; the delay from thesource to the destination and back to the source. Inother words, we check that Troundp2Tmax and assumethat this implies that the downstream delayTdownpTmax:In the remainder of this subsection we prove that our

method is quite accurate in radio networks by showingthat the one way downstream delay from the source todestination, denoted by Tdown; is approximately thesame as the upstream delay from the destination to thesource, denoted by Tup: We observe that Tdown and Tuphave the following three basic components:

(1) TqueueðIÞ; the queueing delay at each relaying nodeI : (Since each wireless node has only one outputqueue, the average queueing delay for either down-link or uplink is the same.)

(2) TtransðIÞ; the packet transmission time at node I ;i.e., service time. (Since we assume each node hasthe same data rate, given that the packet sizes ofroute request and reply are almost the same, thetransmission time for each direction is the same.)

(3) Tprop; the end-to-end packet propagation delay(Since we assume a symmetric channel, the propa-gation delay on the downlink is the same as that onthe uplink.)

As shown in the example presented in Fig. 3, S

transmits to D via intermediate nodes A;B and C: Tdownand Tup for this case are given by

Tdown ¼X

I

½TqueueðIÞ þ TtransðIÞ

þ Tprop ðI ¼ S;A;B;CÞ; ð10Þ

Tup ¼X

I

½TqueueðIÞ þ TtransðIÞ

þ Tprop ðI ¼ D;C;B;AÞ: ð11Þ

So the difference Tdiff between Tdown and Tup is given by

Tdiff ¼ Tdown � Tup ¼ TqueueðSÞ � TqueueðDÞ: ð12Þ

Fig. 2. Traffic aggregation of requesting flow.

Q. Xue, A. Ganz / J. Parallel Distrib. Comput. 63 (2003) 154–165158

Using the computations above we obtain

Tround ¼ Tdown þ Tup ¼ 2Tdown � Tdiff ; ð13Þ

Tdown ¼ ðTround þ TdiffÞ=2: ð14Þ

For each route discovered, we want to guaranteeTdownpTmax; which implies

Tround þ Tdiffp2Tmax: ð15Þ

Since we estimate the end-to-end delay Tdown of eachcandidate route by half of the round trip delay Tround;which we can measure. The error probability Pe can beroughly given as

Pe ¼ P½2Tmax � TdiffpTroundjTroundp2Tmax¼ Tdiff=2Tmax: ð16Þ

Because Tdiff is a small value relative to Tmax; Pe is verysmall. Moreover, Tdiff is only a function of the queueingdelay at the source and the destination, which areindependent of any specific candidate route. From (13)we observe that the route with the minimum round tripdelay Tround implies the minimum Tdown (and minimumTup) among all the candidate routes discovered.During the route discovery phase we may find

multiple candidate routes, each with a different roundtrip delay. Since the end-to-end delay of the route ismore sensitive to violations, we choose the route onwhich the first in-time reply arrives at the source. If noreply arrives within 2Tmax; it indicates that the routediscovery phase has failed. In such case the source mayback-off and initiate a route rediscovery procedure lateror turn down the flow.

2.4. Bandwidth reservation

As discussed in Section 2.3.2, the route with theminimum round trip delay implies the minimum Tdownand Tup; respectively, among all the discovered candi-date routes. So, upon receiving the first in-time replypacket, the source S will send out the data packet of theflow along the route from which the reply arrives. Thus,we choose the best route available in terms of smallestend-to-end delay with bandwidth guarantee. To guar-antee the availability of the resources to the requestingflow, reservations are made at each node along the routediscovered. In AQOR, the bandwidth reservation will beactivated for the flow only when the real data flowarrives at the registered node.However, the routes of the reserved flows are subject

to QoS violations due to the channel behavior, mobility

of the nodes or even power failure. Thus efficientresource release mechanisms are needed to free thereserved resources at each node when the existingreserved routes are no longer used. In AQOR, this isdone automatically by the use of temporary reservation,i.e., the bandwidth reserved for each flow at theforwarding node is only effective for a certain periodof time. If the node does not receive subsequent datapacket of a reserved flow during the time period Tinterval;the reservation becomes invalid automatically. Theduration of Tinterval can be given by the flow upon routediscovery, as the maximum inter-packet arrival time ofthe flow. By setting the reservation period, AQOR putan upper bound on the burstiness, variance of the end-to-end delay, of the flows.The default value of Tinterval is a function of the

minimum bandwidth requirement Bmin of the flow, themaximum data packet size N supported by the physicallayer (e.g. N ¼ 4095 byte in IEEE 802.11a [2]) and theallowed packet loss k; given by

Tinterval ¼ ðk � N � 8Þ=Bmin: ð17Þ

By using temporary reservation, we eliminate the needfor explicit resource release upon route changes, whichcould be frequent in mobile networks. As we will see inthe next section, temporary reservation also helps toinstantly detect possible route breaks of the reservedflow. For applications with long silent suspensionsession in the flow, light-weighted dummy data packetsshould be sent in order to keep the reservation validalong the route.

2.5. Adaptive route recovery

Because of the changing topology due to nodes’mobility and the shared unreliable physical medium,communication in MANET usually disconnects andexperiences channel deterioration. For multimediaapplications in MANET, instant QoS violation detec-tion and recovery mechanisms become crucial.

2.5.1. QoS violation detection

End-to-end QoS violations are caused either by end-to-end delay violation due to channel deterioration orcongestion along the existing route or by route breaksdue to node mobility or power failure.

2.5.1.1. Delay violation detection. So far, we have onlymeasured, in route discovery procedure, the round tripdelay Tround: However, to provide instant route recov-ery, we need to monitor the one way delay of the existing

Fig. 3. Round trip delay.

Q. Xue, A. Ganz / J. Parallel Distrib. Comput. 63 (2003) 154–165 159

data flow as well as the control packets. In order toestimate Tdown and Tup; respectively, we define:

* TS; the generation time of the request packet at thesource.

* TD; the generation time of reply packet at thedestination, which is also the arrival time of requestpacket.

* TS ARVL; the arrival time of the reply packet at thesource.

* Toffset; the estimated time offset between the systemclocks of source and the destination.

Assuming Tdown ¼ Tup ¼ Tround=2 as discussed inSection 2.3.2, we have

Tup ¼ Tround=2 ¼ ðTS ARVL þ ToffsetÞ � TD; ð18Þ

Tdown ¼ TD � TS � Toffset: ð19Þ

So Toffset is given by

Toffset ¼ Tround=2� ðTS ARVL � TDÞ; ð20Þ

where Tround; TS ARVL and TD are known at the sourceduring route discovery.Now we can measure Tdown and Tup by using Toffset;

the time stamps on each packet at the sender, and thearrival time at the receiver. Thus, the end-to-end delayviolation can be easily detected at the destination bymonitoring the delay of the arriving data packets. If thedestination receives n consecutive data packets whosedelay exceeds the maximum delay requirement Tmax; theQoS recovery will be triggered.

2.5.1.2. Route break detection. The common approachfor route break detection used in most of existing ad hocrouting protocols is by neighbor lost detection [12], i.e.,the hello message from a lost node does not arrive to itsneighbor in time. When neighbor lost is detected, a routebreak message is sent to the source notifying about thebreak. Then the source initiates the reroute process.However route break detection by neighbor lostnormally takes several seconds, which is not desirableto time sensitive real-time flows requiring QoS. Inaddition, the rerouting process may cause excessivecontrol overhead.In our approach, we utilize the bandwidth reservation

timeout at the destination to signal possible route breaksinstantly. If the destination fails to receive data packetsof a reserved flow before its reservation timeout, routerecovery will be triggered at the destination. Using thismethod, the route break detection time is implicitlyupper bounded by Tinterval: In addition, we can detectboth types of QoS violations at the same spot andhandle them identically.In addition, the basic neighbor lost detection is also

used for best effort traffic and in case the route updateof instant recovery cannot reach the source because ofnetwork partition or packet loss. In such case, when a

node I detects that the downlink node on a reservedroute is lost, it will send a route error packet, with itscurrent route sequence number, to the correspondinguplink node along the route. The route error packet isthen forwarded upwards to the source to indicate theoccurrence of the route break. As a consequence, thereserved bandwidth of the flow will be released atthe forwarding nodes. The route error packet has thehighest priority in the network, in order to facilitateinstant violation detection.

2.5.2. QoS violation recovery

To provide instant route adaptivity, AQOR adoptsdestination-initiated route recovery. After the QoSviolations are detected, the destination will increase itsroute sequence number and broadcast an unsolicitedroute reply packet, also called route update, back to thesource. The route update is treated in the same manneras a route request packet with admission control andloop prevention mechanism from destination to source.Since it analogs route exploration but in the reversedirection, we call it reverse exploration. To reduce theoverhead of the route update propagation, the locationor hop count information can be used.Upon receiving the first in-time route update packet

with appropriate route sequence number, the sourceswitches the flow in question to the reverse route onwhich the update arrives. By this means the flow isautomatically adjusted without the notice of the higherlayer applications, avoiding the cumbersome tear-downand re-establishment processes. The accuracy of end-to-end delay measurement in reverse exploration isguaranteed by the discussions in Section 2.3.2.On the other hand, a late route update packet or a

route error packet, with a valid route sequence, signalsthe occurrence of QoS violation and the failure of routerecovery. In such case, the source can either decide tocontinue transmitting the flow with the absence of QoSguarantee or suspend the flow and try later.

3. Performance analysis

To verify AQOR’s performance under different net-work traffic and mobility, we have developed a detailedsimulation model based on OPNET Modeler [19]. Wehad the following objectives for our simulation:

(1) To validate that AQOR can provide QoS supportas requested by the real-time flows.

(2) To show that AQOR’s route establishment is quickand reliable.

(3) To show that AQOR reacts swiftly to QoSviolations due to channel degradation and routebreak.

(4) To justify the efficiency of AQOR under large-scalenetworks with multiple QoS flows.

Q. Xue, A. Ganz / J. Parallel Distrib. Comput. 63 (2003) 154–165160

3.1. Simulation model

Our AQOR routing model is built on top of the IEEE802.11 DCF MAC model provided by OPNET.Modifications are made to the original MAC model tosupport multi-hop wireless connection. By default, eachnode has the same transmission range of 250m and rawdata rate of 2Mb/s, with a MAC layer FIFO transmis-sion queue of 64 packets at maximum.In the AQOR routing model, a send buffer of 64

packets is implemented to buffer all data packetswaiting for a route, e.g., packets for which routediscovery has started but no reply has arrived yet. Toprevent buffering of packets indefinitely, upon discoveryfailure the data packets in the buffer are flushed. Themaximum packet size used in the temporary bandwidthreservation is set to 1024 bytes. Upon route discoveryfailure, the node will initiate rediscovery after a back-offperiod, which exponentially increases from 2Tmax to64Tmax:We have implemented a random way point mobility

model [5] at each node. If enabled, each node will movetoward a random destination within the field at aspecified speed. After reaching the destination, the nodewill stay there for a predefined period of time then startmoving again. The general motion of a particular nodeis simulated through a set of discrete small step intervals.A node in motion updates its position every fixed periodof time. In our simulations, the length of each step wasset to a value of 2m.

3.2. Study of QoS recovery

In this subsection we investigate the recovery time dueto route breaks that occur due to node’s mobility. Inorder to provide a clear exposition of the simulationresults we implemented a small network with five nodesand one flow (Fig. 4). All the nodes are stationary exceptthe Mobile node moving upward at the speed of 10m/s

from the beginning of the simulation. There is a real-time flow transmitting from the node Source to thenode Destination, requesting Tmax of 0.1 s and Bmin of400Kb/s. The simulation duration is 120 s.The throughput and delay plots are shown in Fig. 5.

We observe from the top two plots shown in Fig. 5 thatinitially the throughputs of the Mobile and Destinationnodes are identical, indicating that flow was establishedon the upper path: Source-Mobile-Destination. Atapproximately 15 s after the start of the simulation, theMobile node assumes position (600, 350), which isoutside the range of the source, resulting in route breakand therefore no throughput at the Mobile nodeafterwards. Since no data packet is forwarded to theDestination after the route breaks, bandwidth reserva-tion at the destination times out at T1 shortly after theroute breaks. Then, the recovery procedure is triggeredat the Destination (see the bottom plot in Fig. 5) bysending back update packets to the Source. Afterreceiving the route update, the Source switches the flowto the lower route: Source-Lower node1-Low-er node2-Destination. As shown in Fig. 5, shortlyafter time T1; the throughput at the Destination isidentical to the throughput of the Lower node2 shownin the third plot.Throughout the session, the Destination is monitoring

the end-to-end delay of the arriving data packet. At timeinstant T2; the Destination detects that the delays ofdata packets exceed the threshold Tmax (0.1 s). QoSviolation occurs due to channel deterioration. Thenroute recovery is triggered again. Fortunately, thechannel deterioration is temporary and the end-to-enddelay of the route drops below Tmax after recovery. Therecovery procedures are triggered at time instants T3and T4 due to channel deterioration, following thesimilar behavior to the recovery procedure that occurredat time T2: From the above result, we observe thatAQOR react swiftly to route break and end-to-end delayviolations.

Fig. 4. QoS recovery scenario.

Q. Xue, A. Ganz / J. Parallel Distrib. Comput. 63 (2003) 154–165 161

3.3. Study of large network performance

In this section we investigate AQOR’s performancefor large networks, with different nodes’ speeds andmultiple traffic flows.

3.3.1. Network configuration

To simulate stream media applications we useconstant bit-rate (CBR) traffic sources with fixed datapackets of 512 bytes and sending rate of 10 packetsper second. All the flows have the same requiredbandwidth Bmin of 40Kb/s and end-to-end delay boundTmax of 0.1 s. The source–destination pairs of the flowsare distributed randomly among the 50 nodes in thenetwork.In most of the existing simulation measurements [5,8],

the narrow rectangle field of 1500m� 300m is com-monly used to yield enough hops from source todestination. However, with node’s transmission rangeof 250m, such kind of space area dictates that most ofthe movement will take place in the y-axis. In oursimulation, we chose a 1000m� 500m rectangle field,which provides enough space diversity and the oppor-tunity of alternate routes. To maintain enough routelength, the access range of each node is reduced to

200m. The nodes’ mobility is determined by therandom-way-point model with pause time set to 0.We test eight scenarios with different maximum

nodes’ speeds of 0, 2, 5 or 10m/s for both 10 and 15flows. For each scenario we run the simulation for2400 s.

3.3.2. Performance metrics

So far, no benchmark metrics have been defined forevaluating performance of QoS routing protocols inMANETs. In our simulation, we have measured thefollowing five key performance metrics:

(i) Traffic admission ratio, ratio between the numberof data packets sent to the network from thesources and the number of data packets generatedat the sources. This metric shows the effect of theadmission control policy.

(ii) End-to-end delivery ratio, ratio between the numberof data packets received at the destinations and thenumber of data packets sent from the sources. Thismetric indicates the reliability of the admittedflows.

(iii) Average end-to-end delay, the latency incurred bythe packets between their generation time and their

Fig. 5. Throughput and delay plots.

Q. Xue, A. Ganz / J. Parallel Distrib. Comput. 63 (2003) 154–165162

arrival time at the destination. This metric indi-cates the performance of the admitted flows.

(iv) Ratio of late packet, ratio between the number oflate data packets and the number of packets thatarrive at the destination. This metric indicates theperformance of the admitted flows.

(v) Normalized control overhead, the ratio between thenumber of routing packets ‘‘transmitted’’ hop-wiseand the number of data packets ‘‘delivered’’ at thedestination. The Hello packets are not included inthe calculation because it is almost static band-width consumption.

3.3.3. Results analysis

Figs. 6 and 7 plot the traffic admission ratio and theend-to-end delivery ratio of admitted load versus the

node mobility, with their standard deviation (SD). Forthe stationary scenario with 10 flows, all the traffic isadmitted and about 99.7% of the traffic is successfullydelivered to the destination. With the increased trafficload of 15 flows, only about 75% of the traffic isadmitted and about 96.4% of the traffic is successfullydelivered to the destination.We notice that with increased mobility, the end-to-

end delivery ability of the network decreases gracefullyaccompanied by reduced traffic admission ratio. Withhigh movement speed of 10m/s, the traffic admissionratio of AQOR reduces to about 86% or 59% underloads of 10 and 15 flows, respectively. The delivery ratioof the admitted traffic is still above 98% or 96%, underloads of 10 and 15 flows, respectively. The plots provethat AQOR provides reliable delivery to the admittedflows, and the admission control policy of AQOR isefficient and correct.Fig. 8 shows the ratio of late packets received at the

destination under different node speeds and differentflows. We notice that the ratio of late packet in all 10flows scenarios, in Fig. 8(a), is below 0.14%. Theminimum value occurs under node speeds of 5 and10m/s, while the peak of the curve occurs at node speedof 2m/s. The reason can be found in Fig. 6. With trafficadmission ratio of about 99%, at nodes’ speeds of 2m/salmost all the traffic generated is sent to the network,similar to the stationary scenario. However, because ofthe nodes’ mobility, the probability of collisions androute break increases. Thus both the late packet ratioand its SD increase. However, as for the case of nodespeeds of 5 and 10m/s, the total traffic admission ratio isreduced by 10% or more than the stationary scenario asshown in Fig. 6. Thus the collision probability reduceswith the reduced total traffic load in the network,resulting in a lower late packet ratio.As shown in Fig. 8(b), the ratio of late packet for

scenarios with 15 flows are about 10 times higher thanthat of the 10 flows, varying between 1% and 1.8%.With the increased node mobility, the ratio of latepackets decreases slightly because of the reducedadmitted traffic load. Both plots show that the trafficload has more influence on AQOR’s performance thannode’s speed.Fig. 9 shows the average end-to-end delay versus node

mobility. The 10 flows plot is consistent with our priorobservations, i.e., the average end-to-end delay for thetwo high mobility scenarios are smaller than that ofthe low mobility ones because there is less traffic in thenetwork. In the 15 flows’ plot, the scenario of nodes’speeds of 2m/s achieves smallest average end-to-enddelay. The reason can be found in Fig. 6. With trafficadmission ratio of about 61%, at nodes’ speeds of2m/s there is only about 80% of the network traffic as inthe stationary scenario while almost the same to thenodes’ speeds of 5 or 10m/s. With the greatly reduced

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Fig. 7. End-to-end delivery ratio versus node mobility.

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network traffic and relative low mobility, the traffic innodes’ speeds of 2m/s experiences smallest averagedelay.In all scenarios, the average end-to-end delay is below

0.04 s which is much lower than the requested bound of0.1 s. Together with the high end-to-end delivery ratio ofabove 96% shown in Fig. 7, the simulation results showthat AQOR can provide reliable QoS support for real-time flows under large mobile networks.Fig. 10 shows AQOR’ normalized control overhead

versus nodes’ mobility. AQOR’s normalized overheadfor 10 flows under stationary scenario is quite low withmean of 6%. For the 15 flows scenarios shown by thedashed line, the normalized routing overheads arearound 35%. Because of the greatly reduced networktraffic under nodes’ speeds of 2m/s, there are fewer flowsto maintain. Thus the normalized overhead does notincrease when compared to the stationary scenario.

4. Conclusions

In this paper we have introduced Ad hoc Qos On-demand Routing (AQOR) protocol that provides per-flow end-to-end QoS support in MANETs in terms ofbandwidth and end-to-end delay. The performance andaccuracy of AQOR is studied by extensive simulationsusing OPNET Modeler. We defined the followingperformance metrics for QoS support in MANETs:traffic admission ratio, end-to-end delivery ratio, aver-age end-to-end delay, ratio of late packet and normal-ized control overhead. Using these metrics in theOPNET simulator we conclude that AQOR cansuccessfully provide sustainable QoS support to multi-media applications. It can recover swiftly from routebreaks and channel deterioration, minimizing theireffect on QoS flows. Because of its instant QoS violationdetection and recovery mechanisms, AQOR scales well

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Fig. 8. (a) Ratio of late packets versus node mobility for 10 flows; (b) ratio of late packets versus node mobility for 15 flows.

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Fig. 9. Average end-to-end delay versus node mobility.

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Fig. 10. Normalized control overhead versus node mobility.

Q. Xue, A. Ganz / J. Parallel Distrib. Comput. 63 (2003) 154–165164

with node mobility up to 10m/s with no significantperformance degradation. In large mobile networks,AQOR dynamically adjusts its admission policy withthe offered load and node mobility while keeping thedelivery ratio of the admitted flow stable at above 95%.The results justify that AQOR’s traffic measurementsand admission decisions are accurate and provide highchannel utilization.

Acknowledgments

This work was supported in part by NSF-0087945,NSF-9812589 and NSF-0080119.

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Qi Xue received the M.S. in Electrical and Information Engineering

from Huazhong University of Science and Technology, China, in 2000.

He is currently a Ph.D. candidate in department of Electrical and

Computer Engineering, University of Massachusetts at Amherst. His

research interests include mobile communication and wireless net-

works.

Aura Ganz is the Director of the Multimedia Networks Laboratory at

the ECE Department, University of Massachusetts at Amherst. She

has experience in topics related to all strata of networking technology,

from work related to topics in the network infrastructure development

to advanced user-space application development for mobile clients.

The research results are validated by a combination of analytical,

simulation and prototyping tools. Dr. Ganz has authored over 120

peer reviewed publications in these subject areas. She has received her

B.Sc., M.Sc. and Ph.D. in Computer Science from the Technion in

Israel.

Q. Xue, A. Ganz / J. Parallel Distrib. Comput. 63 (2003) 154–165 165