Quality of Service Framework in MANETsUsing Differentiated Services

Venus S. Y. To, Brahim Bensaou and Sammy M. K. ChauComputer Science Department, Hong Kong University of Science and Technology

Clear Water Bay, Kowloon, Hong Kong, PRC.E-mail: {venus,brahim,cssammy}@cs.ust.hk

Abstract— Providing Quality of Service (QoS) in mobile ad-hoc networks (MANETs) requires a close collaboration betweenall layers in the protocol stack. To complement other protocolswe designed for medium access control, bandwidth sharing andscheduling and QoS routing, we propose here a framework andprotocols to support QoS on a per class basis that fit withinthe Differentiated Services principle. Our proposed scheme relieson bandwidth provisioning, scheduling and queue qualitativebehavior prediction to provide differentiation between two servicelevels – viz. Expedited forwarding and Best effort – and cope withmobility MAC layer contingencies.

I. INTRODUCTION

Because of the rising popularity of multimedia applicationsin the commercial environment and the ever growing require-ments of mission-critical applications in the military arena,quality of service (QoS) support in Mobile Ad Hoc Networks(MANETs) has become an important area of research. In orderto provide QoS, traditional wired and wireless infrastructurenetworks reply on the availability of a good infrastructure:links are stable and fail only due to major disasters or dueto malicious attacks, routers have enough processing capacityto maintain QoS, and most importantly bandwidth is virtuallyunlimited - if a link’s capacity become frequently congestedindicating an increase in the long term demand for bandwidth,the bandwidth can be increased physically. Therefore, QoS hastraditionally been supported by deploying three major prin-ciples: traffic admission control to ensure that the aggregateamount of traffic in the network does not statistically (i.e.,in long term average or call time scale) exceed the networkcapacity to provide QoS; QoS-routing to find end-to-end pathsthat are capable of maintaining the requested guarantees;and finally bandwidth provisioning and traffic scheduling toascertain that bandwidth sharing among many flows does notimpede the guarantee of QoS in a short-time scale, such aspacket level).

In MANETs, it is very difficult to provide QoS as thelinks are established and torn down dynamically. Due to thewireless nature of ad-hoc networks, the bandwidth of a givenlink between two nodes is variable in different time scales:because of channel errors but also and mainly because ofthe dynamic nature of ad-hoc networks and the contentionsthat occur between nodes for the limited wireless bandwidth.As a consequence, firstly, admission control as known inclassic networks is obsoleted by the dynamic nature of linkbandwidth: admitting a flow that creates a new link between

two nodes not only reduces the available bandwidth of thelink by the bandwidth requested by the flow, but, and mostimportantly, it may also reduce the capacity of other existinglinks in the vicinity since links share specially the limitedphysical bandwidth. Secondly, due to distributed nature ofthe control and mobility, it is very difficult to perform anyscheduling in MANETs.

Providing QoS in ad-hoc networks requires therefore a closecollaboration between all layers in the protocol stack. Theproposed framework is one among the many such protocolsthat make up the stack designed to provide QoS in MANETs.In a nutshell, at the lowermost layer, namely the MAC layer,a modified backoff algorithm [5] is used along with thestandard IEEE 802.11 protocol to provide statistical fair accessto the physical link according to preset fair shares, whichrepresent the bandwidth share that each link should obtain.Due to contention between links in the wireless environment,we opted for the max-min sharing principle as a means ofdetermining the nominal share of a link given the competitionit faces. This is useful to deploy efficient admission control ofboth flows and links (i.e., determine whether a link can be ac-cepted or not). A distributed max-min fair share approximationalgorithm [6] provides an accurate estimate of the bandwidthshare of each link in the network. This algorithm relies onknowledge of local topology information, which is fulfilled bythe so-called flow information dissemination protocol (FloID).Within this environment Quality of Service Ad-hoc Routing(QuaSAR) [4] is a distributed QoS routing protocol, whosegoal is to search for and admit with the least amount of routingoverhead, end-to-end least cost shortest network paths thatsatisfy a flow establishment request with a given bandwidthrequirement.

In this context, the present paper proposes a QoS frameworkfor mobile ad hoc networks. The goal of the framework isto provide per-class service differentiation that is similar toDifferentiated Service on the Internet. This paper is organizedas follows. Section II gives a brief overview of related work.Section III describes the framework architecture: admissioncontrol, service differentiation and resources release, respec-tively. Section IV presents the performance evaluation usingthe ns-2 simulator. Section V concludes the paper.

II. RELATED WORK

In this section, we present a brief survey of major (note-worthy) work done in the ad hoc QoS frameworks area.

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INSIGNIA [8] is an IP-based quality of service frameworkthat supports the delivery of adaptive services in MANETs.The framework tries to duplicate RSVP approach in MANETswithout the signalling overhead. It therefore proposes anin-band signaling protocol and uses a soft-states resourcemanagement approach. Since INSIGNIA is based on per flowguarantees, it can face a scalability problem like IntServ [3]model on the Internet.

In [12], the so-called Flexible QoS Model for MANETs(FQMM) was proposed. FQMM combines the per-flow granu-larity of IntServ and per-class granularity of DiffServ. FQMMsuggests simply that the highest priority class gets per-flowprovisioning, while lower priority classes get per-class provi-sioning, so the model adds the complexity of the two schemesin one which requires a node to switch back and forth betweenthe protocols of IntServ and DiffServ. Since FQMM definesthe source node as the Ingress node which is responsiblefor marking and conditioning packets, so that the subsequentnodes can process them accordingly. As such misbehavior bythe source nodes goes undetected in FQMM.

Service Differentiation in Stateless Wireless Ad Hoc Net-works (SWAN) [1] is a stateless network model which usesdistributed control algorithms to deliver service differentia-tion in mobile wireless ad hoc networks. SWAN uses ratecontrol for UDP and TCP best effort traffic, and sender-based admission control for UDP real time traffic. SWAN usesexplicit congestion notification (ECN) to dynamically regulateadmitted real time traffic in face of network dynamics.

A cross-layer quality of service model [10] is proposed re-cently. It separates metrics at different layers (i.e., applicationlayer metrics, network layer metrics and MAC layer metrics)and maps them accordingly. At the network layer, nodes’power state, buffer state and stability state are recommendedto characterize the quality of network. At the MAC layer, thelink signal-to-interference plus noise power ratio is used asthe MAC layer metrics.

III. FRAMEWORK ARCHITECTURE

The Ad Hoc DiffServ Framework provides QoS based onthe Internet Differentiated Services model [2]. The servicedomains in this framework are specially re-defined by con-sidering the characteristics of MANETs. The source nodeserves as a special flow-based domain which contains onlyitself. All the other nodes (including the destination) alonga traffic path form a DiffServ domain (relative to the sourcenode). The first downstream node from the sender acts as theIngress node which is responsible of fulfilling tasks such asclassifying and possibly conditioning traffic from the source toensure that packets which transit the domain are appropriatelymarked to select a supported per-hop behavior (PHB). Inthis framework we support two PHBs, Best Effort (BE) andExpedited Forwarding (EF). The domains of different flowscan overlap.

A. Per-flow Admission Control with Per-class State

Admission control is done together with route discoveryby QuaSAR, both of them are flow based and placed with a

request-reply mechanism. A route request message carries theservice level and bandwidth request in addition to the flowid triple. Only the EF service needs admission control andresource reservation in this framework. Best effort requestscan be accepted without admission control, they just requireroute discovery.

A node receiving the EF request performs its admissioncontrol on the upstream link. It works with QuaSAR, anduses the max-min algorithm to estimate the fair share of eachlink in the vicinity. Each node not only ensures that there isenough available for the new flow but also the service levels ofadmitted traffic are not deteriorated by the new flow [4]. Dueto node mobility, intermediate nodes may need to maintainEF traffic in excess of the resources reserved. To address thisissue, (similar to Internet DiffServ) only a small fraction of theavailable fair share of a link is reserved for EF traffic. Besides,in order to cope with mobility and MAC layer short termcontingencies, the fair share of the links are assigned only toa fraction of the bandwidth. The remaining bandwidth is usedas a backup bandwidth in case of sudden mobility. ThereforeEF traffic that requests admission beyond the defined fractionis rejected.

In addition to assured bandwidth, EF PHB requires lowlatency. Therefore, the EF queue length and thus the queue-ing delay and delay deviation at all intermediate nodes areconsidered when admitting a new flow. To do this, the EFqueue length is sampled when a new EF packet arrives orscaled during idle time. The queue length is estimated byexponential averaging. The queueing delay is estimated fromthe exponential average of the queue length:

Delayt = (1−wd)Delayt−1+wd×AvgEFQueueLent

FairBandwidtht

(1)

The fraction AvgEFQueueLent/FairBandwidtht rep-resents the current delay and is averaged with the previousaverage delay in (1). The delay deviation is also calculatedusing:

SERRt =AvgEFQueueLent

FairBandwidtht

−Delayt−1 (2)

Deviationt = (1− γ)×Deviationt−1 + γ × |SERRt| (3)

With these two parameters, during admission control, if theestimated delay and the delay deviation are smaller than somesmall constants, the request is accepted, otherwise, the routerequest packet is discarded.

A flow is admitted as EF if it satisfies both of the followingconditions;

1) There is enough bandwidth to support the flow andadmission of this new flow will not violate the servicelevel of other admitted flows.

2) The estimated queueing delay and the delay deviationare small enough.

If the request passes both the bandwidth and delay admis-sion control at all intermediate nodes (hop by hop) and finallyarrives at the destination. The destination sends a route replyto the source. When the route reply arrives at the Ingress

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node (i.e., the first downstream node from the source), it addsan entry to its Policy Table which maintains the flow triple,service level, bandwidth request and the current token bucketstates. Note that like the original DiffServ in the Internet,only the Ingress node is required to maintain this per-flowinformation for this particular source for the purpose of trafficconditioning. All intermediate routers will treat traffic as anaggregate and network resources are reserved on a class basis.

B. Per-class Differentiation

Three important components comprise the DiffServ archi-tecture: the initial classifications and conditioning of trafficentering the network, the assignment of a DiffServ CodePoint (DSCP) value to the DiffServ field in IP header, andsubsequent PHBs that are triggered within the network by theDiffServ field value as the packet passes through the network.

All traffic entering the DiffServ domain in the framework isfiltered through a Multi-field traffic classifier. The Multi-fieldclassifier selects packets based on the DSCP and the explicitcongestion notification (ECN) bits. The ECN bits, which arethe last two bits of the TOS byte in the IP header, are used forend-to-end congestion notification in the Internet, however inMANETs, end-to-end congestion notification is not justifiedas the intermediate routers can move around and the sourceas well around. Therefore the ECN bits are redefined here tobe used by the Ingress node to indicate that the packet haspassed classification, conditioning and marking at the edge ofthe DiffServ domain.

Packets are marked by the source node with a flow identifier‘FlowID’ in the TOS and ‘00’ in the ECN bits. The first‘0’ indicates that it is ECN-incapable, and the second ‘0’indicates that the packet is marked by the source node. Eachnode receiving a packet checks if the incoming packet’s ECNbits are ‘00’, it then knows that it is responsible for mappingthe FlowID to a DSCP and of marking the packet. When anIngress node receives an incoming packet with ‘00’ ECN bits,it looks up its Policy Table, for an entry which was addedwhen a route reply arrived, to retrieve the corresponding trafficprofile. The traffic profile is based on a token bucket, it lookslike: code point = EF; use token-bucket r,b

The above profile indicates that all packets marked with DScode point EF should be measured against a token bucket me-ter with rate r and burst size b. The rate r at which tokens aregenerated determines the long-term average data rate permittedby the token system, it is the requested bandwidth stored in thePolicy Table. The configured depth of token bucket b describesthe permitted variance from the ideal constant rate trafficprofile. Out-of-profile packets are those packets in the trafficstream which arrive when insufficient tokens are available inthe bucket. In-profile packets are mapped to EF and allowed toenter the DS domain without any further conditioning, whileout-of-profile packets that are inferior to EF are mapped to BE.The Ingress node also marks the ECN bits as ‘01’ to indicatethat the packet carrying a DSCP instead of a FlowID.

After undergoing the marking, the packets are put in thecorresponding queues and forwarded to the appropriate down-stream neighbor. Every nodes has two queues per link: Best

Effort and Expedited Forwarding. EF queue has a strict priorityover BE queue and is served as long as it is not empty.Packet forwarding is much simpler than packet marking. Ifa node receives packets with ‘01’ ECN bits, it assumes thatthe packet has been marked and conditioned by the Ingressnode. It forward the packet according to the indicated DSCP,in other words the packet will be enqueued in the appropriatequeue.

Since the EF queue has a strict priority over BE queue, theEF traffic is always transmitted ahead of the BE traffic. Thescheduling algorithm is straightforward. A packet is scheduledfrom the head of the BE queue as long as the EF queueis empty. The associated discard algorithm is preemptive, itattempts to discard a BE packet to make space to queue anEF packet.

The problem of priority queue is well known. It can causeall traffic at low priority to experience delay or even starve ofresources. To protect the low priority (BE) traffic, admissioncontrol is associated for high priority (EF) traffic, whichensures that the amount of EF traffic admitted to the networkwill not consume all available network resources.

C. Automatic Resources Release

Some signalling protocols release the reserved resources by‘tear-off’ message or use soft states, i.e., wait until the reserva-tion expires and release resources then. Both of these methodsdo not work in this framework. First, there may be changesin the topology in MANETs such that some intermediatenodes can not be reached by the ‘tear-off’ message. Secondly,soft-state reservation does not work as network resources arereserved on a class-basis by this framework therefore a nodedoe not know how much resources to release.

An automatic resources release mechanism is thus pro-posed in this framework. Nodes estimate their own EF queuelength and queueing delay permanently through a movingaverage mechanism. By checking the so-called moving averagecrossover, the trend of the queue can be predicted: if the short-term average queue delay is larger than the long-term one, thequeue is considered to be in a growing trend; while in theopposite situation, the queue is considered to be shrinking.A shrinking queue means that the reserved resources are notfully utilized and some resources should be released. Howeverthe amount of bandwidth released is critical. If too muchbandwidth is released, there may not be enough bandwidthfor the EF traffic and it may cause drops of EF packets or lowdelays. Therefore, resources should be released slowly.

To release resources, we first estimate the amount of unusedbut reserved bandwidth, then a small fraction of this resourcesare released at one time as:

Release← σ×(ReservedBandwidth−BandwidthUsage)(4)

where ReservedBandwidth is amount of reserved band-width, BandwidthUsage is the amount of used bandwidth,sigma is a constant smaller than 1, Release is a portion of un-used bandwidth. Equation(4) is triggered when the short-termaverage delay becomes smaller than the long-term one (i.e., at

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the cross over point). The unused but reserved bandwidth isreleased asynchronously by all active links periodically. Theactual amount of bandwidth released at each link depends onthe number of active links, the latter share a total amount ofRelease. Resources are released whenever a route expires oris being repaired or a broken link is detected. Under these threeconditions, the resources are released to a single indicated link.

D. Inter-node Differentiation

Differentiating packets by their DSCP and putting themin queues with different priorities can be viewed as ‘intra-node differentiation’. Within a node, EF packets are givenpriority by being served. However, ‘intra-node differentiation’is insufficient. Neighboring nodes are competing for the samephysical channel. They try to access the medium by carriersense multiple access. The head-of-line EF packet at a nodecompetes with the head-of-line BE packets at the neighboringnodes. Neither IEEE 802.11 MAC [7] or the modified MACused by the framework [5] give priority to the EF packetin accessing the medium. In this case, an EF packet isblocked by the BE packets in other nodes. To solve thisproblem, ‘inter-node differentiation’ is needed. Normally, adata packet at the MAC waits for distributed coordinationfunction interframe space (DIFS) before being transmitted.With ‘inter-node differentiation’, a EF packet waits for DIFSwhile a BE packet waits for two DIFSs. This is similar tothe forthcoming IEEE 802.11e standard. By making the BEpacket wait longer, the EF packet has a higher probability ofbeing transmitted first.

IV. EVALUATION

The performance of the Ad hoc DiffServ Framework isevaluated by simulation. The simulator used is the NetworkSimulation ns-2 release 9a [9]. The Distributed CoordinationFunction (DCF) of IEEE 802.11 is used as the MAC layerprotocol with the wireless channel having a nominal bit rateof C = 2Mbps 1 and a nominal radio range of 250m. Theinterface queue has a maximum size of 500 packets. Allsource are constant bit rate (CBR) traffic, generating datapackets of 512 bytes. All the nodes start from an initial statuswith an empty buffer. The backoff is modified as indicatedpreviously and all of FloID, the max-min allocation algorithmand QuaSAR are implemented. The proposed framework iscompared to an ‘original system without QoS’, which consistsof best effort routing protocol (AODV [11]) and MAC layerprotocol (IEEE 802.11). We also compare our results to thoseobtained from SWAN. All the simulation results are averagedover ten simulation runs.

Fig.1 shows a topology with broken link. The simulationlasts for 350.0 seconds. There are ten nodes aligned in twostrings. There are three flows, one from node 0 to 4, the othersfrom node 5 to 9 (Table I). Node 7 goes down at 200.0 seconds.Node 6 then detects the broken link and initiates a route repairfor the two EF flows. The route repair packet is forwarded

1Note that although the bit rate of 11Mbps is the current standard, 2Mbps

is used as it is the stable parameter under ns-2 release 9a

� � � � �

� � � �

����

����

Fig. 1. Topology with broken link

service traffic source destinationEF(video) UDP 30Kbps 5 9EF(voice) UDP 5Kbps 5 9BE(FTP) TCP wt pkt 512B 0 4

TABLE ITRAFFIC FLOWS: BROKEN LINK

along the nodes lying on the lower string. It first reaches node1, 2, and then 3. When node 8 receives the repair packet fromnode 3, an alternative QoS supported path is found. Fig.2 to6 show the simulation results in different frameworks.

Both the Ad Hoc DiffServ framework and SWAN guaranteethe EF (real time video and voice) traffic with 99.9% goodput.Without QoS, the EF flows compete with the best effort TCPflow. The former gets only 87.7-88.0% goodput. TCP trafficadapts to the network situation by increasing/decreasing itscongestion window. Thus, the TCP flows in all frameworkshave a goodput above 95%. However, there is a big differencebetween the throughput of the TCP flows in different frame-works. The average throughput of the TCP flows are 151Kbps,79Kbps and 160Kbps in the Ad Hoc DiffServ framework,SWAN and best effort model respectively. SWAN providesguarantee to the real time traffic at a cost of lower TCPthroughput and network utilization.

Both the Ad Hoc DiffServ framework and SWAN guaranteea small delay less than 0.05 seconds for the EF (real time videoand voice) traffic, while in the best effort model, EF trafficexperiences an average delay of 0.2 seconds. The averagedelay of the BE traffic is close to 0.2 seconds in the Ad HocDiffServ framework and the best effort model, while it is aslarge as 1.44 seconds in SWAN. The provision of guaranteedthroughput and delay for EF flows is at a cost of large delaydeviation of BE traffic.

It is shown that the performance of the Ad Hoc DiffServframework is comparable to that of SWAN. The Ad HocDiffServ framework provides a similar level of guarantee asSWAN to real time traffic with a higher utilization of networkresources.

QoS SWAN Best Effortdelay dev delay dev delay dev

voice 0.041 0.024 0.029 0.006 0.209 0.120video 0.043 0.042 0.019 0.008 0.195 0.110tcp 0.187 2.339 1.442 0.022 0.228 0.071

TABLE IIPACKET DELAY WITH DEVIATION

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V. CONCLUSION

In this paper, a QoS framework for MANETs was proposed.The proposed framework uses the idea of Differentiated Ser-vice on the Internet to provide a class based guarantee toreal time traffic. The DS domain is redefined to meet thecharacteristics of MANETs. The first downstream node fromthe source acts as an Ingress node and is responsible forpolicing and marking the incoming packets. Other nodes thenclassify an incoming packet by its DiffServ code point and pro-vide both ‘intra-’ and ‘inter-node differentiation’. Simulationresults show that the proposed framework together with otherprotocols in the QoS architecture provides both bandwidth anddelay guarantees to real time traffic. The assurance is given notonly in static networks topologies but also in dynamic networktopologies.

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[2] S. Blake, D. L. Black, M. A. Carlson, E. Davies, Z. Wang, and W. Weiss.An Architecture for Differentiated Services, Dec. 1998. RFC 2475.

[3] B. Braden, D. Clark, and S. Shenker. Integrated Services in the InternetArchitecture: an Overview, June 1994. RFC 1633.

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[6] X. L. Huang and B. Bensaou. On Max-min Fairness and Scheduling inWireless Ad-Hoc Networks: Analytical Framework and Implementation.In The second ACM MobiHOC, pages 221–231, Oct. 2001.

[7] IEEE Computer Society LAN MAN Standards Committee, editor. IEEEStandard for Wireless LAN Medium Access Control (MAC) and Phys-ical Layer (PHY) Specifications. IEEE Std 802.11-1997. The Instituteof Electrical and Electronics Engineers, New York, 1997.

[8] S.-B. Lee, G.-S. Ahn, X. Zhang, and A. T. Campbell. INSIGNIA: AnIP-Based Quality of Service Framework for Mobile ad Hoc Networks.Journal of Parallel and Dist. Comput., 60(4):374–406, Apr. 2000.

[9] S. McCanne and S. Floyd. ns—Network Simulator. June 1, 2003.[10] N. Nikaein and C. Bonnet. A Glance at Quality of Service Models for

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[12] H. Xiao, W. K. Seah, A. Lo, and K. C. Chua. A Flexible Qualityof Service Model for Mobile Ad-Hoc Networks. In IEEE 51st VTC,volume 1, pages 445–449, May 2000.

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