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Computer Networks 47 (2005) 167–183

www.elsevier.com/locate/comnet

An adaptive QoS framework for integrated cellularand WLAN networks

Xin Gang Wang a,*, Geyong Min a, John E. Mellor a,Khalid Al-Begain b, Lin Guan a

a Department of Computing, School of Informatics, University of Bradford, Bradford BD7 1DP, UKb School of Computing, University of Glamorgan, Wales CF37 1DL, UK

Available online 6 August 2004

Abstract

The design of a network architecture that can efficiently integrate WLAN and cellular networks is a challenging task,

particularly when the objective is to make the interoperation between the two networks as seamless and as efficient as

possible. To provide end-to-end quality of service (QoS) support is one of the key stages towards such a goal. Due to

various constraints, such as the unbalanced capacity of the two systems, handoff from user mobility and unreliable

transmission media, end-to-end QoS is difficult to guarantee. In this paper, we propose a generic reservation-based

QoS model for the integrated cellular and WLAN networks. It uses an adaptation mechanism to address the above

issues and to support end-to-end QoS. The validity of the proposed scheme is demonstrated via simulation experiments.

The performance results reveal that this new scheme can considerably improve the system resource utilization and

reduce the call blocking probability and handoff dropping probability of the integrated networks while maintaining

acceptable QoS to the end users.

� 2004 Elsevier B.V. All rights reserved.

Keywords: WLAN and cellular network integration; QoS framework; Reservation; Bandwidth adaptation

1389-1286/$ - see front matter � 2004 Elsevier B.V. All rights reserv

doi:10.1016/j.comnet.2004.07.003

* Corresponding author.

E-mail addresses: [email protected] (X.G. Wang),

[email protected] (G. Min), [email protected]

(J.E. Mellor), [email protected] (K. Al-Begain), l.guan@

bradford.ac.uk (L. Guan).

1. Introduction

In the future, wireless service provision will be

characterised by global mobile access anywhere

and anytime [1]. Two major access technologies

for those mobile communication systems are wire-

less local area networks (WLAN) and cellular

ed.

mailto:[email protected]




mailto:l.guan@

168 X.G. Wang et al. / Computer Networks 47 (2005) 167–183

networks, such as global system for mobile com-

munication (GSM), general packet radio service

(GPRS) and universal mobile telecommunications

system (UMTS). WLAN systems provide very

high data rates at a relatively low cost comparedto cellular networks and is becoming more and

more popular. However, WLAN technology is

more likely a complimentary access method rather

than a competitor to 3G networks because it has

limited coverage area and less support for high

speed mobility. So far WLANs have been setup

in places like airports, hotels, and campuses. 3G

networks are gradually deploying worldwide.Interconnecting WLAN radio access networks

and 3G cellular networks with QoS support offer

an efficient way to enhance the network operator

service.

The communication systems dominated by

voice transmission employed circuit-switching

technology [2] for a long time. However, the de-

mand for data communication is increasing anddrives the development of the packet switching

technology, which led to the born of the Internet.

Currently, the mobile communication system is

facing the same evolution as the Internet. The

network operators are migrating from circuit-

switched GSM systems to GPRS and 3G net-

works worldwide [3]. The ultimate vision is to

provide a universal all-IP platform. The integra-tion of WLAN and cellular networks is an impor-

tant step for this process. It can provide end users

with benefits like lower cost of transmission and

higher bandwidth without losing the roaming fea-

tures or pervasive aspects now emerging. How-

ever, the design of a network architecture that

efficiently integrates WLAN and cellular net-

works is a challenging task, particularly whenthe objective is to make the interoperation of

the two technologies as seamless and as efficient

as possible [4].

To provide end-to-end quality of service (QoS)

support is one of the key issues in the design of

integrated WLAN and cellular networks. Two

major models for QoS support have been pro-

posed in the network research community. One isbased on reservation and another is based on pri-

oritization, namely: IntServ and DiffServ [5]. They

differ in that the reservation-based approach sends

signals through the data path and books its QoS

requirements before the actual data transmission,

while the prioritization-based approach simply

marks the traffic on an individual packet basis to

indicate the QoS requirements and sends the pack-ets to the network. It is well known that the Inter-

net has some fundamental scalability limitations

when it comes to the management of individual

traffic flows using the reservation approach. Its

successor, the prioritization approach, addresses

the scalability problem at the cost of coarser serv-

ice granularity.

Many difficulties emerge when attempting toprovide QoS solutions for integrated WLAN

and cellular networks owing to the unbalanced

capacity of the two systems, issues raised by han-

dover between homogeneous cells and heteroge-

neous cells caused by user mobility, and

transmission through the unreliable wireless

media. To enable efficient use of the scarce re-

sources provided by cellular networks while alsomaintaining strong QoS guarantees, we propose

a generic reservation-based QoS model for the

integrated cellular and WLAN network. Under

the proposed QoS framework, we develop an

adaptation mechanism to address the various

challenges in the integrated mobile networks.

The validity of the proposed frame-work is dem-

onstrated through simulation experiments. Theperformance results indicate that this new scheme

can improve the system resource utilization and

considerably reduce the call blocking probability

and the handover dropping probability of the

integrated network while still maintaining accept-

able QoS to the end users.

The rest of this paper is organized as follows.

Section 2 reviews the existing QoS architecturesand mechanisms which are essential for the fol-

lowing analysis. Section 3 presents the problems

related to QoS support over the integrated sys-

tem. We introduce and analyze the proposed

QoS framework in Section 4. An adaptive algo-

rithm to manage QoS in the framework is intro-

duced in Section 5. Section 6 describes the

simulation and discusses the performance resultsbased on the proposed framework. Section 7

summarizes this study and gives concluding

remarks.

X.G. Wang et al. / Computer Networks 47 (2005) 167–183 169

2. Preliminary work

2.1. WLAN Qos

The success of the Internet and the availabilityof inexpensive WLAN equipment has spurred the

demand for mobile data access. WLANs often

operate on a centralized architecture, where an ac-

cess point (AP) coordinates mobile terminals (MT)

in accessing the wireless medium and links the traf-

fic into the wired network [6]. The AP is either a

layer 2 bridge between IEEE 802.11 and Ethernet

or a layer 3 router between IEEE 802.11 and abackbone network. The MT is typically a laptop

computer or a personal digital assistant (PDA)

with a built-in WLAN radio module or a WLAN

card. There are two majorWLAN standards: IEEE

802.11 and HiperLAN. The success of the IEEE

802.11 in the marketplace has made it the de facto

WLAN standard worldwide. Even for the IEEE

802.11 standards used today, there are a few varia-tions: the widely deployed 11 Mb/s IEEE 802.11b

[6], the high speed (54 Mb/s) version 5 GHz IEEE

802.11a and its cousin IEEE 802.11g. From the

WLAN system point of view, the consequences of

these upgrades are mostly limited to the radio inter-

face as higher layers remain unchanged and they

only support the best effort service to the end users.

To address the QoS requirements, a supplementstandard IEEE 802.11e is under development [7,8].

Two new mechanisms are defined for QoS sup-

port, namely enhanced distributed coordination

function (EDCF) and hybrid coordination func-

tion (HCF) [7]. EDCF is a basic QoS supporting

mechanism. It can provide differential of service

(DoS) [9] and it is still contention-based, while

HCF works as a guaranteed method to provide

Table 1

Traffic categories and access categories

Traffic categories (TCs)

0 (Default) Best effort

1 Background

2 Standard (spare)

3 Excellent effort (business critical)

4 Controlled load (streaming multimedia)

5 Video (interactive media)

6 Voice (interactive voice)

7 Network control reserved traffic

QoS. In the standard, an area covered by a

802.11g network is called a quality basic service

set (QBSS), which is often composed of a hybrid

coordinator (HC) and some 802.11e-compliant en-

hanced stations. The HC can be any station in theQBSS which can work as the central coordinator,

but it typically resides within an 802.11e AP.

EDCF is a contention-based medium access

method and QoS support is realized with the intro-

duction of traffic categories (TCs) and access cate-

gories (ACs). There are eight TCs to provide

differentiated distributed access to the wireless

medium. They are the same as defined in the IEEE802.1d bridge standard for reasons of consistency.

These eight TCs are mapped into four ACs as

shown in Table 1.

The access priority for different traffic classes is

controlled both by a given different contention

window (CW) and by a different inter frame space

(IFS) to different ACs as illustrated in Fig. 1. Each

AC is characterised with an arbitration inter framespace (AIFS) and a persistence factor (PF). The

higher AC has a lower AIFS and a smaller PF

compared to lower ACs. Their formulation is

listed below:

AIFSD½AC� ¼ SIFSþAIFS½AC� � Slottime; ð1Þ

newCW½AC�PððoldCW½AC� þ 1Þ � PFÞ � 1: ð2Þ

The HCF serves as an extension for the EDCF

and it has both contention-based and controlled

contention-free channel access methods in a single

channel access cycle. Each transmission cycle is

realized in the form of a superframe as shown inFig. 2 which consists of a contention period (CP)

and a contention free period (CFP). The EDCF

Access categories (ACs)

0 Best effort

0 Best effort

0 Best effort

1 Video probe

2 Video

2 Video

3 Voice

3 Voice

Contention Free Period (CFP)

802.11E Periodic Superframe

Contention Period (CP)

TBTT

TXOP

Beacon CFP-endHC Poll

RTS/CTS/fragment DATA/ACK

TXOP

Time

Fig. 2. HCF superframe structure.

AIFS[j]

AIFS[i]

DIFSContention Window

Slot time

Busy Medium

Defer Access

Next Frame

Select Slot and Decrement Backoff as long

SIFS

PIFSDIFS/AIFS

Immediate access when

Medium is free >= DIFS/AIFS[i]

as medium is idle

Backoff Slots

Fig. 1. Different IFSs and CWs for different ACs.


operates in the CP and a controlled channel access

mechanism called polling operates concurrently

within the CFP. Because the CFP uses a shorter

IFS called polling IFS (PIFS) than the CP, HCF al-

ways has priority over the EDCF method. During

a superframe, a HC sends out a QoS CF-Poll which

includes the transmission order and the maximumtransmission time. A station will not access the

channel unless it receives such a polling packet.

This HC controlled channel access method guaran-

tees time-bounded service to QoS applications.

2.2. UMTS QoS

The UMTS is the widely accepted 3G cellularnetwork standard and has a layered architecture

for the support of end-to-end QoS for the packet

data domain [10,11]. Fig. 3 shows the UMTS

QoS architecture. Each module calls its bearer

service (BS) to accommodate the QoS require-

ments, when making a QoS transmission. A BS

has a basic functionality defined in each layer fea-

tured by different parameters like traffic type, traf-

fic characteristics and supported bit rate. It

includes all aspects to enable the provision of acontracted QoS. These aspects are, among others,

the control signaling, user plane transport and

QoS management functionality. There are various

BS managers in the different modules to coordi-

nate the overall management procedures. A signa-

ling protocol then can call these BS managers to

accommodate the requested QoS [12].

Packet data protocol (PDP) is used to establishthe QoS connection within the UMTS network. If

the destination is an address outside the UMTS

network, the external BS manager which resides

UTRAN TE TE MT CN Iu EDGE NODE

CN Gateway

End-to-End Service

UMTS Bearer Service

Radio Access Bearer Service

UTRA FDD/TDDService

TE/MT Local Bearer Service

External Bearer Service

CN Bearer Service

Backbone Bearer Service

Iu Bearer Service

Radio Bearer Service

Physical Bearer Service

Fig. 3. UMTS QoS architecture.


in the gateway GPRS support node (GGSN) has

to be used to control IP bearer services by stand-

ard IP mechanisms. Before a terminal equipment

(TE) can send out actual data traffic, it has to send

a PDP request packet through the entire data pathand a QoS path is established while receiving a

PDP acceptance packet.

There are four basic types of traffic classes de-

fined in UMTS [13], namely conversational,

streaming, interactive and background. Conversa-

tional and streaming classes are for real-time

applications, while interactive and background

classes are used for delay-tolerant applications.Conversational class is the most challenging class

and only a very short delay and negligible delay jit-

ter are acceptable. As the trend is to an all-IP net-

work, this class is expected to support voice over

IP for radio applications. The streaming class has

fewer requirements than the conversational class

although still in the real-time catalog. A larger buf-

fer is arranged on the receiver side to remove thedelay variations. These UMTS QoS classes are

summarized in Table 2.

2.3. WLAN and UMTS Integration

The early work on the integration of WLAN

and 3G networks was done by the ETSI BRAN

project [14]. Two different fundamental methods

have been proposed for merging WLAN and cellu-

lar networks namely loose coupling and tight cou-

pling [14]. Loose coupling is shown in Fig. 4 and it

features less integration between the two types ofnetworks, as its name implies. In this scenario,

the WLAN and cellular networks are two separate

access networks. The WLAN access network is at-

tached to the Internet backbone, and the cellular

networks into the cellular core network. The access

networks do not have anything in common, but

the core networks are connected together. Without

necessarily modifying the 3G core network, aloosely coupled WLAN and 3G network can use

existing mechanisms to accommodate its users�needs, for instance, using an authentication,

authorization and accounting (AAA) server to

handle the user subscription to these networks

and using mobile IP (MIP) to facilitate user�sroaming among different access networks [4]. The

motivation is to try and minimize the changes tothe cellular core networks, therefore reducing the

cost of this solution.

Tight coupling illustrated in Fig. 5 suggests that

WLAN technology is employed as a new radio ac-

cess technology within the cellular system. Regard-

less of the access technology, there would only be

one common cellular core network. This can be

Table

2

UM

TS

QoS

trafficclasses

Tra

fficclass

Conversa

tional

Strea

ming

Intera

ctive

Back

gro

und

Chara

cteristics

•Preserv

etime

relation

(variation)

between

info

rmation

entities

ofth

estream

•Asy

mmetricapplica

tions,

more

tolera

ntto

jitter

than

conversa

tionalclass

•Req

uestresp

onse

pattern

•Destination

isnot

expectingth

edata

within

acertain

time

•Conversa

tionalpattern

(stringen

tand

low

delay)

•Use

ofbuffer

tosm

ooth

outjitter

•Preserv

edata

integrity

•Preserv

edata

integrity

Applica

tion

examples

Voice,

video

telephony,video

games

Strea

mingmultim

edia

Web

bro

wsing,

network

games

Back

gro

und

download

of

e-mail,electronic

postca

rd

Fig. 4. Loose coupling.


done by connecting a WLAN AP to a radio net-

work controller (RNC) via the Iu bearer interface.

Another possible approach is that the whole radio

access network (including the base station control-

ler) is WLAN specific and it would attach into the

core network via an Iu interface. Since the corenetwork has to be directly exposed to the WLAN

for tight coupling, the same operator must own

both the WLAN and 3G networks and this makes

the integration of independently operated WLAN

with the 3G networks not possible.

3GPP has recently also taken the initiative to

develop a cellular–WLAN interworking architec-

ture [10]. This interworking architecture is basedon loose coupling and introduces the authentica-

tion, authorization and accounting (AAA) service

and mobile IP (MIP) functionality into the 3GPP

standards. The entire integration is achieved with-

out setting any 3GPP-specific requirements on the

Fig. 5. Tight coupling.


WLAN systems, but relying on the existing func-

tionality available in a typical WLAN access

network.

3. QoS issues in integrated WLAN and UMTS

Supporting QoS for integrated WLAN and

UMTS networks is a challenging task. In the fixed

broadband, admitted resources for a QoS connec-

tion remain relatively static, since there is no user

movement or any radio fading problem. Unlike

in homogeneous wired networks, providing QoSfor integrated WLAN and UMTS networks has

some fundamental bottlenecks [15].

Firstly, WLAN and UMTS networks have dif-

ferent transmission capacity over the radio inter-

faces, therefore the handoff between the two

systems makes the maintenance of QoS connec-

tion very hard. WLAN can provide a transmission

speed from 11 Mb/s up to 54 Mb/s theoretically,while UMTS has only 144 kb/s at vehicular speed,

384 kb/s outdoor to indoor and pedestrian and 2

Mb/s indoor. If we keep the QoS resource as-

signed by UMTS to a connection when it is actu-

ally in a WLAN hotspot, the advantage of the

high speed of WLAN is not fully taken. On the

other hand, if we use a WLAN parameter for a

station in UMTS network, the connection maynot be admitted at all. Therefore, to maintain a

sensible QoS framework, one has to consider the

significant different transmission capacity between

two systems especially when user handoff takes

place.

The second constraint is that WLAN operates

on a free ISM band and has a lot of uncontrollable

interference (i.e., microwave), although some tech-niques like spread spectrum are used to reduce the

interference. Such kinds of problems are beyond

engineering control and a hard QoS guarantee is

very difficult or even impossible to achieve under

such circumstances.

To support QoS in packet switching networks,

there has to be some mechanism to control net-

work load under a threshold so that the systemcan achieve a satisfied performance. The third bot-

tleneck is that the achievable QoS levels in WLAN

and 3G cellular networks do not match each other.

3G cellular networks are very well designed with

careful network planning and mature admission

control algorithms. Therefore, the achievable

QoS level is relatively high, while 802.11e WLAN

works under a more robust environment and it isdifficult to achieve hard QoS, although some form

of admission control [7] has been provided for

HCF in the IEEE 802.11e standard. Even the

EDCF can only provide differential of service

(DoS).

All these problems lead us to find an adaptive

solution for integrated WLAN and cellular net-

works, which can address the above issues and alsoprovide practical and user-satisfying QoS.

4. An adaptive QoS architecture

Increasing data service requirements and Inter-

net applications are driving the cellular network

evolving into an IP-based packet switching net-work [3]. Our proposed QoS framework is based

on a packet switching core network with the

UMTS architecture. However, it holds as well with

the GPRS 2.5G networks or other packet switch-

ing cellular systems. The overall architecture is

shown in Fig. 6. It is well known that the Internet

has some fundamental scalability limitations [5]

when it comes to manage individual traffic flowsusing the reservation-based approach. Its succes-

sor, the prioritization approach addresses the sca-

lability problem at the cost of coarser service

granularity. To enable efficient use of scarce re-

sources provided by the cellular networks while

also maintaining strong service guarantees, we

adopt the reservation-based approach [16]. In

WLAN the reservation is achieved by using theHCF and in UMTS is achieved by the functional-

ity provide by BS. The other components of the

framework are defined below:

• A policy provisioning module (PPM)The PPM is responsible for mapping actual user

QoS profiles with their subscription informa-

tion and decides the traffic classes for the usertraffic flows. Then these QoS parameters can

be handed to the connection admission control

module (CAC) to process.

Fig. 7. A PPM structure.

Fig. 6. Proposed QoS architecture.


• A connection admission control module (CAC)The CAC is to admit the number of flows that

can be served and allocates bandwidth to

them through signaling to all the network

nodes along the traffic path. It also needs to

maintain the QoS requirements of existingconnections.

• A QoS mobility management module (MMM)The MMM decides whether terminals are de-

tached, connected or idle and also monitors ac-

tive nodes moving at high speed.

• A QoS monitoring module (monitor)The monitor continuously measures whether

the QoS requirements of mobile nodes havebeen satisfied.

The components illustrated are viewed as logi-

cal entities. These components can be actually

implemented combined with realistic network

components or in an independent location. A com-

bined IntServ and DiffServ method is adopted

when connecting the integrated network to theInternet backbone in order to address the scalabil-

ity problem.

4.1. Components analysis

4.1.1. QoS policy provisioning

Users� context with the QoS requirement is first

issued to PPM where the users� subscribed infor-

mation together with traffic classes is examined.Then a QoS signal with suggested degradation

profile is made and sent to both the end user and

CAC module (Fig. 7).

Data In

CAC

Data Out

Perflow QoS Forwarding Table

Packet Forwarding

Packet Scheduling

Routing RSVPSignalling network

Fig. 8. QoS structure inside a network node.


• Degradation profileThe negotiation of established QoS connec-

tion is allowed through the degradation

profile. When the user requests to establish a

QoS call, certain network resources need tobe admitted. The requested QoS has to be

allocated when the connection is setup. If cer-

tain conditions change over the activation

time, a negotiation procedure is called. The

degrade profile can include the following

QoS attributes:

– the minimum acceptable rate (bit/s),

– the bit error rate (BER) or frame error rate(FER),

– the maximum loss ratio (the proportion of

received packets to undelivered packets),

– the maximum tolerated delay (ms),

– the maximum tolerated jitter (ms) (the varia-

tion in delay).

• Users� subscription informationPractical service solutions should provide flexibleways of deliveringQoS to the users. For example,

the network operator could offer four packages:

gold, silver, bronze and pay as you go. The gold

package would allow users to transmit at the

maximum rate 5 mb/s in the hot-spot area plus

other calling features. Silver is maximum 1 mb/s

and bronze is just best effort service. This infor-

mation can be accessed by the PPM to iden-tify and mark individual traffic flows for

coordinating QoS from end to end between net-

work elements.

4.1.2. QoS connection admission control (CAC)

The CAC module receives a connection request

from the PPM along with the QoS requirements. Itconsults with the MMM to get the status of user

mobility. Then CAC uses some reservation proto-

cols, RSVP, for example, to book the actual re-

source for users� flow. Based on RSVP signaling

feedback, the connection is finally granted, de-

clined or renegotiated. Some related issues are dis-

cussed below:

• Required resources availableRSVP is an end to end signaling protocol. It re-

serves necessary network resources along its

way until reaching the destination. This reserva-

tion information can either be hard or soft in

the router buffer. Hard state means that the

state information stored in the router has to

be removed by an explicit signaling messagewhile soft state has a timeout field and removes

itself when this value gets to zero. The well

known scalability (or known as state explosion)

problem with the reservation approach, limits

the domain of this solution to small networks.

However, soft state can be used to effectively in-

crease the network scalability. On the other

hand, hard state cannot only reduce the amountof signaling but also guarantee user�s QoS pro-

files. These trade-offs should be considered to-

gether with the practical factors of some

particular networks.

• Degradation of other connectionsApplying QoS means treating some traffic in

preference to others, and this implies the ability

to reject traffic. Especially in wireless mobilecommunication networks, uncontrolled error

rate and users� mobility make us have to look

for adaptation solutions. The use of the degra-

dation profile provides us a gradation between

different QoS merits; negotiation between differ-

ent network flows is an effective way to improve

the overall system performance.

• QoS structure within a single network nodeQoS within a single network element is illus-

trated in Fig. 8. When there is a new connection

or a handoff connection, the request is submit-

ted to the CAC and then the CAC invokes the

signaling protocol RSVP to book the required

Fig. 10. Normal handoff.


QoS resource along the whole data path. An

adaptation mechanism, which integrates the

user degradation profile into its QoS profile,

can be used along with the RSVP signaling pro-

tocol to improve the probability of successfuloperations. Finally, the result of the RSVP sign-

aling is returned to CAC and a decision is made

whether to accept this connection or reject it.

4.1.3. QoS mobility management module (MMM)

Users� mobility has a significant impact on the

QoS of CAC and it plays an important role inthe model. Within an integrated cellular and

WLAN network, a handoff can occur when a mo-

bile node enters a hot-spot area or when it decides

to leave the hot-spot area. Because hot-spots are

usually within the coverage of cellular networks,

the actual handoff is not necessary and a decision

should be made based on user desire. We name

this user-triggered handoff or desirable handoff(DH). Note it is different from general term of

handoff, because it is not time critical as the mobile

nodes can be connected to WLAN and cellular

networks simultaneously (Fig. 9).

• Roaming from cellular networks into WLANA DH may occur when a mobile node roams

into a WLAN. This implies that the route takenby data will change. Any QoS that was estab-

lished for that data flow will be disrupted. A

simple solution to this problem is to establish

a new WLAN reservation before handing the

mobile node over to the WLAN, because

DH�s time tolerance makes this approach realis-

tic. As the wireless link bandwidth will rise dra-

matically, the new submitted QoS profile shouldconsider users� subscription status and give an

appropriate request.

Fig. 9. Desirable handoff.

• Roaming from WLAN into cellular networksA normal handoff occurs when a mobile node

roams from WLAN into a cellular network

(Fig. 10). A new reservation has to be made

again. Moreover the actual handoff time needs

to be kept tightly in order to provide seamlessservice. Since the network resources reserved

by the user in the WLAN is normally over the

UMTS capacity, the actual handoff dropping

probability could be very high. An adaptation

mechanism needs to be embedded in CAC and

this module can reduce the QoS request by

using the degradation profile. Therefore, the

system performance can be improved withoutlosing acceptable QoS level.

• SpeedConsidering the limited coverage area of

WLAN, a user moving at high speed could

experience handoff too frequently to register

with a WLAN system. Therefore, some kind

of speed measurement could be defined in

MMM. A threshold value could also be deter-mined to prevent such an undesirable handoff

from occurring.

4.1.4. QoS monitoring

Once the streaming data is flowing, traffic meters

measure its temporal properties against the QoScontract. If the QoS profile established by end users

is not satisfied, thismonitormay pass state informa-

tion to CAC or other components to trigger specific

actions. This feedback approach enables the QoS to

adapt to the dynamic changes in the networks.

4.2. Connection with the IP backbone

This section describes the QoS architecture

when the integrated networks are connected to

End to End RSVP signaling

IntServ Domain IntServ Domain DiffServ Core

Fig. 11. Combined IntServ and DiffServ architecture.


an IP backbone. The main focus of this network

QoS mechanism is to provide IntServ flexible

QoS definition while not losing scalability. The

overall architecture is shown in Fig. 11. Mobile

terminals (BT) and local network operators imple-

ment IntServ and core network operators imple-

ment the DiffServ architecture. RSVP is used as

the signaling protocol for real-time services.Signaling takes place between end nodes and Int-

Serv edge routers. Some IntServ routers also act as

DiffServ edge routers. From the perspective of an

IntServ network, these routers simply tunnel

through a non-IntServ region. From the perspective

of DiffServ routers, the IntServ network is not visi-

ble and treated as normal traffic with priorities.

4.3. QoS class mapping

To provide unified QoS traffic classes, the QoS

traffic classes from UMTS and WLAN are mapped

into a new set of QoS traffic classes namely: broad-

band conversational (B-conversational), broad-

band streaming (B-streaming), narrowband

conversational (N-conversational), narrowbandstreaming (N-streaming), interactive and back-

ground. The mapping relationships are shown in

Table 3.

Table 3

QoS classes mapping table

Class Integrated network WLAN UMTS

1 B-conversational Voice –

2 B-streaming Video –

3 N-conversational – Conversational

4 N-streaming Video probe Streaming

5 Interactive – Interactive

6 Background Best effort Background

5. The adaptation algorithm

The bandwidth adaptation algorithm, as the

key factor of the proposed framework, decides

how to adjust the QoS connections since mobile

users should be able to seamlessly maintain their

ongoing sessions at a satisfactory level. Ideally

each call in the system should be allocated themaximum allowable bandwidth. However, WLAN

and cellular networks have different transmission

capacities; a session that consumes a moderate

amount of bandwidth in a WLAN system can be

greedy and therefore could be rejected in the cellu-

lar networks. A connection switched from cellular

networks to WLAN needs to up its bandwidth,

otherwise it will lose the benefit of the integra-tion. So we need to degrade some connections

adaptively to accommodate more new arrivals

and handoff calls. Some methods have been pro-

posed [17–25] for this purpose. Our method tackles

the problem from a new angle based on the con-

cept of the proposed degradation profile. We effec-

tively degrade the longest calls in the system based

on their state information because they have agreater probability of quitting the system and leav-

ing fewer degraded connections in the system. Use

of the degradation profile can guarantee the satis-

fied QoS level to the end user and degrading the

longest calls can reduce the degradation degree

of the whole system. The pseudo-code of the adap-

tation algorithm is described in Table 4, where Birepresents the required bandwidth and Di denotesthe minimum bandwidth request defined in the

connection degradation profile.

The level of the performance degradation of

the overall system is critical information to the

network operators. If this happens frequently in

Table 4

Pseudo-code for the adaptation algorithm

New call arrivals

IF (New requested bandwidth Bi < system available bandwidth)

assign Bi;

ELSEIF (New requested band Di < system available bandwidth)

assign Di;

ELSE

WHILE (undegraded call exists AND Di > system bandwidth)

degrade longest call;

IF (Di < system available bandwidth)

assign Di;

ELSE

reject the call;

Handoff call arrivals

IF (Handoff requested bandwidth Bi < system available bandwidth + guard bandwidth)

assign Bi;

ELSEIF (Handoff requested band Di < system available bandwidth + guard bandwidth)

assign Di;

ELSE

WHILE (undegraded call exists AND Di > system available bandwidth + guard bandwidth)

degrade longest call;

IF (Di < system available bandwidth+guard band)

assign Di;

ELSE

reject the call;

Departures

WHILE (system available bandwidth > 0)

find the shortest degraded call;

assign Bi for this call;


a certain area, a new base station or a new access

point may be installed to solve the problem perma-

nently. For this purpose, we define a new perform-

ance merit called system degradation degree. Some

system parameters are described before we intro-

duce the definition of this concept.

The traffic class of a connection is defined as Ci,

where Ci 2 {C1,C2, . . .,Ci, . . .,CK}, where K is thenumber of service classes. The corresponding

bandwidth requirement for each class is defined

as Bi 2 {B1,B2, . . .,Bi, . . .,BK}, for the sake of sim-

plicity we assume that all the connections in the

same class have the same requested bandwidth.

Di 2 {D1,D2, . . .,Di, . . .,DK} denotes the minimum

bandwidth request defined in the connection deg-

radation profile.

Let pi(t) denote the degradation probability of

class i and ni(t) the number of connections from

class i at time t. Thus the degradable bandwidth

at time t can be written as

XKi¼1

ðBi � DiÞpiðtÞniðtÞ: ð3Þ

We define bandwidth degradation degree BR asthe ratio of the amount of reduced bandwidth

and the requested bandwidth:

BR ¼PK

i¼1ðBi � DiÞpiðtÞniðtÞPKi¼1BiniðtÞ

: ð4Þ

The overall system degradation degree SD is the

integration of BR over the period t:


SD ¼Zt

PKi¼1ðBi � DiÞpiðtÞniðtÞPK

i¼1BiniðtÞ: ð5Þ

Table 5

Simulation parameters

Parameter Value

UMTS capacity (U) 2 mb/s

WLAN capacity (W) 11 mb/s

UMTS to WLAN handoff 0.05

WLAN to UMTS handoff 0.01

Reservation signaling cost 1% * W

Session time Exp(50)

Guard band 5%

{B1,B2,B3,B4} {5% * W,3% * W,5% * U,3% * U}

{D1,D2,D3,D4} {4% * W,2% * W,4% * U,2% * U}

Simulation time 1000 s

6. Performance analysis

6.1. The simulation model

This section uses simulation experiments to

investigate how the proposed approach can im-

prove the overall QoS for the integrated cellular

and WLAN networks. Following the assumptions

widely used in previous studies [21,23,24], the call

arrivals in our simulation follow an independentPoisson process and the session time of each con-

nection is exponentially distributed. It is well

known that dropping an established communica-

tion is worse than rejecting a new call. Therefore

cellular systems reserve a guard bandwidth for

the handoff calls in order to reduce the handoff

dropping probability. The reserved guard band-

width can be either static or dynamic [22,24,25].The dynamic approach often outperforms the sta-

tic one at the expense of generating more control

overheads [3]. However, the static approach is of-

ten attractive in practice owing to its design sim-

plicity. In our simulation, a static guard

bandwidth (i.e., 5% of the system capacity) is em-

ployed to deal with handoff calls.

The integrated network in the simulation con-sists of one cellular network and one WLAN hot-

spot. Since WLAN has a higher capacity and is

cheaper than UMTS, we assume the handoff prob-

ability from UMTS to WLAN is 5 times as much

as that from WLAN to UMTS. The system capac-

ity for UMTS and WLAN is 2 and 11 mb/s respec-

tively. The bandwidth requirement for each of four

QoS classes {B1,B2,B3,B4} defined in Section 4.3and their acceptable degradation level defined in

degradation profile are assumed to be a portion

of the system capacity listed in Table 5. The reser-

vation signaling cost before the establishment of

each new or handoff connection is set to a fixed

value. For the sake of clarity, all the relevant

simulation parameters are summarized in Table

5. The simulation is carried out under various traf-

fic loads. We compare the proposed approach with

non-adaptive multimedia services.

6.2. The experiment results

This section presents the simulation results to

demonstrate the effectiveness of the proposed

scheme. To do so, we assign the same traffic loads

to two systems working under normal operation

conditions and under the proposed framework.

Each simulation experiment was run until the sys-tem reached its stable state. To measure the system

performance merits, we first examine the normal-

ized system utilization defined as the amount of

data transmitted in the unit time normalized with

the system capacity. We then consider QoS param-

eters: the call blocking probabilities and handoff

dropping probabilities. Finally, the overall system

degradation is calculated.Fig. 12 compares the bandwidth utilization sup-

ported by the proposed adaptive scheme in the inte-

grated network to that without the adaptive scheme

under various traffic loads. From this diagram, we

can observe that the utilization increases as traffic

loads increase. Under all system traffic loads, the

adaptive strategy uses the system recourses more

efficiently than non-adaptive connections. Whenthe traffic load becomes higher, the advantage is

more evident. The reason that adaptive connections

can better utilize the system bandwidth is that the

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9Traffic Load

Util

izat

ion

Non-Adaptive

Adaptive

Fig. 12. Utilization vs. traffic load.


proposed scheme allows the network to intelligently

adjust each admitted QoS connection by its degra-

dation profile and give sufficient resources for the

new or handoff calls.

Fig. 13 depicts the call blocking probability vs.

the traffic load for adaptive connections and non-

adaptive connections. From the diagram, we canobserve that there is no call blocking probability

for both methods with light traffic load. Particu-

larly, we start to see the call blocking probability

when the traffic loads reached 0.4 in the non-adap-

tive situation and for the adaptive conditions we

start to observe the call blocking probability at

0.5 traffic load. This clearly demonstrates the effec-

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

0.4 0.5 0.6 0.7 0.8 0.9

Traffic Load

Cal

l Blo

ckin

g Pr

obab

ility Non-Adaptive

Adaptive

Fig. 13. Call blocking probability vs. traffic load.

tiveness of the proposed mechanism. With further

increments of the traffic load, the call blocking

probability increases, since channels became more

and more crowded. The figure also reveals that the

adaptive approach reduces the call blocking prob-ability compared to the non-adaptive approach.

Fig. 14 further evaluates the handoff dropping

probability in the integrated network. From the fig-

ure, we can observe that the handoff dropping prob-

abilities increase as the system traffic loads increase.

The handoff dropping probability for adaptive con-

nections is much less than that for non-adaptive

connections at the same traffic load condition.When the traffic load becomes higher, the trend is

more evident. For instance, when the rate of traffic

loads reaches 0.9, the handoff dropping probability

is 0.1079 for adaptive connections and 0.0104 for

non-adaptive connections. Under the adaptation

system, we barely see the handoff dropping calls

and this only emerges at traffic load 0.7. This reveals

that the proposed approach reduces a great numberof handoff dropping calls for the integratedWLAN

and cellular system, which is often a disturbing

event in cellular networks.

Fig. 15 shows the degree of overall system deg-

radation defined in Section 5. This designed

parameter can act as indicator to network opera-

tors. When the overall system degradation param-

eter stays high for a certain period time, thenetwork operator should think of installing more

base stations or access points. From the figure,

0

0.02

0.04

0.06

0.08

0.1

0.12

0.4 0.5 0.6 0.7 0.8 0.9Traffic Load

Han

doff

Dro

ppin

g Pr

obab

ility

Non-Adaptive

Adaptive

Fig. 14. Handoff dropping probability vs. traffic load.

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0.045

0.5 0.6 0.7 0.8 0.9Traffic Load

Syst

em d

egra

de d

egre

e

Fig. 15. System degrade degree over traffic load.


we observe that the degradation increases nearly

linearly with the increment of traffic loads, sincewith more users wanting to use the channel, the

system is more adaptive. Also in practical systems,

this performance merit can be designed as a

threshold for control of the system performance

by the network operator.

7. Conclusions

The rapid deployment of WLAN and the 3G

cellular systems provide the two major technolo-

gies for future networks. The design of a network

architecture that can efficiently integrate WLAN

and cellular networks is a challenging task. Many

difficulties emerge when providing QoS, such as

the unbalanced capacity of the two systems, han-doff due to user mobility and unreliable wireless

media. To enable efficient use of the scarce re-

sources provided by the cellular networks while

also maintaining strong service guarantees, this

study has proposed a generic reservation-based

QoS model for the integrated cellular and WLAN

networks. Our model supports the delivery of

adaptive real-time flows for end users taking theadvantage of high data-rate WLAN systems as

well as the wide coverage area of cellular networks.

In particular, we analyze the different components

of the model and their interaction. An adaptation

mechanism is also developed under the proposed

QoS model to address the various challenges gen-

erated by designing integrated WLAN and 3G

networks.

The superior performance of the system is re-vealed via simulation experiments. The results

show that the proposed scheme uses system re-

sources efficiently. Simulation experiments also

indicate that the adaptive multimedia framework

outperforms the non-adaptive approach in terms

of lower handoff dropping probability and call

blocking probability while still maintain accepta-

ble QoS for the end users.

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Xin Gang Wang received his first B.Sc.degree in Computer Science from theHeilongjiang University, P.R. China,in 2001. He is currently a Ph.D. stu-dent in the computing department,University of Bradford. His researchinterests include performance mode-ling of mobile networks.

Geyong Min received the Ph.D. degreein computing science from the Uni-versity of Glasgow, United Kingdom,in 2003, and the B.Sc. degree in com-puter science from Huazhong Univer-sity of Science and Technology, China,in 1995. He is currently a lecturer in theDepartment of Computing at theUniversity of Bradford, United King-dom. His research interests includeperformance modelling/evaluation,parallel and distributed systems,mobile computing, computer net-

works, multimedia systems.
He is the founding co-chair of the International Workshop
on Performance Modelling, Evaluation, and Optimisation ofParallel and Distributed Systems (PMEO-PDS) held in con-junction with IEEE/ACM-IPDPS. He is the guest editor of thejournals Computation and Concurrency: Practice and Experi-ence, Future Generation Computer Systems, and Supercomput-ing. He has served on the program committees of a number ofinternational conferences. He is a member of the IEEE Com-puter Society.

John Mellor has worked in the mod-elling and simulation of communica-tion networks for 25 years. Early workincluded dynamic alternate routingand the application of learningautomata to routing strategies in cir-cuit and packet switched networks.Collaboration with a Cambridge UKcompany led to the development of aLAN protocol which consistently out-performed Ethernet. He was sent as agovernment expert to study the man-ufacturing messaging protocol in the

USA and Japan. He later became a technical expert consultant
on the application of European Directives within the manu-facturing industry. A forray into radio frequency identificationtags resulted in the development of a novel protocol that wasexploited by a major vehicle component manufacturer. He nowfinds himself involved in wireless protocols with researchersworking on WiFi (802.11) and on security aspects of mobilecommerce. He is leader of the Mobile Computing and Net-works Research Group at the University of Bradford andcourse tutor to three innovative advanced M.Sc. courses inmobile computing, applications and security.

er Networks 47 (2005) 167–183 183

Khalid Al-Begain is Professor ofMobile Networking and Head of theMobile Computing and NetworkingResearch Centre at the School ofComputing of the University ofGlamorgan in Cardiff/Wales/UK. Hereceived his High Diploma (1986), theSpecialisation Diploma of Communi-cation Engineering (1988) andhis Ph.D. degree in CommunicationEngineering (1989) from the Tech-nical University of Budapest inHungary.

From 1990 to 1996, he held the position of a Assistant

X.G. Wang et al. / Comput

Professor at the Department of Computer Science of theMu�tah University in Jordan. Then he became an AssociateProfessor at the same university. In 1997 he moved to theDepartment of Computer Science at the University ofErlangen-Nuremberg in Germany as Alexander von Hum-boldt research fellow. Later, he spent one year as GuestProfessor at the Chair of Telecommunications, DresdenUniversity of Technology, Germany. From 2000 to 2003, hehas been Senior Lecturer and Director of PostgraduateResearch in the Department of Computing of the Universityof Bradford, UK before moving to Glamorgan. He co-authored the book ‘‘Practical Performance Modelling’’published by Kluwer Academic Publishers in Boston andmore than 100 refereed journal and conference papers. Healso served/serves as Guest Editor for several special issues ofthe International Journal of Simulation on Analytical and

Stochastic Modelling Techniques. He is UNESCO Expert innetworking, UK Representative to EU COST Action 290Management Committee, senior member of the IEEE andmany other scientific organisations. Since 2003, he is theConference Chair for the annual ASMTA (Analytical andStochastic Modelling Techniques and Applications)Conference (ASMTA�03 in Nottingham, UK and ASMTA�04in Magdeburg, Germany). He also manages several researchprojects funded by the EPSRC and EU.

His research interests include performance modelling andanalysis of computer and communication systems, modellingand design of wireless mobile networks and multicast routingin mobile IP networks. He is also interested in mobile com-puting research.

Lin Guan received the B.Sc. degree incomputer science from HeilongjiangUniversity, Heilongjiang, China, in2001. She is currently a Ph.D. stu-dent in University of Bradford. Herresearch interests focus on developingcost effective analytical models forthe performance evaluation of con-gestion control algorithms for Inter-net traffic.

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