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Survey of admission control algorithms in IEEE 802.11e Wireless LANs

Yanbing Liu

Department of Computer Science and Technology

Chongqing University of Posts and Telecommunications

& Chongqing University Chongqing, China

Email: liuyb@cqupt.edu.cn

Man Meng

Department of Computer Science and Technology

Chongqing University of Posts and Telecommunications

Chongqing, China

Email: mengmanfree@gmail.com

AbstractThe provision of Quality of Service (QoS) inwireless network becomes very important. IEEE 802.11estandard was introduced to enhance the Media AccessControl (MAC) layer operations to provide the QoS expe-rienced by traffic flows. But only IEEE 802.11e can notguarantee network congestion avoidance and traffic QoSespecially to multimedia traffics. So, an efficient admission

control scheme is necessary to transmit multimedia trafficin high efficiency and quality. At present many admissioncontrol schemes have been proposed, in this paper we overallsummarize the purpose, basic components, and classificationsof admission control. And then present a survey of admissioncontrol in IEEE 802.11e EDCA and HCCA, these admissioncontrol schemes are discussed according to different cate-gories: Measurement-Based, Model-Based, Hybrid schemesof EDCA and Physical-Rate and Contention-Window-Basedof HCCA in IEEE 802.11e WLANs. Finally we will comparethese schemes to get the advantages and disadvantages andpoint out the remaining challenges which are useful for us tostudy the admission control under heterogeneous networksand make admission control schemes accurate and simple.

Keywords-IEEE 802.11e; admission control; QoS;

I. INTRODUCTION

With the rapid growth of wireless communication sys-

tems, the number of wireless users has consequently

increased. Therefore, wireless networks should be able

to provide guaranteed QoS for different services. IEEE

802.11e standard [1] was introduced to overcome the lack

of QoS support for the legacy IEEE 802.11 WLANs.

It introduces a new access method named Hybrid Co-

ordination Function (HCF) which consists of two parts:

Enhanced Distributed Channel Access (EDCA) which can

only support relative QoS; and the HCF Controlled Chan-

nel Access (HCCA), which can support absolute QoS, but

involve complex polling and scheduling to allocate the

resources to the competing stations. The former supports

QoS by providing service differentiation through assigning

different channel access parameters (CAPs) to different

Access Categories (ACs). But only service differentiation

can not satisfy the QoS requirement of each traffic class.

The latter is not suitable for VBR traffics. To solve

the above problems, proper admission control scheme is

essential to support multiple types of traffics with various

QoS requirements. Reference [2] has summarized some

admission control schemes and compared their character-

istics.In this paper, we provide a new survey of recent

advances in admission control scheme of IEEE 802.11e

WLANs. Our purpose is to study how the new QoS

schemes and parameters provided in EDCA and HCCA

can be well utilized to fulfill the requirements of admission

control, thus will help us analyze the admission control

under heterogeneous networks in future. We also compare

these schemes to point out their advantages and disadvan-

tages which are useful to make admission decision simple,accurate, and improve network performance.

The remainder of this paper is organized as follows.

Section II gives an overview of admission control. Section

III and IV describe the survey of recent research works

in admission control for both EDCA and HCCA. Section

V presents the comparison of these admission control

schemes. Finally, we draw the conclusion.

II. AN OVERVIEW OF A DMISSION C ONTROLS CHEME

A. Propose of Admission Control

It is a key component of QoS-based resource man-

agement schemes and mainly manages wireless resourcesin order to adapt to traffic variations. In other words,

admitting a new flow must meet two conditions: one is

that there are enough resources to meet the QoS of new

traffics; the other is that the upcoming real time traffic

into a particular service class does not degrade the QoS of

the existing traffics, while simultaneously ensuring that the

scarce bandwidth is utilized efficiently. But many purposes

of admission control schemes vary in term of the design

principles as indicated in [3]. Also the issue of fairness

among different traffic classes should be taken into account

in assigning admission control schemes.

B. Basic Components of Admission Control

Admission control extracts its decision based on the

collaboration of three basic components. As shown in

figure 1 [4], traffic descriptor, admission criteria, and net-

work QoS state and flow information are the fundamental

architectures of an admission control scheme. These three

components are in cooperation with each other in order to

achieve specific objectives.

An admission control module obtains the traffic descrip-

tor, and the QoS requirements of the flow as its inputs,

and outputs its decision of either admitting the flow at

the demanded QoS or denying it if that QoS is not met.

A traffic descriptor is a set of parameters of the sourcethat describes the traffic characteristics. In order to obtain

the admission control decision, the admission controller

2009 ETP International Conference on Future Computer and Communication

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DOI 10.1109/FCC.2009.47

230

2009 ETP International Conference on Future Computer and Communication

978-0-7695-3676-7/09 $26.00 2009 IEEE

DOI 10.1109/FCC.2009.47

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Traffic Descriptions and

QoS Requirements

Admission Criteria

Admission Control

Unit

Network QoS State

and Flow

Information

Admission control

module

Admission Decision

Figure 1. Basic Components of Admission Control

Admission Control

Classifications

Centralized or

Distributed

Approaches

Model-based or

Measurement-based or

Hybrid

Approaches

Uniform Cell-based,

Non-

Uniform Cell-based or

User-based

Figure 2. Classifications of Admission Control

performs the admission criteria module, which is a set of

rules used by the admission control scheme to make the

decision [5].

C. Classifications of Admission Control

The admission control schemes can be classified by

several properties. Some of these properties are shown

in figure 2. They are based on various criterions. Each

criterion has its advantages and disadvantages. In next

section, We will study the admission control schemes for

IEEE 802.11e in detail.

III. ADMISSION C ONTROLF OR EDCA

Recently, several admission control schemes have been

proposed for EDCA. We will classify these admission

control schemes into three classifications: measurement-

based, model-based, and a joint measurement-based and

model-based admission control scheme.

A. Measurement-Based Admission Control

1) Threshold-Based Admission Control: Generally, in

this scheme, each station needs to measure the traffic

conditions and the network defines suitable upper or lower

bound threshold values that indicate the current network

load like [6]. It is centralized and Network Utilization

Characteristic (NU C) of a flow will be used as the

decision criterion in admission control. N U C of a flow

is defined as the fraction of time per time unit needed to

transmit the flow over the network. If the N U C of all

the flows (NU C total) is below the set N U C threshold

(NU C threshold), the flow can be admitted.

Although this scheme is very easy to implement and

can guarantee the QoS of high priority flows when the

medium is heavily loaded, the throughput of the low

priority flows with admission control performs worse than

the case without admission control, that is the issue offairness is not considered. Another problem is difficult to

set the NU C threshold value.

2) Resource Sharing-Based Admission Control: The

reservation and sharing of bandwidth is an important

method to achieve QoS guarantees like [7]. In this scheme,

bandwidth is reserved for a particular traffic AC and

also be shared among them, such as 20% reserved to

VoIP (AC0); 40% reserved to video (AC1); 30% sharedbetween AC0 and AC1; 10% exclusively reserved tocontentions between web and ftp traffic belonging toAC2andAC3respectively. Thus, utilization percentages of thechannel can be got: UAC0 0.5 and UAC1 0.7 andUAC0 + UAC1 0.9. UACi can also be expressed as theratio between the total throughput of the corresponding

AC and the BSS maximum throughput Thpeq with a

certain mean packet size during an observing interval.

So, the detail criteria of admission control is as follow:

IfUAC0 0.5, reject new flow. IfUAC1 0.7, reject newflow. IfUAC0 + UAC1 0.9, reject new flow.

The advantages of this scheme are its simplicity and fair

to all different traffics. However, one drawback is the staticpartition of bandwidth which could lead to an inefficient

utilization of resources if significant load variations occur.

B. Model-Based Admission Control

The earliest model of WLANs is Markov Chain Model

which is the foundation of the latter model, but it is

proposed for IEEE 802.11 and it has some limitations.

Researchers have built new models for IEEE 802.11e

through improvement.

1) G/G/1-Based Admission Control: In [8], an im-

proved analytical model G/G/1 is firstly built to derive

an average delay estimation, as well as channel utilization(cu) which are the decision criteria. In this scheme, the

average data rate (Rmean), peak data rate (Rpeak) and

average packet length (P Kl) are used to characterize the

bandwidth requirement of a real-time traffic. Then, cu

can be calculated corresponding to a flows bandwidth

requirement as follows: cu= RPKl

Tsuc, where R is the

traffic rate. Thus, bandwidth requirement of a flow can be

translated into (cumean, cupeak).

The coordinator records the total channel utilization

due to all admitted real-time flows into two parameters

(cuA,mean, cuA,peak). We also estimate the average delay

Di using the G/G/1 model. So in order to admit a

new QoS flow, three requirements need to be satisfied:

the first is cuA,mean+cui,mean < CUrt; the second is

cuA,peak+cui,peak < CUmax; the last is the average delay

Di less than the delay bound Di, i=2,3.

The proposed scheme successfully guarantees strict QoS

requirements of real-time traffics, while achieving high

channel utilization. But the G/G/1 model delivers a rough

upper bound for the average delay, which become looser

as the number of flows increases. As a consequence, this

scheme can only suggest a pessimistic limit on the number

of admission users for small-size networks.

2) Parameters-Based Admission Control: To improve

the performance of network, only adjusting EDCA pa-rameters cant satisfy the QoS of traffics. So We should

combine adjusting parameters with the admission control

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scheme like [9]. This scheme works jointly with a tuning

algorithm which decides the most suitable configuration

of the MAC parameters when a new flow arrives or

leaves the system. An EDCA analytical model, which is

presented in [10], is used to estimate the feasibility of

the new state conditions (including the requesting flow)

and allows to evaluate all EDCA parameters. The most

suitable combination of the MAC parameters is from an

heuristic real-time algorithm. The algorithm first computes

the minimum aggregated bandwidth required by all flows.

Using this value and the achievable maximum physical

bandwidth, the data rate, the MAC parameters are adjusted

based on a set of predefined thresholds.

This scheme sufficiently considers all EDCA parameters

and fairness between uplink and downlink. But the values

of threshold are difficult to set and some assumptions exist

which is inaccurate to algorithm.

C. Measurement-Aided, Model-Based Admission Control

To avoid the drawback of measurement-based and

model-based schemes, a hybrid scheme has become the

main method in admission control scheme.

1) Threshold-Based Admission Control: This scheme

like [11] is that a QAP monitors the channel continu-

ously and measures the contention probability. When a

new flow ofACi requests admission, the QAP estimates

the equivalent number of competing entities of class i

which is a method for converting a heterogeneous EDCA

network into a homogeneous equivalent DCF network, and

predicts the achievable bandwidth and one-hop delay of

the new flow. This can be done using the non-saturation

homogeneous model. Only if the bandwidth and delay

requirements of new and admitted flows are all satisfied,

the new flow can be admitted.

This scheme proves to be very simple, and more practi-

cally feasible without complex computation compared to

the approach that relies on a direct study of the EDCA

system. However, the analytical model of a non-saturated

is for IEEE 802.11 DCF which is not accurate to admission

control for EDCA.

2) Channel Access Parameters (CAPs)-Based Admis-

sion Control: This method [12] is similar to the above

[10]. But in this scheme, the admission control parameters

including the maximum tolerable collision rate for traffic

i, the maximum retransmission limit, , and TXOP period,

TXOPi are obtained through existing analytical model

[13], then dynamically updates the traffic CAPs based

on periodical measurement of current channel conditions.

If the traffics maximum tolerable collision rate is less than

the channel collision rate, the traffic required delay bound

and dropping rate cannot be satisfied under the current

channel condition, the traffic will be rejected at the station

level. If the traffic can be admitted at the station level, thestation will further forward this admission request to the

AP. The AP makes a decision according to (1) to accept

or reject this admission request.

TXOPi,k+1 Ri(n) +

K

k+1

TXOPk Rk(n) SI (1)

where k is the number of existing flows, R is the ratio

of the total allocated time over the stated application ratesrequired time for successful MSDU transmission, the value

ofRi(n) is used as an index of the current channel packet

error rate, k+ 1 is used as an index for newly arrivingstream, and Kis the total number of new flows, S I is the

service interval.

Through dynamically adjusting channel access param-

eters, it is possible to provide the guaranteed QoS for

admitted real-time traffic while maintaining good channel

utilization. However, If the chosen increment or decrement

of the channel access parameters is too large, the systems

will oscillate, if it is too small, the system will take a long

time to reach the optimal status.

IV. ADMISSION C ONTROLF OR HCCA

Due to the centralized control of HCCA, it has higher

complexity and inefficiency for normal data transmissions.

Thus, there is not much research on the admission control

issue in it. But HCCA is efficient in handling time-

bounded multimedia traffic and can provide absolute QoS

guarantee, so it is necessary to study it and its admission

control scheme. A simple admission control has been

developed as a reference in the 802.11e standard [1]. This

reference scheme only works fine for CBR traffic other

than VBR traffic.

A. Physical-Rate and Contention-Window-Based Admis-

sion Control

This scheme [14] uses the current rate transmission

of QSTAs instead of the minimum rate transmission

according to their positions for calculating the load of

network (L), such as L=36Mbps if the position p of

the station from the QAP is 5 meters; L=11Mbps if

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Table ICOMPARISON OF A DMISSIONC ONTROL M ETHODS

Index

AdmissionMethod Measurement-

basedModel-based

Hybrid-based

HCCA

Complexity Simple Complex ComplexMoreCom-plex

Theoretical Founda-tion

Worse Better Better Worse

Network Utilization High Low Higher High

Flexibility Good Poor Better Good

Expansibility Good Good Good Worse

at dynamically adjusting parameters based on channel

condition but difficult to choose a proper threshold and

lack of theoretical foundation; Model-based admission

control schemes are based on some analytical models

and it is possible to optimize the entire system, but are

weak at dynamically adjusting the channel parameters to

achieve optimal channel utilization; A joint measurement

and model methods can avoid mentioned limitations. For

HCCA there is not much research work on the admission

control due to its centralized control. The detail compari-

son is shown as table I. So, we should take into account to

use new theoretical analysis methods such as cross-layer

[15] [16] and game theoretical[17][18] for satisfying QoS

of traffics maximally.

V I. CONCLUSION

In this paper we have surveyed various admission con-

trol schemes for both EDCA and HCCA. Although manyadmission control schemes have been proposed for them,

there are more or less limitations to support QoS especially

multimedia traffic in WLANs. Many challenges remain

for them. We should decrease the assumption to make the

admission decision accurate. Especially, we need to know

how to ensure end-to-end QoS, how to optimally map

the QoS requirements between different network layers,

how to map the QoS from application into the channel

access parameters, and how to dynamically adjust the

QoS on upper layers while underlying network condition

changes. For HCCA it is not clear how to optimally

select effective TXOPs to trade off between flow QoSand network utilization. So, cross-layer frame work and

game theoretical analysis methods become more and more

important field of In the future, we will study admission

control schemes under heterogeneous wireless networks.

ACKNOWLEDGMENT

This work is supported by the Science Research, Foun-

dation of MOE of China under Grant No.209101, and CQ

CSTC.

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