MAC ENHANCEMENTS TO SUPPORT QUALITY OF
SERVICE IN WIRELESS NETWORKS
A THESIS
Submitted by
RAJESH S.
in fulfillment for the award of the degree
of
MASTER OF SCIENCE (BY RESEARCH)
DEPARTMENT OF ELECTRONICS ENGINEERING
FACULTY OF INFORMATION AND COMMUNICATION
ENGINEERING
ANNA UNIVERSITY
CHENNAI 600 025
MAY 2004
ii
BONAFIED CERTIFICATE
Certified that this thesis titled ‘MAC enhancements to support quality of
service in wireless networks’ is a bonafide work of Mr. S.Rajesh who carried
out the research under my supervision. Certified further, that to the best of my
knowledge, the work reported herein does not form part of any other thesis or
dissertation of the basis of which a degree or award was conferred on an
earlier occasion on this or any other candidate.
Date:
Place: MIT, Chennai.
Dr.S.Srikanth,
Member Research Staff,
AU-KBC Research Centre,
MIT Campus, Anna University,
Chromepet, Chennai,
TN – 600 044 – India.
Dr.C.N.Krishnan,
Director,
AU-KBC Research Centre,
MIT Campus, Anna University,
Chromepet, Chennai,
TN – 600 044 – India.
iii
ABSTRACT
High raw data rates at physical layer have become possible in
wireless communication. But for multimedia (voice, video, games) applications
to use these, it is necessary to design medium access control (MAC)
schemes that can support quality of service (QoS). In this thesis, we propose
MAC enhancements to improve the performance of wireless networks.
Specifically, we address the MAC issues in wireless ad hoc networks and
wireless local area networks (WLANs) to support traffic with QoS
requirements.
We have assumed the use of carrier sense multiple access
(CSMA) based schemes in this work. The wireless channel is a shared
medium and hence it is necessary to have efficient MAC schemes. In wireless
ad hoc networks, the MAC is usually distributed, whereas, in WLAN, the MAC
could be distributed or centralized based on topology and requirement.
Support for QoS involves catering to two types of traffic:

Traffic that has priority assigned per packet (based on type of data in the
packet or the link end-points involved). This requires the MAC to
differentiate (prioritize) and give the appropriate ratio of the available
bandwidth to the traffic.

Traffic streams that must be guaranteed certain bandwidth, delay and
other requirements (put together as QoS requirements) irrespective of
other traffic in the system.
Traffic streams with QoS guarantees are supported in the
centralized MAC scheme only.
iv
Contributions made in this thesis are:

Wireless ad hoc networks with directional antenna at nodes are
considered and we propose a MAC protocol that uses the directional
antennas used by the nodes. We show that there is improvement in
throughput and delay performance due to this.

We then consider WLANs with centralized MAC and propose an
enhanced MAC to improve the delay and throughput performance of
the system so that the QoS requirements can be met.
v
ACKNOWLDEGEMENT
This thesis is the outcome of the direction, encouragement and
invaluable guidance from my supervisor Dr.S.Srikanth and co-supervisor
Dr.V.Vaidehi. My sincerest thanks to them for helping me move ahead with
the research work at every stage and motivating me to do the best.
I am greatly indebted to Dr.C.N.Krishnan, the Director of Anna
University - K.B.Chandrasekhar (AU-KBC) Research Centre for the
extraordinary effort and ideology behind the whole research programme. A life
shall not suffice to return what I have gained out from him and the Research
Centre.
My sincere thanks to Dr.S.Anand and Dr.R.Jayaparvathy for their
invaluable suggestions and many interesting discussions which threw light on
a number of subtle points in the study. Thanks to all staff for every course I
had undergone has helped me in this work. Dr.S.Shanmugavel’s suggestions
came in at the right time to add the missing glitter to the work.
My heart felt thanks to all friends including Bhat, Gopi, Kadal,
Khan, Masood, Nandhan, Rajesh, Sangeeta, Vijayalakshmi and Vinosh
for having helped me in more than one way throughout the course and
research work.
All my success in working towards this degree is due to the love
and immense moral support my parents and sister have given me. And of
course, to God my thanks have no bounds but are too less still.
vi
TABLE OF CONTENTS
ABSTRACT
III
LIST OF TABLES
VIII
LIST OF FIGURES
IX
LIST OF ABBREVIATIONS, SYMBOLS AND NOMENCLATURE
X
CHAPTER 1
1
INTRODUCTION
1
1.1 Overview
1
1.1.1
Literature Review
2
1.2 Problem Definition
3
1.3 Assumptions
3
1.3.1
Scope
4
1.4 Contribution in this Thesis
4
1.5 Thesis Organization
4
CHAPTER 2
6
MAC ENHANCEMENTS IN AD HOC NETWORKS
6
2.1 Overview
2.1.1
Ad Hoc Networks
2.2 The IEEE 802.11 Standard
6
6
7
2.2.1
Distributed Coordination Function
7
2.2.2
QoS Enhancement
9
2.2.3
EDCF Mode of IEEE 802.11e MAC
10
2.3 Proposed Scheme
10
2.4 System Model
11
2.4.1
MAC Enhancements with Directional Nodes
12
2.4.2
QoS Enhanced MAC with Directional Nodes
14
2.5 Performance Study
14
vii
2.6 Results and Discussion
15
CHAPTER 3
18
QOS IMPLEMENTATION ON WLAN
18
3.1 Overview
18
3.2 Existing Technology
18
3.2.1
PCF Mode of IEEE 802.11 MAC
19
3.2.2
HCF Mode of IEEE 802.11e MAC
20
3.3 System Model
21
3.3.1
MAC Scheduler Enhancements
21
3.3.2
Design of Scheduler
22
3.3.3
Enhanced Scheduling Algorithm
24
3.4 Performance Study
3.4.1
Simulation
3.5 Results and Discussion
28
29
31
CHAPTER 4
38
CONCLUSION AND FUTURE SCOPE
38
4.1 Conclusion Summary
38
4.1.1
Applications
39
4.1.2
Future Scope
39
APPENDIX 1
Assignment of Type of Service
40
40
Case 1
40
REFERENCES
43
PUBLICATIONS OUT OF THIS WORK
46
viii
LIST OF TABLES
Table 1. TSPEC based Admission Control .................................................... 23
Table 2. Twin Token - Bucket Parameters .................................................... 27
Table 3. AC association - Simple case (Case 1) .......................................... 41
Table 4. AC Assignment – Complex Case (Case 2) ..................................... 42
ix
LIST OF FIGURES
Figure 1. DCF mode of operation
8
Figure 2. State Diagram of the Protocol
13
Figure 3. Delay Performance with increasing Network Density
15
Figure 4. Performance of ad hoc MAC schemes
16
Figure 5. Effect of Power-backoff
17
Figure 6. CFP, CP and Super-frame
19
Figure 7. System - Block Diagram
22
Figure 8. Twin Token Bucket Implementation
24
Figure 9. Alternating CFP and CP
25
Figure 10. EMDR (Estimated Mean Data Rate) Curve
26
Figure 11. TXOP generated by Scheduler in HCF compared with basic PCF28
Figure 12. Parameters for generation of traffic of 4 ACs
30
Figure 13. Variation in effective goodput with traffic
31
Figure 14. Behavior of EDCF and HCF
32
Figure 15. Traffic Streams supported for different peak data rate deviation on
a non-ideal channel
33
Figure 16. Traffic Streams supported and EDCF Throughput for a network
when scheduler in HCF handles TXOPs of both contention free and
contention based traffic.
34
Figure 17. Goodput v/s delay for various schemes.
35
Figure 18. Co-efficient of variation versus delay plot.
36
x
LIST OF ABBREVIATIONS, SYMBOLS AND
NOMENCLATURE
s

AC
ACK
Ad Hoc Network
AIFS
AP
Atomic Sequence
BC
BEB
BER
Beacon
BSS
CAP
CBR
CCA
CFP
CP
CSMA
Micro Seconds (1s = 10-6 Second)
tou – stands for traffic density – Traffic to be
transmitted to or received from a particular
source or sector of a network region (direction)
Access Category
Acknowledgement
An infrastructure-less, topology-free wireless
network.
Arbitration IFS
Access Point
A transmission of the following sequence
 RTS (from Source)
 CTS (from Destination)
 Data (or MPDU from Source)
 ACK (from the Destination)
Broad-cast
All that can hear are the intended recipients.
Binary Exponential Backoff
Bit Error Rate
A management frame (that has to be
transmitted periodically) carrying the network
parameters and timing information.
Basic Service Set
Controlled Access Phase
Constant Bit Rate
The type of traffic that is encoded using a
constant bit rate encoding like a 64kbps for a
voice frame.
Clear Channel Assessment
Contention Free Period
Contention Period
Carrier Sense Multiple Access
xi
CSMA/CA
CSMA/CD
CTS
CW
DCF
DACK
DCTS
DData
DIFS
Directional Antenna
DRTS
EDCF
EIFS
EMDR
FCFS
Goodput
HC
HCF
IBSS
IFS
LAN
MAC
MANET
maxMSDULifetime
MDR
MPDU
MSDU
Multicast
Network Density
CSMA/Collision Avoidance
CSMA/Collision Detection
Clear To Send
Contention Window
Distributed Coordination Function
Directional ACK
Directional CTS
Directional Data
DCF IFS
An antenna that radiates only a few degrees
(much less than 360) on the horizontal as well
as vertical planes.
Directional RTS
Enhanced DCF
Extended IFS
Estimated MDR
First Come First Serve
We define goodput as the total number of bits
of data transmitted successfully by the MAC
layer per unit time. Maximum goodput of a
particular topology corresponds to the traffic
condition that results in maximum bits transfer
in MAC.
Hybrid Coordinator
Hybrid Coordination Function
Independent BSS
Inter-frame Spacing
Local Area Network
Medium Access Control
Mobile Ad hoc Network
A constant set in every station which tells how
long to hold a MSDU in queue before dropping
it in case it doesn’t get a chance to get
transmitted.
Mean Data Rate
MAC PDU
MAC Service Data Unit
A regulated broadcast which is meant for a
selected set of recipients.
It is the density of the network mentioned in
xii
OCTS
Omni-directional
antenna
ORTS
PC
PCF
PDA
PDF
PDU
PER
PIFS
QoS
QAP
QBSS
QSTA
RED
RTS
SIFS
SME
STA
Super frame
TBTT
TC
TS
TSPEC
terms of the average number of neighboring
nodes per node.
Omni-directional CTS
An antenna that radiates 360 degrees solid
angle. (In practice omni directional antennas
radiate 360 on the horizontal plane but only a
few degrees, (less than 10,) on the vertical
plane).
Omni-directional RTS
Point Coordinator
Point Coordination Function
Personal Digital Assistant (A hand-held
computing device)
Probability Density Function
Protocol Data Unit
Packet Error Rate
PCF IFS
Quality of Service
QoS enabled AP
QoS enabled BSS
QoS enabled STA
Random Error Detect
Request To Send
Short IFS
Station Management Entity
Station
Duration combining a CFP and a CP as
scheduled by the hybrid coordinator. Usually
the super frame size is the same as the TBTT.
Target Beacon Transmission Time
The time duration information in every beacon
telling other nodes about the time after which
an attempt to transmit the next beacon frame
will be done.
Traffic Category
Traffic Stream
A higher layer end to end traffic which has link
level QoS requirements (delay, minimum
bandwidth etc)
Traffic Specification
xiii
TXOP
VBR
VLAN
Wi-Fi
WLAN
WSTA
Transmission Opportunity
This is the fixed duration informed by the QAP
in the poll within which the polled station must
finish an atomic sequence of transmission.
Variable Bit Rate
The type of traffic that is encoded using
varying coding rate based on the information
content of the frame. Typically used for coding
video frames.
Virtual LAN
Wireless-Fidelity (A certification that ensures
interoperability of wireless devices with the
same certification.)
Wireless LAN
Wireless STA
Used in the QoS enhanced Station context
only.
1
CHAPTER 1
INTRODUCTION
1.1 OVERVIEW
This thesis presents medium access control (MAC) schemes to
handle traffic with QoS requirements in wireless networks. In particular, ad
hoc networks and wireless local area networks (WLANs) have been
considered. A thorough study of the literature in this has been carried out
and various mechanisms for QoS enhancements have been proposed.
Enhanced distributed access mechanism with directionality aware MAC has
been proposed for ad hoc networks.
Centrally coordinated WLANs have been considered for carrying
traffic with QoS requirements. Admission control, traffic shaping and policing
and scheduler mechanisms have been proposed for QoS support in these
networks.
These cases have been analyzed wherever appropriate and
extensive simulations have been carried out at every step. Results of these
have been dissected, compared and discussed.
2
1.1.1 Literature Review
Ad hoc networks have been studied for long and Mobile ad hoc
networks (MANET) in particular were proposed by Macker and Corson
(2001). The CSMA/CA based MAC scheme was proposed for ad hoc
networks and WLAN by the IEEE 802.11 standard (1999). The performance
of ad hoc networks with distributed coordination function (DCF) mode
specified in this standard was studied by Kamerman and Aben (2000). Most
MAC protocols proposed for ad hoc networks assumed omni directional
antennas at all the nodes. Sanchez et al (2001) studied the performance of
the IEEE 802.11 DCF in a network of nodes with directional antennas.
However, the MAC protocol and the scheduling mechanism did not exploit
the directional antennas at the nodes in the network. Work by Matthias and
Tse (2001) showed that in the absence of delay constraints, mobility of the
nodes enhances the throughput of ad hoc networks. However, in ad hoc
networks with QoS support, it is necessary to satisfy the delay requirements
of users. Thansis et al (2003) consider MAC protocol specifically designed
for directional ad hoc networks but this too does not deal with inherent QoS
issues. Some of the handshake techniques in their papers have been reused
here but with a difference in scheduling.
The IEEE 802.11a standard (2001) and the IEEE 802.11g draft
(2003) define how high data rates up to 54Mbps can be achieved at the
physical layer in WLAN. To exploit the availability of high raw data rate at the
physical layer, enhanced MAC layer protocol is required to support
applications with delay and throughput guarantee requirements. The IEEE
802.11e (2002) supplement was drafted to enhance the MAC of the IEEE
802.11 standard to support QoS in WLAN. This supplement formulates the
guidelines for QoS support and leaves a lot of space for the implementers to
add implementation specific functionality. Guidelines for scheduler design
and queue handling have been taken from this.
3
1.2 PROBLEM DEFINITION
High raw data rates (up to 54Mbps as per standards and twice
that in proprietary ways) at physical layer have become possible in wireless
communication. But for multimedia (voice, video and game) applications to
use these, it is necessary to design medium access control (MAC) schemes
that can support quality of service (QoS). In this thesis, we propose MAC
enhancements
to
improve
the
performance
of
wireless
networks.
Specifically, we address the MAC issues in wireless ad hoc networks and
wireless local area networks (WLANs) to support traffic with QoS
requirements.
1.3 ASSUMPTIONS
The following assumptions have been made regarding the
problem in hand while arriving at the solution. These assumptions define the
scope or the boundaries of the solution formulated.
Carrier sense multiple access schemes have been used
throughout. Near symmetry in uplink and downlink has also been assumed.
In case of directional antennas, the implication due to the direction-switching
mechanism has been considered only to the extent of a delay factor. For
obtaining positional information, the exact scheme has not been studied but
one specified in literature by Rahul et al (1999) can be used in lieu of a full
fledged geo positioning system. The MAC schemes also assume low mobility
of the individual nodes in the network.
4
1.3.1 Scope
The standard MAC guidelines used and assumptions presented
above make the solution suitable only for ad hoc networks with less number
of hops and for wireless local area networks with central coordination. In
either case, these schemes are not suitable for networks with highly mobile
nodes. Positional information is required which must be either provided
through a higher layer tunnel or an immediate routing protocol.
1.4 CONTRIBUTION IN THIS THESIS
Contributions made in this thesis can be split into two categories
viz., Ad Hoc networks and WLANs:

Wireless ad hoc networks with directional antenna at nodes are
considered and we propose a MAC protocol that uses the directional
antennas used by the nodes. We show that there is improvement in
throughput and delay performance due to this.

We then consider WLANs with centralized MAC and propose an
enhanced MAC to improve the delay and throughput performance of
the system so that the QoS requirements can be met.
1.5 THESIS ORGANIZATION
Chapter 2 deals with MAC enhancements for ad hoc networks.
We discuss how stationary nodes if at appropriate locations can contribute to
the enhancement in network performance. We also show how directional
antennas at nodes can be used to enhance throughput and delay
performance in ad hoc networks with suitably enhanced distributed MAC
scheme. The pre-final chapter deals with the specific problem of handling
QoS traffic in case of wireless local area networks (WLANs) where a central
coordinator is present. In each chapter the analysis and/or simulation results
5
have been discussed appropriately. The last chapter summarizes the
conclusions drawn from the work and, also shows the applications and future
scope of the same.
6
CHAPTER 2
MAC ENHANCEMENTS IN AD HOC NETWORKS
2.1 OVERVIEW
Ad hoc networks are topology-free infrastructure-less wireless
networks. The nodes might have asymmetric capabilities. This chapter
describes how directional antennas at nodes can be used to enhance
throughput and delay performance in ad hoc networks with enhanced
distributed MAC scheme.
2.1.1 Ad Hoc Networks
Though ad hoc networks are simply characterized by their
topology-free and infrastructure-less nature; all nodes in the network are
usually capable of routing. Each node participates in forwarding the packets
and thus the network is not dependent on any single node for its existence.
These nodes might be asymmetric in other aspects like power consumption,
antenna power, antenna type, buffer size, sensitivity and complexity of the
digital processing circuitry. These networks typically find applications in
military during war, rescue operations, sensor networking, component
tagging etc. Recently these are finding normal applications like connecting
Wireless-Fidelity (Wi-Fi) or Bluetooth certified mobile devices (laptops, cell
phones, PDAs, etc) without wire.
7
2.2 THE IEEE 802.11 STANDARD
The IEEE 802.11 standard (1999) specifies MAC protocols for
operation in ad hoc mode and centrally coordinated mode. The distributed
coordination function (DCF) is used for operation in the ad hoc mode.
2.2.1 Distributed Coordination Function
The DCF is based on carrier sense multiple access with collision
avoidance (CSMA/CA). The standard defines the common duration for
carrier sensing by the Clear Channel Assessment (CCA) function or DCF
Inter Frame Space (DIFS) at every node and also the contention window
ranges (CWmin, CWmax). The time gap between two packets in the
handshake sequence or an atomic operation, defined as Short Inter Frame
Space (SIFS), is less than DIFS. This prevents other nodes from capturing
the channel when one transmission (in the same area) is already going on.
All nodes that can hear each other and agree to join and form an
Independent Basic Service Set (IBSS). These nodes remain in synchrony
with a special management frame called the ‘Beacon frame’. This frame is
periodically generated by one of the nodes in the IBSS. Once a node
captures the channel, it can send data packet of at most one MAC Service
Data Unit (MSDU) which might be broken into fragments or MAC Protocol
Data Units (MPDUs) as specified by the variable Fragmentation Threshold. A
four-way handshake is optionally used.
A typical sequence (depicted in Figure 1) would be:

The node willing to transmit (source node, S1 in Figure 1) performs
carrier sensing.
ACK 2
FREE
MPDU
(2)
ACK 1
MPDU
(1)
CTS
BUSY
Backoff
RTS
8
time
S1
time
S2
time
S3
SIFS
SIFS
SIFS
SIFS
SIFS
DIFS
-------NAV------ ----NAV---
Figure 1. DCF mode of operation

If it finds the channel free for a DIFS duration, it may transmit.

To avoid collision situation, it back’s off in random multiples of a
constant time (Slot-time) chosen from the contention window (CW min
and CW max).

After the backoff countdown, a request to send (RTS) frame is sent by
the source node.

If the destination node (S2 in Figure 1) is ready to receive then it
initiates a clear to send (CTS) frame within a SIFS duration.

The source node initiates the sending of the Data frame (MPDU or
fragment) within a SIFS duration.

If the destination node properly receives the MPDU it responds with
an acknowledgement (ACK) packet.
In case of failure the source node backs-off again with a random number
chosen from a doubled contention window. Absence of ACK is treated as
9
collision in which case, the node has to carrier sense for an extended IFS
(EIFS).
The duration for which the transmission would go on is
continuously updated through the network allocation vector (NAV) field in the
handshake frames. The NAV information is used by other nodes (like S3 in
Figure 1) in the network to stay away from transmitting. When one
transmission is going on the same area, another transmission will lead to
collision. This combined with the handshake helps overcome the hidden
node problem to a good extent but creates more number of exposed nodes.
MSDUs in MAC queue for duration longer than a (configurable) constant
'maxMSDULifetime' are dropped from the queue. In addition to this a
retransmit limit can also be fixed.
For handling data packets a simple First Come First Serve (FCFS)
queue is used by all the nodes. This protocol allows fair-channel access on
the long-run, given the traffic generation characteristics and channel
condition due to environmental changes are even across all nodes in the
network. This doesn't differentiate nodes or traffic in anyway and hence it is
suitable for best-effort type of traffic only.
2.2.2 QoS Enhancement
The QoS enhanced MAC has the requirement that the protocol
data units (PDUs) that reach the MAC layer, from the higher layers, be
associated with certain traffic categories (TC), which is typically 8. Each TC
is mapped to one of four access categories (ACs) and the available resource
is distributed to these ACs based on the preset priorities for the ACs.
Prioritizing is achieved by assigning different values for various parameters
like the backoff window size and the inter-frame spacing in the basic
CSMA/CA based MAC.
10
2.2.3 EDCF Mode of IEEE 802.11e MAC
Though ad hoc networks do not support traffic streams with
guaranteed service, the available bandwidth can be distributed based on the
Traffic Category (TC); each TC having a different priority. The IEEE 802.11e
standard provides enhanced mechanism to handle TCs that are mapped to
one of the 4 Access Categories (AC). Each AC has different priority of
channel access. Multiple instances of the DCF (i.e., one for each AC) exist in
every node. Once a node captures the channel, it can transmit for a duration
termed as Transmission Opportunity (TXOP). Prioritization amongst ACs is
achieved by having different: values for:

Clear channel assessment (CCA) duration or arbitration inter frame
spacing (AIFS) per AC,

contention window ranges or CW min and CWmax per AC and

Transmission Opportunity (TXOP) per AC.
2.3 PROPOSED SCHEME
In this thesis, we propose a MAC for ad hoc networks that takes
into account, the directionality of the antennas at the nodes. We also study
the effect of having stationary or immobile nodes placed at strategic
locations. We consider a network in which the transmission ranges of the
nodes are comparable to the geographical area of the network.
Nodes with directional antennas can be used in ad hoc networks
to increase concurrent transmissions due to decreased interference. We also
consider power back off at the antennas. Power back off is defined as the
reduction in the transmission power in any specified direction. We consider
the usage of both fixed beam-width antenna arrays as well as variable beamwidth antenna arrays.
11
Mobility in ad hoc networks was shown to have resulted in an
enhanced throughput in the absence of delay constraints (Matthias 2001).
However, in ad hoc networks with QoS support, it is necessary to satisfy the
delay requirements of users. Therefore, it is of interest to selectively
immobilize nodes in an ad hoc network and study the delay performance.
The locations of the immobile nodes are fixed taking the following into
consideration:

The transmission ranges of all the immobile nodes are proper subsets
of the geographical area of the network.

For networks with a given probability distribution of node positions in a
given area, the immobile nodes must be placed following the same
distribution.

As a corollary, when nodes are distributed uniformly in the network
area, the immobile nodes must also be placed in a uniformly
distributed manner.
We show that an improvement of 50% in the delay performance and 5% in
the throughput performance can be achieved by combining the above
techniques, i.e., selectively immobilizing nodes in an ad hoc network and
exploiting the directionality of the antennas at the nodes. We also show that
the proposed enhancements to the MAC result in improved network
connectivity.
2.4 SYSTEM MODEL
We consider a flat circular geographical network area of radius 'R'.
Let fd(x,y) be the probability density function (pdf) of the position of the
nodes. The objective is to propose a MAC scheme and scheduling
mechanism
1. that takes into account the directionality of the antennas at the nodes,
and
2. by immobilizing a selected subset of nodes.
12
We make the following assumptions to carry out the required study.

There are N nodes in the network

Each node can transmit only to nodes which are at a distance lesser
than a specified distance limit, d0.

The contention mechanism is same as DCF for traffic without QoS
requirements, and the EDCF for traffic with QoS requirements.

As described by Rahul et al (2000), the nodes are assumed to know
their individual positions.

The RTS frames contain the MSDU expiry time i.e., the time relative
from the recent most Beacon frame, when the corresponding MSDU
would be dropped from the MAC queue if it does not receive service.
This is calculated considering the current time and the IEEE 802.11
parameter, MSDU lifetime. (Not part of the existing standard).
2.4.1 MAC Enhancements with Directional Nodes
We propose the following enhancements in the MAC for a network with
directional antennas at the nodes (depicted as state diagram in Figure 2):

Before the basic atomic sequence, (RTS/CTS/Data/ACK), every
source node with at least one MSDU in its queue contends to send an
omni directional RTS (ORTS) at maximum power. The ORTS contains
the position of the source node.

The destination node responds with a omni directional CTS (OCTS) at
maximum power. The OCTS also contains the position of the
destination node.

If the source does not receive an OCTS after ORTS,
o it may send another ORTS to the same node after a time
period corresponding to an extended inter frame space (EIFS)1,
or
1
As per the standard, after every erroneous transmission, the channel access should be
deferred for an EIFS period.
13
o the can send an ORTS corresponding to a different destination
node as indicated by another MSDU in its queue.
ORTS
1
OCTS
2
ORTS
4
3
Timeout
Timeout
OCTS
DRTS
Timeout
DACK
DCTS
5
DData
6
7
Figure 2. State Diagram of the Protocol

On successful reception of the OCTS, the source node uses the
information on the position of the destination and computes the
direction of the destination node. Similarly, the destination node
computes the direction of the source node from the ORTS.

Depending on the residual life time of the MSDU (i.e., the difference
between the maximum MSDU lifetime (maxMSDULifetime) and the
delay already experienced by the MSDU), the source node chooses
either to continue sending ORTS to other nodes or initiate
transmission of directional DATA (DData) to the destination

The scheduler at the directional nodes can decide to switch to
directional mode in any particular direction and initiate reception using
Directional Request To Receive (DRTR) after which directional atomic
sequence (DRTS/DCTS/DData/DACK) can go on. It shall select to
orient to the direction from where maximum traffic is coming in terms
of sum of requests.
As illustrated by the simplified state diagram, when in state 3, the
scheduler decides whether to send another ORTS or a DRTS based on the
queue status and residual lifetime of the packets for which DCTS has been
14
received. Without moving to a state greater than or equal to state 5, the node
can not hold the channel for more than a MSDU transmission time.
2.4.2 QoS Enhanced MAC with Directional Nodes
In a network with QoS parameter specifications for the traffic, we
consider 8 traffic categories (TCs), which, in turn, are mapped to 4 access
categories (ACs). Weights are assigned to the ACs depending on the QoS
requirements. The only additional change in the protocol is that, the
scheduler selects to orient to the direction in which maximum weighted traffic
is expected to be transmitted. The maximum weighted traffic is computed
from the weights assigned to the ACs.
2.5 PERFORMANCE STUDY
We study the throughput and delay performance of the proposed
MAC in ad hoc networks for the following scenarios:

Omni-directional nodes with basic CSMA/CA based MAC

Directional nodes with enhanced scheduler based MAC

Directional nodes with EDCF for QoS traffic handling

Directional nodes with enhanced scheduler based MAC for QoS traffic
handling
The performance of the network with omni directional antennas at the nodes
are provided for comparison.
We study the goodput defined as ‘the total number of bits of data transmitted
successfully by the MAC layer per unit time’. Maximum goodput of a
particular topology corresponds to the traffic condition that results in
maximum bits transfer in MAC.
15
2.6 RESULTS AND DISCUSSION
Simulations were carried out with the specified parameters for an
ad hoc network with increasing number of nodes within a 1000m* 1000m
area. We define ‘goodput’ as the total number of bits of data transmitted
successfully by the MAC layer per unit time. Maximum goodput of a
particular topology corresponds to the traffic condition that results in
maximum bits transfer in MAC. As shown in the graph (Figure 3), we
observer that as we increase the network density (number of nodes per unit
area; where the unit are is the area of coverage of one omni-directional
node), the delay performance improves.
Delay corresponding to Maximum goodput (msec)
Effect of immobility and directionality on delay
600
All mobile nodes
10% immobile nodes
All directional nodes
All directional and 10% immobile nodes
500
400
300
200
100
0
2
3
4
5
6
7
8
9
Network density: Average number of neighboring nodes per node
10
Figure 3. Delay Performance with increasing Network Density
The curve corresponding to all mobile nodes indicates the base
performance when all nodes are mobile and omni-directional (using basic
16
IEEE 802.11 protocol). Though at less network density the variation in delay
is not prominently visible, we observed up to 50% drop in delay when the
network has all directional nodes with 10% of them immobilized. This directly
gives better support for traffic with delay based QoS requirements.
Figure 4. Performance of ad hoc MAC schemes
In graph (Figure 4) we see that the maximum goodput is high for
less density of the network and is sustained even at higher network densities
with the enhanced scheduler with QoS handling capabilities. We also
observe that it 16% to 40% better throughput at various network densities.
One of the major causes for the increase in the overall throughput
of the network is due to the possibility of frequency reuse across the network.
Frequency reuse ensures concurrent transmissions at different regions of the
network. The graph (Figure 5) shows the maximum number of neighbors per
node (averaged in time) that fall in the directional beam of that node’s
antenna. This is directly related to more frequency reuse in the network when
less neighbors are affected per beam. We observe that power backoff helps
17
keep the number of affected nodes (called as exposed nodes) to the
minimum even for high network density.
Figure 5. Effect of Power-backoff
Thus we conclude that for an ad hoc network with low mobility,
use of directional antennas with the enhanced MAC with QoS capabilities,
the QoS requirements for typical voice/video traffic can be met.
18
CHAPTER 3
QOS IMPLEMENTATION ON WLAN
3.1 OVERVIEW
This chapter deals with the specific problem of handling QoS
traffic in case of wireless local area networks (WLANs) where a central
coordinator is present. Wireless local area networks (WLANs) are network of
computers or other devices that can communicate with other nodes either
using a central coordinator or distributed coordinator. The distributed
coordination is the same as ad hoc mode detailed in the previous sections. In
central coordination, there is a special node termed as access point (AP).
3.2 EXISTING TECHNOLOGY
In WLANs the MAC deployed is typically based on the IEEE
802.11 standard (1999). Nodes can operate in a distributed manner using
the DCF or in a centralized manner using the point coordination function
(PCF). In the PCF mode, the point coordinator that resides in the AP does
the central coordination. The enhanced version of PCF namely hybrid
coordination function (HCF) in the IEEE 802.11e draft (2002) defines MAC
extensions to support QoS traffic on the standard IEEE 802.11 based
networks.
19
3.2.1 PCF Mode of IEEE 802.11 MAC
In PCF mode, the access point AP is given preferential access to
the medium. This is achieved by sensing the carrier to be free for duration of
PCF inter-frame space (PIFS), which is shorter than DIFS but longer than
SIFS.
BUSY
Contention Free
Repetition interval
Contention
Contention
Contention Free
Free
time
PIFS
PIFS
AP
Super Frame
Figure 6. CFP, CP and Super-frame
The AP may hold the channel in the contention free mode for a
contention free period (CFP) maximum duration after which contention based
transmission takes place (as shown in Figure 6). It can gain access again at
the end of target beacon transmission time (TBTT) or contention free
repetition interval. Thus a contention free period (CFP) and contention period
(CP) alternate. In the CFP, the point coordinator (PC) in the AP forwards any
multi-cast packet and polls the associated wireless stations for transmission
and reception in a round-robin fashion.
20
3.2.2 HCF Mode of IEEE 802.11e MAC
The QoS mechanisms in IEEE 802.11e draft (2002) specified for
the centralized mode of operation is called as the hybrid co-ordination
function (HCF), which provides a mechanism for QoS enhanced STAs
(QSTAs) associated with a QoS enhanced AP (QAP). A QSTA obtains
transmission opportunities (TXOPs) for any of these mechanisms. Within one
TXOP duration, a wireless station (WSTA) may transmit as many MPDUs as
might fit in.

HCF Controlled Channel Access: This mechanism involves a point
coordinator called the hybrid coordinator (HC). It gains channel
access with better preference using PIFS sense duration because
SIFS < PIFS < DIFS or AIFS of any AC. Traffic streams (TSs) may be
created on the wireless link. QSTA may negotiate regarding the traffic
specifications (TSPECs) the QAP must try to provide for the TS with
the HC. The HC schedules traffic during CFP and CP to meet the
requirements of TCs and all accepted TSs.

Admission Control: Resource allocation requests for new TS for
which proper schedule can not be created due to lack of resources as
computed from the link conditions and TXOP budget by the scheduler
are rejected.

Buffer Management: Random Early Detect (RED) algorithm (Braden
et al 1998) can be used for EDCF based traffic. This maintains small
queue size and is suitable for low latency applications.

Traffic Shaping and Policing: Since the input traffic is highly bursty
in nature, it must be shaped and policed before scheduling. Traffic not
belonging to any TS may be rate-limited by using a simple leaky
bucket. However for TSs the aggregate throughput and delay
characteristics of all the admitted TSs should be used as a for traffic
shaping.
This
can
be
achieved
by
the
twin-token
bucket
21
implementation. The decision of token-bucket parameters is based on
scheduler explained in next section.
3.3 SYSTEM MODEL
In this section, we describe the algorithmic implementation of a
system conforming to the IEEE 802.11e draft (2002) which can be ported
either as hardware or software along with other layer two services. The
scheduler must be able to adapt to the channel variations and provide
optimal performance. It must interact properly with the other parts of the
system in establishing queues of shaped and policed stream of packets to be
scheduled.
3.3.1 MAC Scheduler Enhancements
The interaction between different blocks in the system at the QAP
is shown in Figure 7. It shows the flow of packets as it enters the QAP. Only
the downlink (QAP to WSTAs) situation has been depicted. A similar set of
blocks exists for uplink (WSTAs to QAP) Packets entering the down link
buffer are first of all classified based on whether or not a TS has been
created.
The ones for which, TS has been created are sent to the Twintoken bucket based traffic shaper, the others are sent to a Random Early
Drop (RED) based queue. The shaped up traffic is fed to the TS buffers while
the other is classified based on AC and is fed to the 4 AC buffers. The HCF,
common to uplink, downlink and crosslink (WSTA to WSTA direct link in
contention free mode) has two schedulers.
The TS scheduler generates polled TXOPs for the admitted TSs.
Under EDCF, scheduling within every AC is First In First Out (FIFO, except
22
for timeout based packet drops). At any given time instance, only one of the
TSs or ACs (of/for any WSTA) that has obtained a TXOP either by
contention or by poll, occupies the channel. The function of the individual
blocks, related to the TS scheduler is explained, wherever required. The
scheduler closely interacts with the admission controller and, traffic policer
and shaper to optimize the performance.
Traffic Streams
(variable
number)
Rate,
size control
Input
Queue
Admission
control
HCF
TS
Scheduler
EDCF
Channel
Twin Token
Bucket
FIFO per AC
Drop Rate
Cont rol
RED Queue
EDCF
Parameters
Access
Categories (4)
AC=0,1,2,3
Packet Path
Control Information Path
Figure 7. System - Block Diagram
3.3.2 Design of Scheduler
The scheduler must allocate resources such that under controlled
operating conditions, all WSTAs with admitted TS are offered TXOPs that
satisfy the service schedule. The corresponding admission control is based
on the parameters (per traffic stream) as shown in the table (Table 1).
The input for the scheduler to generate a service schedule is the
TSPEC (mentioning Mean Data Rate, Peak Data Rate, Delay Bound, etc.) of
each TS to be admitted. The scheduler must try to generate TXOPs at
23
definite intervals for finite duration computed from the requirements
mentioned and generate corresponding polls. The remaining resource can
be shared by the WSTAs through EDCF mechanism.
Table 1. TSPEC based Admission Control
TSPEC
parameter
Continuous CBR Traffic Bursty traffic Unspecified
time QoS
or non-QoS
traffic
traffic
Nominal MSDU Specified
Specified
Unspecified
Don’t Care
Size
Minimum
Specified Nominal MSDU Mean Data
Don’t care
Service
size / Mean Rate / Nominal
Interval
Data rate
MSDU size
Maximum
Specified
Delay bound / Delay bound /
Don’t Care
Service
Number of
Number of
Interval
Retries
Retries
Inactivity
MUST BE SPECIFIED
interval
Minimum Data
Must be
Same as Mean Unspecified
Don’t care
Rate
specified if
Data Rate
peak data rate
is specified
Mean Data
Specified
Specified
Don’t care
Don’t care
Rate
Maximum
Unspecified
Unspecified
Specified
Don’t care
Burst Size
Minimum PHY
Must be
Equal to mean
Don’t care
Don’t care
Rate
specified if
Data Rate
minimum data
rate is
specified
Delay Bound
Specified
Specified
Don’t care
Unspecified
Surplus
Must be specified if delay and jitter bounds are Don’t care
Bandwidth
present
Allowance
Scheduler was designed such that QAP generates schedules and
admits Traffic Streams based on effective bandwidth (Effective Mean Data
Rate or EMDR) estimation calculated from Packet Error information. For
ease of design and analysis, it is assumed that transmission is always at the
24
same data rate (54Mbps) and that only one QBSS is present. Set rate of
token filling in Twin Token bucket is varied accordingly (Figure 8).
r1 tokens/s
r2 tokens/s
Overflow
Overflow
s1
s2
Token
Addition
Received
traffic
Dropped
packets
Token
Addition
Peak-rate
limited
Shaped
traffic
Dropped
packets
Figure 8. Twin Token Bucket Implementation
Any 802.11 implementation offers more than one data rate. The
mechanism for rate adaptation based on channel characteristics is not
mentioned. Many use schemes based on Received Signal Strength
measurement (Javier et al 2002). If the scheduler mentioned in the section
above is used, it will only get a rough estimate of EMDR. To accommodate
rate adaptation information, obtained from Station Management Entity,
(SME), we modify the algorithm mentioned in previous section.
3.3.3 Enhanced Scheduling Algorithm
The scheduler must try to generate Service Schedule for each TS
such that the requirements mentioned are met. That is, the scheduler must
allocate TXOPs at some definite intervals for definite duration and generate
corresponding polls in the CFP (. The remaining resource can be shared by
the WSTAs through EDCF mechanism.
25
BUSY
Contention Free
Repetition interval
Contention
Contention
Contention
Free
Free
time
PIFS
PIFS
AP
Super Frame
Figure 9. Alternating CFP and CP
Scheduler can be designed such that QAP generates schedules and admits
Traffic Streams based on effective bandwidth (Effective Mean Data Rate or
EMDR) estimation based on Packet Error.
Step 0: EMDR is initialized to maximum data rate supported by the physical
layer and control parameter,  to zero.
EMDR = 54 Mbps
(3.1)
0 = 0
(3.2)
Step 1: For every packet transmitted control factor, n (which is the value of
 updated with transmission of nth packet) is calculated as shown:
n = n-1 + x
(3.3)
where, x n = 1 if successful, -1 if unsuccessful
Success or failure is known from the reception of ACK. The protocol
assumes no usage of Group ACK. With Group ACK delayed updation will
only be possible. (This condition has not be considered for simulation studies
also).
Step 2: Over a large time scale, EMDR is given by (equation 3.4),
26
1
(3.4)
EMDR = 54 *
1+ e-n
or as shown in Figure 10.
EMDR (Mbps)
54--------
27--------n
-infinity
+infinity
0
Figure 10. EMDR (Estimated Mean Data Rate) Curve
In implementation

since we cannot go for n ranging to infinity,

since n should itself adapt based on channel condition,
n is upper limited to a constant (+/- 127) and EMDR is made a function of ’
which is a function of deviation factor n, (initialized to 127), updated
periodically with every packet transmission.
’n (n) = 127* n/n
(3.5)
Where, n is given by
n =
n-1 - 1
if x n = x n-1
127
if x n = x n-1
(3.6)
n is reset to 127 and n to 127 every time n reaches zero.
Therefore, EMDR is given by, (equation 3.7)
1
(3.7)
EMDR = 54 *
1+ e-n’(n)
Step 3: Aggregate the mean and peak data rate requirements mentioned
through TSPEC for each admitted Traffic Stream.
27
Step 4: Set rate of token filling in second bucket in Twin Token bucket (r2) to
estimated EMDR (Table 2).
Table 2. Twin Token - Bucket Parameters
Token filling rate
(Constant)
Bucket Size
Token extraction
rate
Major purpose
Bucket 1
r1 = Peak Data
Rate
s1 = 1 token (mimic
leaky bucket)
Rate limiting
Bucket 2
r2 = Mean Data
Rate
s2 = Maximum
Burst Size tokens
At most Peak Data
Rate
Burst size limiting
Step 5: Admit Traffic Streams until aggregate mean data rate of existing
traffic streams does not exceed EMDR, reject otherwise.
Step 6: Update using step 1 to 4 unless an unhandled exception occurs. On
exception revert to step 0.
While admitting the traffic stream, the slice of time required for the
traffic stream is also calculated. This is now generated as TXOP (Figure 11)
within the CFP. TXOP gives predefined time to the WSTAs unlike the PCF
where the channel holding time of any station once the poll has been
accepted is not dictated by the access point (only a common upper limit
exists).
28
ACK
MPDU (1)
Of MSDU (2)
ACK
MPDU (2)
Of MSDU (1)
ACK
CF-Poll
MPDU (1)
Of MSDU (1)
One MSDU
time
11
TXOP
time
11e
(i)
TXOP
Time
SIFS
SIFS
SIFS
SIFS
SIFS
SIFS
11e
(ii)
Figure 11. TXOP generated by Scheduler in HCF compared with basic PCF
3.4 PERFORMANCE STUDY
Only the BSS (Basic Service Set) type of simulation topology has
been taken into consideration. Since we consider the enhancements
provided by IEEE 802.11e, we have a QBSS (QoS enabled BSS). A single
QAP connecting to many WSTAs has been taken up. The QAP is connected
to the Ethernet interface too.
29
3.4.1 Simulation
Simulations were carried out with nodes implementing the
standard HCF based coordinator with enhanced scheduling scheme. The
system simulated consists of one QoS enabled access point (QAP) with 8
nodes (QoS enhanced wireless stations). No ‘direct-links’ or ‘group/ bulk/
burst –acknowledgement’ have been considered though they are possible as
per the standard HCF protocol.
The table (Table 1. TSPEC based Admission Control) gives us the
details of the parameters taken for AC specific parameters. Simulation of this
with parameters for Best-Effort, Video Probe, Video and Voice as the 4
Access Categories was considered. The weights taken were 1:2:3:4. This is
the performance without explicit traffic stream creation by the management
layer. A QBSS with one QAP and 8 WSTAs was simulated. A 50% of the
total traffic was generated from the QAP and the remaining 50% from the
WSTAs. For EDCF traffic generation belonging to the 4 different ACs, the
parameters, (shown in chart (Figure 12)) were used. For ease of simulations,
accumulated bursty traffic of 512Kbps of AC=3 and 512Kbps of AC=1
requiring a combined Mean Data Rate of 1Mbps has been used per TS. To
alter the QoS parameters, (CW min[AC], CWmax[AC], TXOP[AC]), EDCF
parameters chosen are the same as specified in the standards as default.
Physical layer assumed is as mentioned in the IEEE 802.11a
standard (2000) Simulations were carried out for two different channel
conditions viz., ideal and high bit error rate (BER=10-4) resulting in varying
Packet Error Rate (PER).
30
Traffic Type
Access Category
Non QoS
QoS
Traffic
Traffic
Best Effort
Video Probe
Video
Audio
AC=0
Exponential
AC=1
Pareto with cutoff
(1.7, 1864bits, 12000bits)
AC=2
Pareto with cutoff
(1.1, 652bits, 12000bits)
AC=3
CBR
32 & 64 Kbps
Figure 12. Parameters for generation of traffic of 4 ACs
31
3.5 RESULTS AND DISCUSSION
In this section we discuss the results as found from the study.
Effective Goodput for 4 ACs in EDCF
Effective Goodput (Mbps)
12
10
8
6
4
AC=0 Best-effort
AC=1 Video-probe
AC=2 Video
AC=3 Voice
2
0
0
5
10
15
20
25
30
35
40
45
Input Traffic (Mbps)
Figure 13. Variation in effective goodput with traffic
The graph (Figure 13) illustrates the effective goodput of the
higher AC increasing linearly with incoming traffic at the cost of lower ACs.
In this graph (Figure 14), we study the effective goodput of the two
protocol schemes namely, HCF contention free access and EDCF deploying
the scheduler discussed earlier. We observe that the performance is better
when HCF contention free access is used over EDCF by about 5% at
maximum goodput.
32
Effective Goodput for HCF-Contention Free Channel
Access, EDCF
Effective Goodput (Mbps)
30
25
20
15
10
5
HCF-Contention Free Channel Access
EDCF
0
0
5
10
15
20
25
30
35
40
45
Input Traffic (Mbps)
Figure 14. Behavior of EDCF and HCF
The graph (Figure 15) illustrates the number of 1Mbps streams or
roughly the throughput in terms of Mbps achievable when a channel with
high bit error rate (10-4) is used. The graph includes the case when packet
error rate (PER) is estimated and also when rate adaptation information is
used.
We observe that the adaptive scheme is able to provide service
schedule of TXOPs for Traffic Streams and is able to support equivalent
number of Traffic Streams (TSs) even in bad channel condition. From graph
(Fig 8) it can be seen that throughput performance improves when rate
adaptation information is used for EMDR estimation by the scheduler in HCF.
The performance improvement is significant particularly when BER of the
channel is high. This can be attributed to the fact that the algorithm comes
into effect when estimation of packet error rate is done along with rate
adaptation. In both the cases, trials to admit more TSs than indicated in the
graphs resulted in rejection by the Admission Control procedure.
33
Figure 15 shows the average throughput performance of the
adaptive scheduler in generating service schedules for both

Traffic Streams in Contention Free Period (CFP) and

the four Access Categories in Contention Period (CP)
We observe that the overall throughput is a bit better for contention free
traffic (TSs) due to less contention overheads.
Figure 15. Traffic Streams supported for different peak data rate deviation on
a non-ideal channel
We observe from (Figure 16) that presence of EDCF does not degrade the
performance of the scheduler for Traffic Streams as the HCF allocates only
the bandwidth remaining after TS allocation for EDCF. Such a centralized
scheduling scheme performs well when bandwidth is shared for EDCF
operation due to the higher access priority of HC in QAP (using PIFS). Thus
it can support applications with QoS guarantee requirements on the wireless
link. Optimization of scheduler for polling in CFP when reserved Traffic
Streams are not established has not been considered.
34
Figure 16. Traffic Streams supported and EDCF Throughput for a network
when scheduler in HCF handles TXOPs of both contention free and
contention based traffic.
Simulation was conducted to compare the enhanced scheduling
scheme results with the round robin based scheduling scheme. The same
topology and input traffic pattern (discussed in Simulation section) was used
for both the schemes. This graph (Figure 17) compares the goodput versus
delay for various schemes namely,

EDCF

HCF with basic scheduling based on Round Robin (RR)

HCF with enhanced scheduling scheme designed above (ES)
We observe that the delay performance for EDCF starts with a high delay of
43ms for a system goodput of 5Mbps and increases non-linearly with time to
132ms for 25Mbps. Though HCF with simple round-robin scheduling
performs similarly for low goodput, it performs relatively better for high
35
goodput. But in any case, HCF with the enhanced scheduling scheme gives
much lower throughput.
Figure 17. Goodput v/s delay for various schemes.
Compared to the round-robin scheme, enhanced scheduling
scheme provides 66% lower delay for low data-rates (goodput = 5Mbps) and
a 75% for high data-rates (goodput = 25Mbps).
The parameters shown in Table 1 describe distributional
properties of the amount of information generated per burst. Burstiness
defined as peak to mean bandwidth ratio is an important parameter of the
multimedia traffic. The co-efficient of variation (ρ) defined as,
ρ=
σ
(3.8)
μ
Where, σ is the standard deviation of the traffic from its mean μ.
36
Typical value of ρ for a VBR video frame (packet at application
layer) size is 0.23 and that of the VBR video burst size is 0.31. For CBR, the
standard deviation in the frame size is zero but the variation is contributed
due to the varying burst size. The following simulation was carried out with a
constant co-efficient of variation for the burst (set at 0.31, which is the typical
value for video applications) but with a varying frame co-efficient.
Figure 18. Co-efficient of variation versus delay plot.
We observe from the graph (Figure 18. Co-efficient of variation
versus delay plot.) that the delay for even minor increase in the variation of
the frame size results in drastically high delay for a weighted round-robin (RR
in the plot) based scheme. At typical value of ρ = 0.23 for frame in a video
VBR, the delay offered by the RR based scheme is above a 100ms but for
the enhanced scheduling algorithm (ES in the plot), the delay is below 25ms.
37
This directly gives support for QoS traffic in terms of handling bursty traffic
from VBR sources.
38
CHAPTER 4
CONCLUSION AND FUTURE SCOPE
4.1 CONCLUSION SUMMARY
From the study, we conclude that usage of directional antennas
with appropriate MAC protocol can help enhance performance of ad hoc
networks and can help offer better QoS guarantees. Though at less network
density the variation in delay is not prominently visible, we observed up to
50% drop in delay when the network has all directional nodes with 10% of
them immobilized. This directly gives better support for traffic with delay
based QoS requirements.
We also conclude that when a scheduler with rate estimation
coupled with incoming traffic stream shaping and admission control (adaptive
scheduler) are used, performance can be improved in the centralized
wireless networks. This when combined with IEEE 802.11e protocol is
deployed can help handle both traffic with differentiated QoS requirements
(multiple Access Categories) and integrated requirements (reserved Traffic
Streams). We can admit traffic streams summing up to 25Mbps when the
physical layer raw data-rate is 54Mbps. Compared to the round-robin
scheme, enhanced scheduling scheme provides 66% lower delay for low
data-rates (goodput = 5Mbps) and a 75% for high data-rates (goodput =
25Mbps). Also we have been able to show the better performance of the
39
enhanced scheduler in handling brusty traffic with high co-efficient of
variation in the frame size (typical to video VBR traffic).
4.1.1 Applications
Applications of the ad hoc case include hotspots, campus, office
and outdoor networks with user categorization or different access priorities.
The complete centrally coordinated QoS enhanced system is best suited for
any indoor application where an Access point can be set up. Especially for
offices with VLAN etc. This is the best suited for networks carrying
multimedia dependent applications like audio/video streaming, audio/video
conferencing, gaming, sensor monitoring, remote equipment controlling etc.
4.1.2 Future Scope
This work can be extended to integrate with other systems based
on different standards including Hiperlan/2, GSM/GPRS and UMTS. The
current scheme is not designed with high mobility applications or several hop
ad hoc networks in the design phase. The scheduler design can be extended
considering the distance variation and high mobility possibility.
40
APPENDIX 1
ASSIGNMENT OF TYPE OF SERVICE
In this section we take up case studies of particular networks with
bandwidth (QoS) requirements and see how the QoS categorization would
function with EDCF based QoS.
Case 1
Assume the total available bandwidth (in long run) on an average
to be 10Mbps.

Let there be 5 users, each with 100KBps (or 100*8=800Kbps)
bandwidth requirement.

Let there be 15 users, each with 25KBps (or 25*8=200Kbps)
bandwidth requirement.

Let there be 25 users, each with 10KBps (or 10*8=80Kbps) bandwidth
requirement.

Let there be 25 users, each with 5KBps (or 5*8=40Kbps) bandwidth
requirement.
The following table shows the bandwidth requirement per user
and the total requirement in the system.
41
Table 3. AC association - Simple case (Case 1)
User Type
(αβγδ)
Number
of
users
Alpha (α)
Beta (β)
Gamma
(γ)
Delta (δ)
5
15
25
Bandwidth
per user
(in KBps)
100
25
10
Bandwidth
per user
(in Kbps)
800
200
80
Total
bandwidth
for this
user type
(in Kbps)
4000
3000
2000
Total
bandwidth
for this
user type
(in Mbps)
4
3
2
25
5
40
1000
1
Total bandwidth requirement` in the system (in Mbps) 10
The total requirement of the user type decides the access
category the user belongs to. For instance, in the mentioned case, with users
of type α, β, γ and δ,

α maps to AC3, β to AC2, γ to AC1, δ to AC0 respectively

the bandwidth requirement ratio is AC0:AC1: AC2:AC3 = a:b:c:d =
1:2:3:4
The corresponding EDCF parameters are calculated for this ratio.
Case 2
To illustrate the fact that the higher AC is allotted for the user type
that has higher total bandwidth requirement than the individual requirement
the following case is studied.
Similar to the previous case, the following table shows the
bandwidth requirement per user and the total requirement in the system.
Here the overall requirement per user type is not in any particular order. It is
like in a typical real life scenario.
42
Table 4. AC Assignment – Complex Case (Case 2)
User Type
(αβγδ)
Number
of
users
Alpha (α)
Beta (β)
Gamma
(γ)
Delta (δ)
1
20
40
Bandwidth
per user
(in KBps)
100
25
10
Bandwidth
per user
(in Kbps)
800
200
80
Total
bandwidth
for this
user type
(in Kbps)
800
4000
3200
Total
bandwidth
for this
user type
(in Mbps)
0.8
4
3.2
50
5
40
2000
2
Total bandwidth requirement in the system (in Mbps) 10
The total requirement of the user type decides the access
category the user belongs to. For instance, in the mentioned case, with users
of type α, β, γ and δ,

α maps to AC0, β to AC3, γ to AC2, δ to AC1 respectively

the bandwidth requirement ratio is AC0:AC1: AC2:AC3 = a:b:c:d =
0.8:2:3.2:4
Though the α type users who are seemingly higher priority users
have been given less part of the channel, the total number of users being low
in that category justifies the loss. Thus every individual α user’s bandwidth
requirement is met. So is the case with the other users.
43
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Publications out of this Work
1. Rajesh S., Vijayalakshmi K., Srikanth S. and Vaidehi V. (2003), 'Capacity
and Qos enhancement of ad hoc networks with intermittent smart
directional nodes', Proc. 9th NCC, India, pp. 35-39.
2. Rajesh S., Srikanth S. and Sethuraman M. (2003), 'QoS Algorithms for
IEEE 802.11e Implementation', The 9th APCC, Malaysia.