Comparison of WiMAX Uplink Schedulers for Fixed
and Mobile Environment
Deepak Gyanchandani, Anjulata Yadav, Jayadipti Lal
Department of Electronics and Telecommunication, SGSITS Indore-452003 (M.P.), India
deepakgyanchandani2@gmail.com, yadawanjulata@rediffmail.com, jayadiptilal@yahoo.co.in
Abstract— Worldwide Interoperability for Microwave Access
(WiMAX) based on IEEE standard 802.16 provides wireless
services in Metropolitan Area Network (MAN) at gross data rate
of 1 Mbps - 75 Mbps. In WiMAX Service Classes, Scheduling
and Call and Admission Control (CAC) are defined to provide
Quality of Service (QoS) to applications such as voice, video and
data. Scheduling is the main component of QoS management of
IEEE 802.16 that helps assure QoS to various service classes.
These scheduling algorithms are compared on the basis of
performance metrics average throughput, average end to end
delay and average jitter. This paper aims at comparing various
uplink scheduling algorithms for voice, video and data traffic in
a fixed and mobile WiMAX network.
Keywords— IEEE 802.16, WiMAX, Qualnet, QoS, Scheduling
Algorithms
I. INTRODUCTION
WiMAX is a Broadband Wireless Access (BWA) which
aims at covering wide geographical area along with high data
rates [1]. IEEE 802.16 gives information about QoS
requirements for different service classes but does not give
any standard as how to achieve these QoS. This part of IEEE
standard has been left for researchers and service providers.
IEEE 802.16-2004 forms basis of first WiMAX which aims at
providing services to fixed applications. Next variant IEEE
802.16-2005 also known as mobile WiMAX provides
mobility support and handover. QoS ensures required
treatment to applications by providing sufficient bandwidth,
reducing delay and minimizing jitter and packet loss. Various
multimedia applications like Voice over Internet Protocol
(VoIP), Video Streaming and data traffic have different QoS
requirement. High data rate applications like VoIP, video
streaming require reduced average end to end delay and
average jitter as their major QoS requirement but for low data
rate applications like data traffic better throughput is the major
QoS requirement [9].
Two types of network modes are defined in WiMAX –
mesh mode and Point to Multipoint (PMP) mode. In PMP
there is a centralized Base Station (BS) through which
different Subscriber Stations (SS) communicate with each
other, whereas in mesh mode no concept of centralized BS is
involved and all SS communicate with each other directly.
The IEEE 802.16 standard Media Access Control (MAC)
layer provides QoS differentiation for different types of
applications that might operate over 802.16 networks, through
five defined service class types. They are Unsolicited Grant
Service (UGS) which is designed to support fixed-size data
packets at a constant bit rate (CBR) like VoIP, Real-time
Polling Services (rtPS) which is designed to support real-time
service flows, such as MPEG video that generate variable-size
data packets on a periodic basis, Non-real-time Polling
Service (nrtPS) which is designed to support delay-tolerant
data streams, such as File Transfer Protocol (FTP), Best
Effort(BE) which is designed to support data streams such as
Web browsing that do not require a minimum service-level
guarantee and Extended-real-time Polling Service (ertPS)
which is designed to support real-time applications such as
VoIP with silence suppression, that have variable data rates
but require guaranteed data rate and delay [10].
WiMAX scheduling algorithms like Weighted Round
Robin (WRR), Weighted Fair Queuing (WFQ), Strict Priority
(SP) and Round Robin (RR) are evaluated in [9] to show the
performance of these scheduling algorithms for different QoS
requirements but for only fixed network. Performance of
various scheduling techniques in order to fulfil QoS
requirements for different applications and to develop new
algorithm have been analysed in [3] by varying
Downlink/Uplink (DL/UL) ratio. Comparison of behaviour of
various homogeneous and hybrid algorithms is done in [6] but
focussing only on traffic of rtPS service class. This paper
performs evaluation of various schedulers for both fixed and
mobile network considering traffic of various classes by
varying load and applications.
The remaining paper is organized as follows: Section 2
discusses about different uplink schedulers compared in this
paper. Section 3 gives overview about Simulation parameters
and scenario along with result analysis. Section 4 discusses
about conclusion and future work.
II. UPLINK SCHEDULING ALGORITHMS
Scheduling algorithms are of utmost importance in
WiMAX network in order to satisfy and enhance the QoS
requirements of its users, while effectively utilising its
available resources. Three schedulers are employed in
WiMAX, uplink and downlink scheduler at BS and and uplink
scheduler at SS. Uplink scheduler at BS decides allocation of
channel among users and the order of transmission on their
data units whose number is decided by Downlink scheduler at
BS. The Uplink scheduler at SS requests for Bandwidth (BW)
and transmits its data to BS. BW is allocated in two ways
either allocating bandwidth to each connection which is called
Grant Per Connection (GPC) or allocating bandwidth to each
Subscriber Station which is Grant Per Subscriber Station
(GPSS).
Schedulers are classified as channel aware schedulers and
channel unaware schedulers. Channel unaware schedulers are
further classified as homogeneous schedulers and hybrid
schedulers. Channel aware schedulers are those schedulers
which depending upon current Signal to Noise Ratio (SNR)
value of channel decide its Modulation and Coding technique
according to Adaptive Modulation and Coding (AMC)
scheme. On the other hand Channel unaware schedulers are
those which make no use of channel state conditions. Hybrid
Schedulers are mainly composed of various Homogeneous
Schedulers.
This paper compares following homogeneous schedulers:
Fig. 2 Flow Chart of Weighted Fair Queuing Algorithm
Fig. 1 Flow Chart of Round Robin Algorithm
A. Round Robin Algorithm
This is the simplest type of scheduling algorithm. It assigns
equal transmission time to each connection without taking into
account any priority or queue length. Advantage of this
scheduling algorithm is that it provides fairness into network
as each connection gets a chance to transmit one by one, but it
has a disadvantage that it also assigns bandwidth to
connections which are idle.
B. Weighted Fair Queuing Algorithm
In this type of scheduling algorithm each data flow has its
own queue which is of First in First out (FIFO) type and then
weights are dynamically assigned to each queue. Depending
upon this weight resources are made available to each
connection. This algorithm introduces partiality into network
as queues with large weights or greater number of data
packets may utilize maximum bandwidth. Moreover it also
has a complexity issue.
Robin for mobile nodes using Qualnet 4.5 to investigate their
suitability for particular application.
The scenario selected for simulation is a PMP network
consisting of one BS and SS's varying from 10-60 with 18
data flows comprising of ertPS, rtPS and nrtPS type traffic.
Fig. 4 WiMAX Scenario
Table 1 gives simulation parameters for the scenario.
TABLE I
SIMULATION PARAMETERS
Parameters
Frame Structure
Node Placement
Simulation Grid Size
Simulation Time
Number of SS
Operating Frequency
Transmission Power
Mobility Speed
Network Bandwidth
Fig. 3 Flow Chart of Strict Priority Algorithm
C. Strict Priority Algorithm
In this algorithm each connection has an additional priority
factor attached with it and depending upon this priority value
services are provided to connections that is data flow with
highest priority is served first. Also if two connections have
same priority then they are served according to their order of
arrival in queue. Usually the order of priority is UGS, ertPS,
rtPS, nrtPS, BE. This algorithm provides a decreased
throughput as high priority connections are completely served
first due to which low priority connections are starved.
III. SIMULATION ENVIRONMENT AND ANALYSIS OF RESULT
WiMAX homogeneous scheduling algorithms Weighted
Fair Queuing and Strict priority have been evaluated for fixed
nodes and Weighted Fair Queuing, Strict Priority and Round
Value
TDD
Random
1500m X 1500m
100s
10 – 60
2.4 GHz
30 dBm
10 m/s
20 MHz
Simulation graphs have been plotted for average throughput,
average end to end delay and average jitter by varying number
of nodes form 10 to 60. Along with nodes applications are
also varied. Different applications considered are VoIP for
ertPS service class, Video streaming for rtPS service class and
data traffic for nrtPS service class in the ratio 1:1:1
respectively, when no. of nodes are taken as 10. As nodes are
increased, applications also increase and at 60 nodes they are
in ratio 6:6:6. VoIP model based on H.323 codec has average
talking time of 15 seconds. Rate for video streaming traffic is
4.096 Mbps.
Following Graphs have been observed:
A. Result Analysis for Fixed Nodes
Figure 5 shows the variation of throughput with the
increase in number of SS for video streaming for Weighted
Fair Queuing and Strict Priority scheduling algorithms.
Average throughput of SS’s of a class decreases with
increased concentration of SS’s of that class due to increase in
network load and increase in wastage of bandwidth due to
uplink burst preamble.
Now according to graph when Strict Priority is used as
scheduling algorithm then better throughput is experienced in
case of rtPS traffic as Strict Priority provides first preference
to higher priority traffic.
Queuing as video streaming is second in priority to VoIP so it
will experience some delay. Moreover Weighted Fair Queuing
experiences little less delay as it distributes bandwidth
according to weights of queue.
Fig. 5 CBR average Throughput Vs number of nodes
Fig. 8 VoIP average end to end delay Vs number of nodes
Fig. 6 CBR average end to end delay Vs number of nodes
Fig. 9 VoIP average jitter Vs number of nodes
Figure 8 and Figure 9 shows the variation of end to end
delay and jitter with the increase in number of SS for VoIP for
Weighted Fair Queuing and Strict Priority scheduling
algorithms. It is seen that Strict Priority provides less delay
and jitter in case of VoIP as this is highest priority traffic for
our scenario. So average value for end to end delay and jitter
is less in Strict Priority as compared to Weighted Fair.
Fig. 7 CBR average jitter Vs number of nodes
Figure 6 and Figure 7 show the variation of end to end
delay and jitter respectively with the increase in number of SS
for video streaming for Weighted Fair Queuing and Strict
Priority scheduling algorithms. It is seen that Strict Priority
experiences little more delay and jitter than Weighted Fair
Figure 10 shows the variation of throughput with the
increase in number of SS for data traffic for Weighted Fair
Queuing and Strict Priority scheduling algorithms. As this is
low priority traffic so poor throughput is observed in case of
Strict Priority whereas better throughput is provided by
Weighted Fair Queuing scheduling algorithm.
Fig. 10 FTP average Throughput Vs number of nodes
Fig. 12 CBR average end to end delay Vs number of nodes
B. Result Analysis for Nodes with Mobility
Fig. 11-16 represents comparison of average throughput,
average end to end delay and average jitter. The only
difference is that a mobility element has been introduced in all
nodes and they move randomly in any direction with a speed
of 10m/s.
Figure 11 shows the variation of throughput with the
increase in number of SS for video streaming for Weighted
Fair Queuing, Strict Priority and Round Robin scheduling
algorithms. It is seen that Round Robin algorithm offers good
throughput values for rtPS traffic as it sends packet from each
queue one by one.
Fig. 13 CBR average jitter Vs number of nodes
Fig. 11 CBR average Throughput Vs number of nodes
Figure 12 and Figure 13 show the variation of end to end
delay and jitter with the increase in number of SS for video
streaming for Weighted Fair Queuing, Strict Priority and
Round Robin scheduling algorithms. As was seen earlier
Round Robin algorithm offering good throughput value. Now
since Round Robin gives service to all queues one by one so
with increase in number of queues this algorithm can provide
fair amount of end to end delay and jitter as is seen in graphs.
Again Strict Priority offers less average end to end delay and
jitter amongst all.
Fig. 14 VoIP average end to end delay Vs number of nodes
Figure 14 and Figure 15 show the variation of end to end
delay and jitter with the increase in number of SS for VoIP for
Weighted Fair Queuing, Strict Priority and Round Robin
scheduling algorithms. It is seen from graphs Weighted Fair
Queuing provides lowest value for average end to end delay
and average jitter.
VoIP, video streaming and data traffic by providing the
required QoS.
In this paper we can conclude that for video streaming
which is a rtPS traffic, Strict Priority gives good throughput
values but for nrtPS traffic, Round Robin algorithm provides
good throughput. But in case of VoIP less average end to end
delay and average jitter are observed in case of Weighted Fair
Queuing algorithm.So we can conclude that for VoIP traffic
Weighted Fair Queuing is suitable, for video streaming Strict
Priority is suitable and for data traffic Round Robin is suited.
So we need to use more than one scheduling algorithm for
different data flows available at a single connection. So in
future we can implement a fair, robust and efficient scheduler
which gives better result for all data flows.
REFERENCES
Fig. 15 VoIP average jitter Vs number of nodes
[1]
[2]
[3]
[4]
[5]
[6]
Fig. 16 FTP average Throughput Vs number of nodes
[7]
Figure 16 shows the variation of throughput with the
increase in number of SS for data traffic for Weighted Fair
Queuing, Strict Priority and Round Robin scheduling
algorithms. It is seen that Round Robin algorithm offers good
throughput values for data traffic as it sends packet from each
queue one by one.
IV. CONCLUSIONS
WiMAX is a telecommunication technology providing
wireless data access over long distances in a variety of ways.
It has broad coverage like cell phone networks instead of
small Wi-Fi networks. It supports various applications like
[8]
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