A New Queue Length based Scheduling Strategy for nrtPS Service
Class in IEEE 802.16 Networks
Pallavi Grover
and Marcio Andrey Teixeira
M.E Research Scholar, Comp Sc. & Engg., UIET Panjab University, Chandigarh, India
Department of Computing, Federal Institute of Education, Science and Technology of São Paulo, Catanduva, Brazil
Keywords: IEEE 802.16 Networks, nrtPS, QoS, Scheduling Algorithms.
Abstract: IEEE 802.16 standard is designed to provide services to various types of multimedia applications. It supports
real-time and non-real-time service classes. With such a large volume of traffic, a new strategy needed to be
developed for the non-real-time service class, since there have been limited studies in this area. In this paper,
a new queue length based scheduling strategy for the non-real-time service class is proposed. The proposed
algorithm is developed on the basis of virtual queue’s and counter scheme’s, aiming at ensuring minimum
bandwidth for non-real-time applications.
In recent years, the development of wireless
technology has increased rapidly, particularly in the
field of broadband wireless networks. WiMAX
(IEEE, 2013) is intended to offer low-cost, high-
speed internet access to a wide variety of devices. The
advantages of WiMAX networks include high
transmission speed, scalable bandwidth, link layer
retransmission, robust security, high peak data rates,
and an efficient QoS mechanism for data, voice, and
video. It is very challenging task to assure QoS
requirements of every type of traffic in a wireless
network. The challenges associated with WiMAX
(IEEE, 2013) are due to limitations of wireless
networks such as strong attenuation with increasing
distance, Rayleigh fading, limited scalability etc. The
protocol stack of IEEE 802.16 standard which defines
characteristics of physical layer’s as well as media
access control (MAC) layer’s.
The working architecture of the IEEE 802.16
network is composed of 2 components: Base Station
(BS) and Subscriber Station (SS). The BS is a core
element that acts as an interface between the
infrastructure network such as the Internet Service
Provider (ISP) and the SS. The SS further extends
internet services to its users. The SSs connects with
the BS to provide a variety of services to its users.
WiMAX has defined five service classes: Unsolicited
Grant Service (UGS), real-time Polling Service
(rtPS), non-real-time Polling Service (nrtPS), best-
effort service (BE) and an extended real-time Polling
Service (ertPS). Each of them is associated with a
certain set of QoS parameters such as delay,
throughput, and jitter.
Real-time services such as UGS, ertPS, and rtPS
are always given higher priority by the scheduler,
whereas non-real-time traffic, which amounts to the
majority of internet traffic, is always neglected. With
such large amounts of traffic volume, there is a need
to develop a dedicated strategy for the non-real-time
service class. There have been very limited studies in
this regard.
The IEEE 802.16 standard does not specify any
scheduling algorithm, it is left to the vendors as to
whether or not they will employ their own scheduling
algorithm. Scheduler defines the distribution of
allocated resources in the form of slots, which are
further mapped into sub channels. Logically, it
calculates the number of slots for each class and
physically, it selects the sub channels and time
intervals. There are 3 distinct scheduling processes:
two are for the BS (uplink and downlink), and one is
for the SS (uplink). The proposed algorithm is
developed to act in the uplink scheduling at BS,
because the uplink scheduling is more complex than
the downlink scheduling. In the downlink scheduler,
the BS has complete knowledge of the queue status
whereas in the uplink scheduling, the input queues are
located in the SSs and hence, are separated from the
BS. The BS does not have any information about the
Grover, P. and Teixeira, M.
A New Queue Length based Scheduling Strategy for nrtPS Service Class in IEEE 802.16 Networks.
DOI: 10.5220/0005989601650171
In Proceedings of the 13th International Joint Conference on e-Business and Telecommunications (ICETE 2016) - Volume 6: WINSYS, pages 165-171
ISBN: 978-989-758-196-0
2016 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
arrival time of packets in the SS queues, however, the
BS makes the bandwidth allocation based on the
bandwidth requests (BW-REQ), messages sent by the
SSs. The BW-REQ message indicates the queue
status in the SS.
This paper presents a survey of scheduling
algorithm to the nrtPS connections and proposes a
new scheduling algorithm for nrtPS service class
based on virtual queue and counter scheme. The
proposed algorithm is applied directly to the uplink
virtual queue in the BS aiming at ensuring minimum
bandwidth for nrtPS service class. The scheduling is
done by assigning priority to the connection having
larger queue size. Counter is attached to each virtual
queue to prevent starvation of connections having
lower queue size. The proposed algorithm has been
evaluated by means of modeling and simulation. The
simulations experiments have shown satisfactory
The remainder of this paper is organized as
follows: Section II resumes the related work. Section
III describes the proposed work. Section IV defines
the network scenario and the main parameters used in
the simulation. Section V shows the numerical
results. Finally, Section VI concludes the paper.
The literature survey of non-real-time services can be
traced back to conventional algorithms such as
proportional fairness and modified largest weighted
delay first algorithms. Proportional fairness was
originally designed for downlink traffic to increase
the throughput of the system, as well as to provide
fairness among multiple queues. It calculates a
priority function which is the ratio of the current rate,
to the average rate, and then schedules different
queues accordingly. It is very simple and efficient,
but it does not take into consideration saturated
queues, when dealing with non-real-time traffic.
Qingwen Liu et al. (Liu, 2006) proposed a cross
layer scheduling algorithm providing QoS support in
IEEE 802.16 networks. A priority is assigned to each
connection which is updated dynamically on basis of
wireless channel quality and QoS satisfaction. For
each nrtPS connection, a minimum reserved rate (ŋ)
is defined. The proposed algorithm ensures average
transmission rate should be greater than ŋ. Scheduling
of nrtPS connections is done with the help of priority
function, which is dependent on nrtPS-class
coefficient and rate satisfaction indicators. The rate
satisfaction indicator is the ratio of the average
transmission rate over the minimum reserved rate. If
the value of the indicator is greater than 1, then the
requirement is satisfied; otherwise, packets should be
sent as soon as possible. This scheduler offers
flexibility, scalability, and low implementation
complexity. The major drawbacks include fairness
issues among same service classes and imperfect
channel conditions arising, due to errors in estimation
and feedback latency.
Authors Fen Hou et al. (Hou, 2009) presented a
simple scheduling structure for non-real-time
services in the IEEE 802.16 networks. It is a cross
layer algorithm, which considers selective automatic
repeat request mechanisms at MAC which layers and
uses adaptive modulation and coding schemes at the
physical layer. It tries to ensure minimum throughput
requirements of the nrtPS class, and at the same time,
maintains flexibility between resource allocation and
packet scheduling. To achieve this flexibility, two
parameters, m and n are defined, where m represents
the number of SSs selected in each MAC frame, and
n represents bandwidth, which is granted to SS when
it is being serviced. In the beginning of each frame m,
SSs, which have superior channel conditions, are
selected and n, amounts to the number of resources
that are given to them. The value of m=1 assures
opportunistic scheduling, leading to maximum
resource utilization. When m = the total number of
SSs, then it leads to minimum resource utilization
with lesser delivery delays. This paper focuses on
scheduling unicast nrtPS applications, but there is a
dire need to concentrate on multicast multimedia
Ali Mohammed Alsahag et al. (Alsahag, 2014)
proposed a fuzzy based adaptive deficit round robin
uplink scheduler that adjusts the weights of the
service queues for real-time as well as non-real-time
applications. The allocation of bandwidth is done on
the basis of deadline based schemes. To compute the
deadline authors have used maximum latency for
real-time and throughput for non-real-time as input
variables. The overall mechanism can be divided in
three fundamental phases: fuzzification, fuzzy
inference, and defuzzification. In the fuzzification
process, we use two input variables as real-time
maximum latency (RTML) and non-real-time
throughput (NRTTHR). These input variables are
processed with the help of a rule base in the fuzzy
inference phase, and then finally in the
defuzzification phase, where crisp numerical values
are obtained, which determines the weights that need
to be used, as an indication for priority. In the
bandwidth assignment process, several queues are
maintained which are associated with a DC value. In
each round DC is incremented by a value, which is
WINSYS 2016 - International Conference on Wireless Networks and Mobile Systems
determined by the fuzzy system, keeping in
consideration overall capacity of the system.
Transmission of queue takes place when the DC value
is equal to the amount of requested bandwidth. The
proposed algorithm optimizes the overall systems
utilization, but gives more consideration to satisfying
maximum latency requirements of real-time traffic.
D. David Neels Pon Kumar et al. (Kumar, 2011)
proposed a neural network based on fuzzy priority
scheduling algorithms. Fuzzy is used to calculate
priority, which itself is composed of a primary fuzzy
scheduler and a dynamic fuzzy scheduler. The
primary fuzzy scheduler takes an input Expiry time
(E), Waiting time (W), Queue length (Q), Packet size
(P) and gives priority index as output. After this
priority index is feed as an input to the dynamic fuzzy
scheduler, which calculates the final priority, by
taking certain types of services into consideration.
Scheduling is done using an artificial neural network,
based on prioritized input received from DPFS
(dynamic priority fuzzy scheduler).Artificial neural
network (ANN) consists of three layers: input layer,
modified Kohonen layer and the Grossberg layer. The
input layer processes prioritized output received from
DPFS and arranges them in order of priority. After,
the output is fed to modify the kohonen layer, which
checks whether the value is in the range of the
threshold. If it is given as an input to the grossberg
layer it has less chance to be rejected. This algorithm
improves fairness, and prevents starvation of the low
priority traffic, but it has not considered bursty traffic
conditions. The major drawback is that processing
time has increased.
Dusit Niyato et al. (Niyato, 2007) presented a
survey of the game theory techniques for
management of radio resources in different wireless
networks and also proposed bandwidth allocation and
connection admission control schemes for IEEE
802.16 networks. The bandwidth allocation helps the
non-cooperative game in which three parameters are
considered: players, strategies, and pay off’s. Players
refer to rtPS and nrtPS connection, strategies which
imply the amount of bandwidth that is to be allocated
with a new connection and payoff’s that refer to the
total utility of currently running rtPS and nrtPS
connections, plus the utility of new connections. The
solution of this game is provided with the help of nash
equilibrium which is calculated through best response
function. It maximizes the payoff of BS which defines
QoS requirements of connections. The simulation
results of adaptive scheme shows that it is not able to
satisfy delay and throughput necessities when load is
The proposed scheduling algorithm aims at
guaranteeing the efficient utilization of the bandwidth
resources, and thus, promotes the effective use of the
wireless link. Figure 1 shows the architecture used to
develop the proposed solution.
Figure 1: Architecture used in development of the proposed
As shown in Figure 1, the BS receives from the
SS bandwidth request (BW-REQ) message, which
reports the current queue size of each connection. The
algorithm is applied directly to the nrtPS bandwidth
request which queues in the BS (Teixeira, 2012).
Figure 2 shows the pseud-code of the proposed
scheduling algorithm.
The scheduling process of the nrtPS is explained
below, in the following steps:
1) Initially, the algorithm checks the amount of
bandwidth requested by the nrtPS connections, and
stores them in a virtual queue at the BS (lines 1 - 7).
2) It then verifies the actual amount of bandwidth
requested by the SSs and sorts the bandwidth requests
by the largest queue size (lines 8 - 15).
3) After sorting the bandwidth requests, a
counter is assigned to each virtual queue, which
prevents the starvation of connections, which
ultimately prevents having lower bandwidth requests
(line 16).
4) On completion of the first round of allocation,
the proposed algorithm verifies if the bandwidth
requests are satisfied or not. If it is not satisfied, the
algorithm checks if there are more symbols to allocate
(lines 18 - 25). However, in this case, the scheduling
sorts the connections by the highest counter number.
5) If more symbols are available, then the
proposed algorithm allocates these available symbols
A New Queue Length based Scheduling Strategy for nrtPS Service Class in IEEE 802.16 Networks
to nrtPS connections, and its counter value will be
decreased (line 29). When the counter decreases to
zero, the count is initiated (lines 26-27).
1: Verifies the bandwidth messages request at the BS queue;
2: begin
3: for BWrequest i at the BS queue do
4: begin
5: if (BWrequest[i] = nrtPS) then
6: begin
7: BW[i] += BWrequest[i].length;
8: if (connections_numbers > 1) then
9: begin
10: if ( BWrequest[i].length < BWrequest[i+1].length)
11: begin
12: Temp = BWrequest[i].length;
13: BWrequest[i].length = BWrequest[i+1].length;
14: BWrequest[i+1].length = Temp;
15: end;
16: BWrequest[i].counter = 3;
17: UL-MAP = request order by the length;
18: if (BwToAllocate > 0) then
19: begin
20: if ( BWrequest[i].counter <
BWrequest[i+1].counter) then
21: begin
22: Temp = BWrequest[i].counter;
23: BWrequest[i].counter = BWrequest[i+1].counter;
24: BWrequest[i+1].counter = Temp;
25: end;
26: if (BWrequest[i
].counter == 0) then
27: BWrequest[i].counter =3
28: else
29: BWrequest[i].counter --;
30: UL-MAP = request order by the counter;
31: end;
32: end;
33: end;
34: end;
Figure 2: Proposed Scheduling Algorithm.
Figure 3 shows the Flowchart of the proposed
scheduling algorithm.
The simulation studies and evaluates the properties of
the proposed scheduling algorithm for non-real-time
traffic. It has been implemented in the Network
Simulator 2 (NS-2) version 2.34 (Network, 2016)
along with the WiMAX module. The simulation
scenario consists of a BS, and also of several SSs
distributed around the BS in a random mode. The
Table 1 shows the main parameters used in the
Determine all nrtPS connections
The SS has a
request ?
Store the BW-REQ
Arrange the connections
by the queue length
Are there
more symbols
to allocate?
Is there another
nrtPS connection?
Arrange the connections
by the lowest
counter(ini tially counter=3)
UL-MAP =Process
requests by lowest counter
For all other
counter == 0 ?
Counter --
Counter = 3
For all SSs in BS range
Set Counter =3 for those
which are scheduled
Figure 3: Flowchart of the proposed scheduling algorithm.
Table 1: Main parameters used in the simulation.
Parameters Values
Frequency band (MHz) 5
Transmit antenna gain 1
Received antenna gain 1
Frame duration (ms) 20
Cyclic prefix 0.25
Simulation time (s) 100
Downlink bandwidth (Mbps) 5.4
Uplink bandwidth (Mbps) 10.5
WINSYS 2016 - International Conference on Wireless Networks and Mobile Systems
The sources of traffic used in the simulation were,
voice, video, web and a file transfer, which
corresponds to the UGS, rtPS, BE, and nrtPS class.
The voice traffic is modeled as an on/off scheme with
a mean of 1.2 s and 1.8 s for “on” and “off” periods
respectively. During “on” period packets, 66 bytes are
generated every 20 ms, which follows an exponential
distribution. The voice traffic was modeled on a basis
of an exponential traffic model in NS-2.
The video was modeled using a traffic source that
generates packets periodically with variable sizes,
simulating the MPEG traffic. The packets size vary
between 450 to 1500 bytes. The web traffic was
modeled using hybrid Lognormal/Pareto distribution.
FTP traffic was generated from a source which follows
exponential distribution within a mean of 512 Kbytes.
The performance of the proposed algorithm was
evaluated to take into account the follow performance
Average end-to-end-delay: This is the time taken
by packets to transmit from source to destination.
There can be various reasons for the delay such as
propagation and network delay, source and
destination processing delay etc. It can be calculated
as followed:
Throughput: This measures the data rate which
is generated by the application in terms of bits per
second. It can be calculated as followed:
The nrtPS scheduler should guarantee minimal
bandwidth to the users. It is used with the Throughput
metric. However, the average delay performance
metric is used to analyze whether the proposed
scheduler algorithm is influencing the other service
classes (UGS, rtPS BE).
5.1 Experiment 1
The first experiment analyzes the performance of the
nrtPS connections and verifies how the BS allocates
bandwidth to the nrtPS service class. The simulated
network consists of one BS and a number of nrtPS
SSs, varying between 2 and 12. The transmission rate
of each nrtPS connection is 512 kbps. There are 2
UGS, 4 rtPS, and 8 BE connections as background
traffic, along with nrtPS connections. Each UGS, rtPS
and BE connection generates 40, 320 and 510 kbps
respectively. The Figure 4 shows the behavior of
average delays of nrtPS SSs.
Figure 4: Average delay of the UGS, rtPS, nrtPS and BE
It is possible to see in Figure 4 that the average
delay rises with an increase in the number of nrtPS
connections. The increase in the average delay has
occurred due to link saturation and the total traffic of
the nrtPS connections has increased. The proposed
algorithm prioritizes transmission of nrtPS
connections on basis of queue length, which results in
lesser average delay. The average delay of the UGS
and rtPS classes remains constant, as defined by the
standard. The increased of the nrtPS load traffic does
not interfere in the UGS and nrtPS classes. This is
expected because the UGS and rtPS Traffic have high
priority over nrtPS and BE service classes. The
average delay of the BE is high, however, the BE
service class does not have QoS parameters.
Figure 5 shows the throughput of the UGS, rtPS,
nrtPS and BE connections.
Figure 5: Throughput of the UGS, rtPS, nrtPS and BE
A New Queue Length based Scheduling Strategy for nrtPS Service Class in IEEE 802.16 Networks
Figure 5 shows the increase of the nrtPS traffic
load also does not interfere with the UGS and rtPS
traffic. The BS distributed the resources to all service
classes. However, with the increase of the nrtPS
traffic load, the throughput of the BE connections
decrease. The BE connections have lower priority
among the other service classes, which causes them
to receive less resource (slots).
5.2 Experiment 2
The second experiment compares the performance of
the proposed algorithm with the traditional Round
Robin (RR) scheduling algorithm. This simulated
network consists of one BS a number of nrtPS
connections varying from 2 to 12. There are 2 UGS,
2 rtPS and 4 BE connections as background traffic
along with nrtPS connections. Figure 6 shows the
throughput of the RR and the proposed algorithm.
As we can see in Figure 6, the proposed algorithm
has better performance than the RR scheduling
algorithm. This happens because the proposed
algorithm organizes the uplink frame in accordance
with the queue length. Moreover, the algorithm
verifies the counter of the nrtPS connections to avoid
starvation. The RR scheduler makes the scheduling
and does not consider the queue length.
Figure 6: Throughput of the RR and nrtPS connections.
5.3 Experiment 3
The third experiment verifies the performance of the
nrtPS connections in the presence of high and low
priority traffic. The input traffic has increased by a
ratio of 2:2:2:2 i.e. 2 UGS, 2 rtPS, 2 nrtPS and with 2
BE connections. In such a scenario, performance
metrics are analyzed by increasing traffic inputs up to
10 connections of each service class. This experiment
helps in analyzing the performance of the scheduler
in presence of diverse traffic classes. Figure 7 shows
the throughput of the connections.
Figure 7: Throughput of the UGS, rtPS, nrtPS and BE
It is possible to see in Figure 7 that the throughput
of the nrtPS connections decreases with the increase
of the traffic load in the system. However, the
scheduler distributes the bandwidth to guarantee
minimum bandwidth to the nrtPS connections. This
decrease in throughput can be justified due to the
presence of high priority traffic, along with nrtPS
connections. Increasing demand for these classes
forces the system to allocate more amounts of
bandwidth to them instead of the nrtPS connections.
However, the proposed algorithm allocates
bandwidth efficiently to the nrtPS connections in
presence of UGS and rtPS connections, which are
highest in priority. When the number of connections
increases, the scheduler distributes the resources to
connections with high priority and the BE
connections receives fewer resources once the BE
connections do not have any QoS requirements.
The same experiment has been completed, but this
time, with the RR algorithm, in order to compare the
performance between RR and the proposed
algorithm. The Figure 8 depicts the throughput of the
proposed algorithm and the RR.
Figure 8: Throughput of the RR and nrtPS connections.
WINSYS 2016 - International Conference on Wireless Networks and Mobile Systems
As is shown in Figure 8, the proposed algorithm
allocates the bandwidth more efficiently than the RR
algorithm. The resources were distributed more
efficiently when the scheduler was made using the
information about the queue length. Furthermore, the
counter scheme helps the scheduler to avoid the
starvation to the nrtPS connections that have lower
queue length.
In this paper, a queue length based scheduling
strategy for an nrtPS service was proposed. The
proposed algorithm was verified by performing
different experiments with diverse traffic scenarios.
The performance metrics used to evaluate this
proposed scheduling algorithm were average delay
and throughput. Scheduler is expected to allocate
bandwidth effectively to the nrtPS class. It should be
able to satisfy the constraint of minimum throughput
for the nrtPS class, even in the presence of high
priority traffic classes such as UGS and rtPS. It has
been observed that bandwidth allocation to nrtPS
class is done efficiently because it leads to increased
quality and more user satisfaction. The proposed
algorithm also shows better performance than the RR
scheduling algorithm.
IEEE Std. 802.16n 2013. IEEE standard for local and
metropolitan area networks Part 16: Air interface for
fixed and mobile broadband wireless access systems––
amendment 2: Higher Reliability Networks. IEEE
Computer Society and IEEE Microwave Theory and
Techniques Society. p. 1–132. ISBN 978-0-7381-8425-
8, 2013.
Liu Q, Wang X, Giannakis G.B., 2006. A Cross-Layer
Scheduling Algorithm With QoS Support in Wireless
Networks, IEEE Transactions on vehicular technology;
55(3), 839 – 847.
Hou F, Ho P.H.,2009. A Flexible Resource Allocation and
Scheduling Framework for Non-real-time Polling
Service in IEEE 802.16 Networks, IEEE transactions
on Wireless Communications; 8(2): 766 – 775.
Alsahag A.M, Ali B.M, Noordin N.K, Mohamad H., 2014.
Fair uplink bandwidth allocation and latency guarantee
for mobile WiMAX using fuzzy adaptive deficit round
robin, Journal of network and computer
Kumar D.D.N.P, Murugesan K, Raghavan S, Suganthi M.,
2011. Neural Network based Scheduling Algorithm for
WiMAX with improved QoS Constraints In:
Proceedings of international conference on Emerging
trends in electrical and computer technology, 23-24
March, Tamil Nadu. p. 1076 – 1081.
Niyato D, Hossain E., 2007. Radio resource management
games in wireless networks: an approach to bandwidth
allocation and admission control for polling service in
IEEE 802.16, IEEE Journal of Wireless
Communications;14(1):27–35, Feb.
Teixeira, M. A.; Guardieiro, P. R., 2012. Adaptive packet
scheduling for the uplink traffic in IEEE 802.16e
networks. International Journal of Communication
Systems (Print).
The Network Simulator-ns2.
A New Queue Length based Scheduling Strategy for nrtPS Service Class in IEEE 802.16 Networks