802.11 Wireless LAN performance estimation under varying
network load
CHRIS BASIOS and PANAGIOTIS KOSTARAKIS
Physics Department - Electronics, Telecommunications and Applications Laboratory
Institute of Informatics and Telecommunications - Telecommunications Laboratory
University of Ioannina
Panepistimioupolis, 45110, Ioannina
GREECE
Absract: WLANs are an emerging part of the current wireless communications providing
high bandwidth to users in a limited geographical area. The IEEE 802.11 Standard is a widely
used protocol for this kind of communication. In this paper, we have estimated the
performance of the above protocol for the 2 main WLAN topologies provided by the IEEE
802.11 Standard; an ad-hoc network and an infrastructure network. The performance
estimation was based on throughput values coming out of various different simulations. Our
main interest focused on the transfer of fixed data packets under a varying network load
(depending on the number of users, the message length, the message generation rate etc.).
Key-Words: 802.11, DCF, throughput, ad-hoc, infrastructure, TCP, UDP
1. Introduction
The main concept in our
simulations was the throughput
estimation for the case where every
user that resides in the WLAN requests
and downloads – using either TCP or
UDP transport protocol - a fixed size
message from a remote server. In the
ad-hoc network both users and the
server use the DCF access method –
specified by the IEEE 802.11 Standard
– in order to gain access to the wireless
medium. As for the infrastructure
network the users use the DCF in order
to request and download a message
from the server that resides in a wired
LAN (that uses the access method
specified by the IEEE 802.3 Standard).
We have modeled various scenarios in
order to investigate the network
efficiency under many different
conditions. Thus, we have varied the
offered load (by altering the number of
the users, the arrival rate of the users’
requests to the server, the message size
that the users download from the
server).
The design of the simulation
models and the analysis of their
efficiency have been made by using
the COMNET III simulation program.
With this simulation tool we had the
possibility to built our own network
topology by using and altering many
parameters of the main building blocks
of the program - such as nodes, links,
network devices etc. - that constructed
our designed models.
2. The DCF access method and
simulation basic parameters
In all simulations the access
method that was used by the wireless
users was the DCF (Distributed
Coordination Function). DCF is the
primary access method provided by the
IEEE 802.11 Standard and is based on
CSMA/CA algorithm. In the following
lines we will give an overview of this
algorithm.
Before a station initiates
transmission of a data frame, it needs
to sense the channel in order to
determine whether another station is
currently transmitting. The station can
proceed with its transmission if the
medium is determined to be idle for a
time interval of DIFS (DCF InterFrame Space). After a data frame is
successfully
received
at
the
destination, the receiver must send an
acknowledgment
frame
(ACK),
because the transmitter cannot
determine whether a frame has been
faithfully delivered to its destination by
simply listening to the channel; the
sender may not observe frame
collisions the receiver detects with
other senders not observable by the
first (this is the so-called “hidden
terminal problem”). To transmit the
ACK, the receiver waits for the
channel to be idle for another time
interval of SIFS (Short Inter-Frame
Space). If the transmitter does not
receive an ACK packet within a certain
period (ACK timeout), it presumes that
the data frame is lost and schedules a
re-transmission.
If the medium is busy upon
transmitting a data frame or an ACK,
the transmission must be deferred until
the end of the ongoing transmission. In
this case, a random backoff interval is
selected, as follows. A backoff timer is
set with a random backoff integer (BV)
drawn from a uniform distribution over
the interval [0,CW - 1], where CW
(Collision Window) is an integer
within the range of CWmin and
CWmax. BV is the number of idle
“slots” the station must wait until it is
allowed to transmit. The value is
decremented by one for each idle slot
detected. The backoff timer suspends
when the medium becomes busy
before BV reaches zero. The timer
resumes only after the medium has
been idle longer than the designated
inter-frame space interval. The station
starts transmitting the frame when the
backoff timer reaches zero. For each
successive retransmissions, the value
of CW increases exponentially (i.e.
CWnew = CWold . 2 - 1), until it
reaches and then stays at CWmax . CW
will be reset to CWmin after a
successful transmission. The backoff
method is used to minimize collisions
and maximize throughput at both low
and high network utilizations.
All the wireless users access
the wireless channel of each one of the
2 network topologies by using the
basic DCF method provided by the
802.11 Standard, while at the physical
layer they use the FHSS technique.
The bit rate of the wireless medium is
fixed to 2 Mbps.
The transport protocols we
have used are TCP and UDP. The
congestion
control
algorithm
implemented in TCP was selected to
be the ‘Fast recovery’ algorithm with a
window size equal to 3. We have also
modeled the establishment and
disconnection of a TCP connection
using 2 fixed size (40 bytes) packets
for every message (‘Open’, ‘Close’
packets), while the ACK packet
acknowledging every data packet is 40
bytes long.
The main 802.11 parameters
and their values used in the simulations
are summarized in the next table. We
must underline that the run simulation
time was set to 3600 sec. for all
simulations in order to represent a real
network scenario, in which the users
will have the opportunity to access
more than one time the wireless
medium.
Table 1: Parameters used for the
simulation of the IEEE 802.11 MAC
protocol
802.11 Parameters
Bandwidht
Values
2 Mbps
2304 bytes
0.2 ms
512 ms
0.05 ms
0.028 ms
128 ms
7
255
The main assumption that have
been made for the wireless networks is
that the ‘hidden-node’ problem is not
addressed in the simulation models,
while the wireless users are all in fixed
locations (no mobility).
3. Simulation
results
models
and
In this section, we present the 2
different simulation models and the
individual scenarios being used. We,
briefly, analyze the network topology
and we demonstrate the throughput
graphics coming out for each scenario.
user follow a Poisson distribution, thus
the
request
interarrivals
are
exponentially distributed. In order to
vary the network load we have
simulated 2 different environments
where the mean value of the
exponential distribution takes 2
different values (600 and 300). Both
users and the server make use of TCP
and UDP protocols (TCP have a fixed
sized packet consisted of 1460 data
bytes and 40 overhead bytes, while
UDP packet is consisted of 1480 data
bytes and 20 overhead bytes). The
offered load in the network varies
according to the number of users that
join the ad-hoc network (the min.
number of users is 1 and the maximum
is 30).
2
througput (Mbps)
Frame max
ACK timeout
Frame TxLife Time
Slot time
SIFS
FH dwell time
CWmin
CWmax
1,5
TCP,exp(600)
UDP,exp(600)
1
TCP,exp(300)
UDP,exp(300)
0,5
0
0
10
20
30
40
users
3.1 Ad-hoc model
In this model (figure 1) we
have simulated the transfer of a fixedsize message from a wireless server to
a variable number of wireless users
with both users and the server residing
in the same IBSS.
Figure 1: Simulation model of the ‘adhoc’ network.
1st scenario
Every BSS STA (user) requests
(using a 1000 bytes packet) a fixed size
(2 MB) file from the server located in
the same BSS. The requests from each
Figure 2: Effect of number of users on
throughput for different request
generation rate.
2nd scenario
In this scenario the number of
users is fixed (equal to 10 and 20 for
the 2 different conditions simulated
here) and the main varying parameter
of the system is the length of the
message being downloaded by all 10
users. The interarrival of each request
(1000 bytes) to the server follows an
exponential distribution with a mean
value of 600 and 900. The message
size varies from 0.01MB to 5MB (in
particular 0.01, 0.1, 0.5, 1, 2, 3, 4, 5),
while the packet size of the transport
protocol being used (UDP) remains the
same equal to 1500 bytes (plus the
overhead).
follow an exponential distribution with
2 different mean values (600 and 300).
2
1,5
10us,exp(600)
20us,exp(600)
1
10us,exp(900)
20us,exp(900)
0,5
0
throughput (Mbps)
througput (Mbps)
2
1,5
TCP,exp(600)
1
UDP,exp(600)
0,5
5
4
3
2
1
0,
01
0,
1
0,
5
0
0
10
message size (MB)
Figure 3: Effect of message size on
throughput for different simulation
cases.
20
30
40
users
Figure 5: Effect of number of users on
throughput for different transport
protocols.
3.2 Infrastructure model
2nd scenario
In this simulation model (figure
4) an 802.11 wireless BSS is
interconnected via a wireless portal
with an 802.3 wired LAN (10BASET
technology). Every wireless user that
resides in the BSS requests and
downloads more than one fixed size
files from the server (according to an
exponential distribution with a mean
value of 600), which is connected to
the wired LAN that makes use of the
IEEE 802.3 Protocol. As with the adhoc model, the transport protocols we
have used are TCP and UDP. Both the
above protocols have a fixed size
packet of 1500 bytes including the
overhead.
Figure 4: Simulation model of the
infrastructure network.
1st scenario
The message size that each user
tries to download from the wired
server is fixed and equal to 2 MB. The
interarrivals of the request messages
In this scenario we have
simulated the transfer of a fixed data
packet from the wired server to a fixed
number of users that consist the
wireless BSS. The main variable here
is the number of the message that each
wireless user requests and downloads
from the wired server. The size of the
message varies in a great range from
0.01MB to 5MB. In order to examine
the performance of the certain network
when the load is being doubled, we
have simulated 2 different cases; in the
first the number of the users of the
BSS is equal to 10 while in the second
case the number is equal to 20. In
addition, in order to investigate the
effect of the requests’ generation on
the users’ throughput, we have altered
the generation rate by increasing the
mean value of the exponential
distribution from 300 to 600, thus
decreasing the overall generation of the
requests. Both the users and the server
make use of UDP with the number of
the packet data bytes remaining fixed
to 1480 bytes.
througput (Mbps)
2
1,5
20us,exp(600)
10us,exp(600)
1
20us,exp(900)
10us,exp(900)
0,5
5
4
3
2
1
0,
01
0,
1
0,
5
0
message size (MB)
Figure 6: Effect of message size on
throughput for different simulation
cases.
4. Conclusions
One main conclusion coming
out from the first scenarios of each
model is the better performance of
UDP over TCP. This result has to do
with the ARQ error mechanism
provided by the 802.11 that makes the
use of TCP congestion control and
acknowledgement technique bouncy,
especially for the networks that do not
experience high load and collisions. As
it was expected, TCP enters greater
overhead than UDP because of the
extra use of the ‘Open’, ‘Close’ and
ACK packets. Another result coming
out of both ad-hoc and infrastructure
networks is the fact that the increase of
the users turns to a throughput
decrease. This is due to our selection
of a rather big message size (2MB) that
appears to be a value far away from the
size limit over which throughput stops
increasing (figures 3 and 6).
For the scenarios where the
main variable is the message size, we
have come out with some important
remarks. Firstly, for both ad-hoc and
infrastructure networks, we can clearly
note the existence of 3 throughout
levels; increment, saturation and
decrement. This observation leads to a
certain size limit of the best achievable
throughput. This message size limit is
equal to 0.1MB for both the ad-hoc
and the infrastructure network.
Secondly, we have come out with
another limit over which both the
users’ doubling and the increase in the
request generation rate start to affect
unfavorably the user throughput. This
limit takes a value equal to 0.05MB,
thus discouraging us to use greater
messages, especially when the network
loads come to higher values.
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Information
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IEEE Standard for Information
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