Chapter 5 Simulation Results
5.1 Simulation Platform
5.1.2 Non-real-time Services
Two types of the non-real-time services are simulated in this simulation platform. One is the web browsing service and another is file transport protocol (FTP) service. The traffic model of web browsing and FTP services is explained below.
Fig. 5.3 shows the packet trace of a typical web browsing session. The session is divided into ON/OFF periods representing web-page downloads and the intermediate reading times. In Fig. 5.3, the web-page downloads are referred to as packet calls.
Therefore, a packet call, like a packet session, is divided into ON/OFF periods. Unlike a packet session, the ON/OFF periods within a packet call are attributed to machine interaction rather than human interaction. When receiving a page, the web-browser will parse the HTML page for additional references to embedded image files such as the graphics on the tops and sides of the page as well as the stylized buttons. The retrieval of the initial page and each of the constituent objects is represented by ON period within the packet call while the parsing time and protocol overhead are represented by the OFF periods within a packet call. For simplicity, the term “page” will be used in this thesis to
object” and the each of the constituent objects referenced from the main object are referred to as an “embedded object”.
Fig. 5. 4 Packet trace of typical web browsing session
Fig. 5. 5 Contents in a packet call
Parameters for the web browsing traffic are as follows:
SM: Size of the main object in a page.
SE: Size of an embedded object in a page.
Nd: Number of embedded objects in a page.
Dpc:Reading time.
Tp: Parsing time for the main page.
Packet traffic characteristics within a packet call will depend on the version of HTTP used by the web servers and browsers. Currently two versions of the protocol, HTTP/1.0 and HTTP/1.1, are widely used by the servers and browsers. In this platform, the traffic model of HTTP/1.1 is accepted.
Parameters of web browsing service in the platform are listed in Table 5.3. In HTTP/1.1, persistent TCP connections are used to download the objects, which are located at the same server and the objects are transferred serially over a single TCP
connection; this is known as HTTP/1.1-persistent mode transfer. The TCP overhead of slow-start and congestion control occur only once per persistent connection. The distributions of the parameters for the web browsing traffic model were determined based on the literature on web browsing traffic characteristics [17].
Table5. 3 HTTP traffic model parameters
Component Distribution Parameters PDF Main object
Subtract k from the generated random value to obtain Nd. Reading time
(Dpc)
Exponential Mean = 30 sec
033
Exponential Mean = 0.13
69
Parameters for icat e ble5.4. Fig.5.5 plots the acket trace in a typical FTP session. In FTP applications, a session consists of a sequence of file transfers, separated by reading times. The two main parameters of an FTP session are:
the FTP appl ion sessions ar described in Ta p
S : the size of a file to be transferred
Dpc : reading time, i.e., the time interval between end of download of the previous file and the user request for the next file.
Fig. 5. 6 Packet trace in a typical FTP session
Table5. 4 FTP traffic model parameters
Component Distribution Parameters PDF File size (S) Truncated Mean = Lognormal 2Mbytes Std.
π
Dev. = 0.722
Exponential Mean = 180
006
5.
based on [18] are listed in table 2.3 and table 2.4. A simple link
ad ation ission modes. According to the studies
of channel conditions in WLAN [26-28], channel of this platform is set as AWGN
ch el a n and
variance ar l is listed in table 5.5.
e can assume that error probability of packet transmission is ignorable by using link .
1.3 PHY Layer Assumption
Many values such as SIFS, slottime or the time period each packets occupies the channel are correlated with the assumption of PHY layer. The transmission modes and value assumptions
apt is implemented based on these transm
ann nd the distribution of SNR will be log normal distribution which the mea e equal to 15 dB and 8 dB. Decision rule of rate contro
W
adaptation since good link adaptations would decrease error probability to very low
Table5. 5 Decision rule of link adaptation
Transmission Mode SNR Data rate(Mbps)
Mode 1 SNR< 7dB 6
5.1.4 Performance Crite lation Platform
Following performance criteria
ria in Simu
are considered:
Packet delay: The packet
e time interval from the time thatpacket arrives at the MAC layer to the ission.
delay is defined as th
beginning of a successful transm
Delay Jitter: Delay jitter is the standard deviation of the packet delay. Delay jitter
also affects the quality of real-time services when the delay jitter is large.Packet loss rate: In the simulation platform, packet loss happens because
packets stay in the buffer of the local transmitter longer than the delay bound thatthe real-time service can tolerate.
Capacity: The number of stations that the WLAN system allows to serve in the
system when the QoS is taken into account.Unsatisfied condition: Unsatisfied condition means that there is at least one
active real-time service which its packet loss rate larger than 1%. Unsatisfied condition is defined because the proposed VTSE algorithm reject a new real-time service request when is estimated that the unsatisfied condition will happen or the unsatisfied condition already happens.5.2 Simulation Results
In order to discuss rios are created for the
cation. n 5.2.1 discusses the proposed
ffic source estimation algorithm when all servi n the network are VoIP which generate pack . In sect 5.2.2, best effort services comparison towards a simple algorithm is discussed in section 5.2.3. Observation period of VTSE is 1 second when
oIP services are Markov de.
cenario I
sion in this scenario traffic features of VoIP users in WLAN and e performance of the proposed VTSE algorithm. All VoIP users generate packets in he performance.
ndition. The observed data is focus on
generat st
the sys cord of
Fig.5
the traffic features. Some scena
convenience of verifi Sectio performance of the
virtual tra ces i
services ets in the CBR mode ion
are added to observe the performance of VTSE. A
VoIP services are CBR mode and it will be set 5 seconds when V on/off mo
5.2.1 S
Discus is focus on the
th
CBR mode and the number of active VoIP users is adjusted to examine t Since the VTSE estimates the downlink traffic co
the downlink direction. In scenario I, there are some existing VoIP services begin to e packets in the beginning of simulation. Then, a new VoIP service reque appears during the simulation period. The proposed call admission control will estimate
tem condition and make decision according to its estimation and QoS re existing VoIP services after an observation period equal to 5 seconds.
.6 shows the VTSE estimated delay time and the observed packet queuing delay
in the d SE algorithm can estimated the transmission
conditi ervices is adjusted form 21 to 32.The
a new accepts close to
27th and the service performance begins to degrade
seriously. This phenomenon can be observed from the Fig.5.8. Fig.5.8 plots the average hen there are fixed number of VoIP services. Fig.5.8 reveals that the average unsatisfied users be
ownlink direction. It shows the VT
delay precisely. Fig.5.7 shows the observed conditional probability that unsatisfied on happens when the number of active VoIP s
conditional reject probability of VTSE algorithm is also plotted in Fig.5.7. VTSE rejects service request when it predicts that the network will be unsatisfied if the system the new VoIP service. Fig.5.7 reveals that the reject probability of VTSE basically the probability that unsatisfied condition happens in realistic except when the 28th VoIP service request. It is because
unsatisfied users in the system w
gin to increase seriously when there are 27 active VoIP users in the system.
Number of VoIP Services in the WLAN system
22 24 26 28 30 32
Delay
0.030
0.015 0.025
0.020
(Sec)
0.000 0.005 0.010
Predicted downlink packet delay Observed downlink packet delay
Fig. 5. 7VTSE estimated delay and the observed packet queuing delay in the downlink direction
Number of VoIP Users
22 24 26 28 30 32
Probability (%)
0 20 40 60 80 100
Probability which unsatisfied condition happens VTSE Reject Probability
Fig. 5. 8 Observed conditional probability that unsatisfied condition happens and the conditional reject probability of VTSE algorithm
Number of VoIP Services in the system
22 24 26 28 30 32
Number of Unsatisfied VoIP Users
0 5 10 15 20 25 30
Average number of unsatisfied VoIP Users in the system
Fig. 5. 9 Average unsatisfied users in the system when the number of VoIP services in fixed
Fig.5.9 tion
happens in the system ets in
Markov on/of te the average
length of on/of de and the VTSE
plots the VTSE reject probability and the probability that unsatisfied condi when VoIP users are fixed and all VoIP services generate pack f mode. It is assumed that the proposed VTSE can estima
f period and generates virtual packets in on/off mo
observation period is 5 seconds. The result shows the reject probability is close to the probability that unsatisfied condition happens.
Number of VoIP Users
32 34 36 38 40
0 10 15 20 25
Reject Probability (%)
5
Reject Probability of VTSE
Conditional Probability that unsatisfied condition happens
Fig. 5. 10 Observed conditional probability that unsatisfied condition happens and the conditional reject probability of VTSE under Markov on/off mode
5.2.2 Scenario II
In the scenario II, number of best effort services is fixed in 100 web browsing services and 10 FTP services. All the web browsing services generate packets in the downlink direction and FTP services are assumed bi-directional to simulate the uplink best effort services. Then, the number of VoIP services in the platform will be adjusted to examine the performance of VTSE algorithm. The effect of the proposed bandwidth reservation will also be surveyed in this scenario.
Fi od
ulation
period. Simu xed numbers of
active VoIP
tim ly in the 0 to 100th
second. A TSE
to ma services request,
it m and 100 web browsing
servic ts that the
system ition” happens
after the sy to examine the
diff
when the number of acti . The reject probability
f VTSE algorithm is also plotted in Fig.5.11. Fig.5.11 reveals that the VTSE algorithm ied condition close to the probability that unsatisfied condition happens when the new VoIP service is allowed to access the system. Fig.5.12 reveals the reject p
the system allows how many VoIP services to access the system when the number of best effort service is fixed in 100
g. 5. 11 Assumptions of interarrival of different services in the simulation peri
Fig.5.10 describes the assumption of interarrival of different services in the sim lation period will last up to 200 seconds. In the beginning, fi
services begin to generate packets in the 0th second. Then, the interarrival e of 100 web browsing services and 10 FTP services are set random
new VoIP service request happens at the 100th second and it relies on the V ke decision. i.e. When the VTSE makes decision for the 27th VoIP
eans that there are 26 existing active VoIP services and 10 FTP
es in the system. VTSE will reject new VoIP service when it predic will become “unsatisfied”. The probability that “unsatisfied cond
stem accept the new service request will also be observed erence of predicted unsatisfied probability and real unsatisfied probability.
Fig 5.11 shows the observed conditional probability that unsatisfied condition happens ve VoIP services is adjusted from 15 to 30
o
can estimate the unsatisf
robability and the observed probability that unsatisfied condition happens when the bandwidth reservation is implemented with the VTSE algorithm. In Fig.5.12 the reject probability is larger than the realistic observed probability. It is because BR reserves bandwidth for real-time services adaptively when the new service request is allowed to access the system. But the bonus of BR toward real-time services has not taken into account in the VTSE. Fig.5.13 is the capacity that
web browsing services and 10 bi-directional FTP services. Fig.5.14 plots the influence of the proposed BR towards system throughput; the system throughput would degrade 10%~20% in average when BR is implemented.
Fig.5.15 reveals the comparison of delay jitter of VoIP services whether the BR is ented or not. BR will keep the delay jitter of VoIP services steady except when there are more than 27 VoIP users in the system. But the system only accepts27 Vo implem
P
users in ma .13,. So,
VTSE algorithm rejects new VoIP service before the BR fail to keep delay jitter steady.
I ximum when BR is implemented according the result plotted in Fig.5
Number of VoIP User
16 18 20 22 24 26 28 30
Reject Probability (%)
0 20 40 60 80 100
Reject Probability of VTSE
Conditional Probability that Unsatisfied scenario happens
Fig. 5. 12 Conditional probability of unsatisfied condition and the conditional reject probability of VTSE
100
Number of VoIP Users
16 18 20 22 24 26 28 30
40 60 80
itional Probability (%)Cond
0 20
Reject Probability of VTSE with BR
Conditional Probability that unsatisfied scenario happens
Fig. 5. 13 Conditional reject probability of VTSE and observed conditional probability of unsatisfied condition when BR is implemented with VTSE
Number of VoIP Users in the system 0
20 60 80 100
16 18 20 22 24 26 28 30
ability (%)Prob 40
Accept probability without BR Accept Probability with BR
Fig. 5. 14 Capacity of VoIP services with fixed number of non-real-time services
Number of VoIP Users in the WLAN system
16 18 20 22 24 26
Throughput (Mbps)
0 1 2 3 4 5 6 7
Throughput without BR Throughput with BR
Fig. 5. 15 Comparison of the throughput when BR is implemented or not
.
Number of VoIP Users in the system
14 16 18 20 22 24 26 28
Jitter (ms)
0 2 4 6 8 10 12 14 16
Delay Jitter of the VoIP services without BR Delay Jitter of VoIP services with BR
5.2.3 Scenari
le and intuitive
call admi . Daqing Gu & Jinyun
including best effort in [29] will
halt the cont ore than β %
of tim
Then, best ef are the blocking
ented with Fig.5.16 describes the
assump mulation
fort services requests
are assume services and
interarrival tim he 0 to 100th
second. Both algorithms will reject best effo
larg pled form
the 400th VTSE in scenario III is 1
second.
o III
In Section 5.2.3, the VTSE algorithm with BR is compared with a simp ssion algorithm proposed in [29], which is proposed by
Zhang. In this algorithm, the network reject new service request,
service, when the channel is busy more than α % of time period. Algorithm ention process of the lowest priority when the channel is busy m e period. In scenario III, α is equal to 90 and β is equal to 95.
fort services are simulated with VoIP services to comp probabilities of both call admission algorithms and the BR algorithm is implem VTSE to verify the blocking probabilities of both algorithms.
tion of interarrival of different services in the simulation period. Si period will last up to 500 seconds in scenario III. Numbers of best ef
d 100 web browsing services and 10 bi-directional FTP es of these best effort services are randomly selected in t
rt services when the channel busy period is er than 90% of a beacon interval. The simulation observation data are sam
second to the 500th second. The observation period of
Fig5.17 com when the mean
interarrival tim time of new VoIP
ean interarrival
time is adju II will last a period
of time which is also set based on exponential distribution and the mean value is 120
seconds. accept
Fig. 5. 17 Assumption of the interarrival of different services
pares the blocking probabilities of both algorithms e is adjusted from 1 to 5 seconds. The interarrival service request is assumed based on exponential distribution which the m
stable. Every active VoIP service existing in the scenario I
VoIP services generate packets in CBR mode. It shows the VTSE can
more VoIP services when system can support the QoS of all VoIP services.
Interarrival Time of VoIP Services
0
Reject Probability of VTSE with BR
Blocking Probability of Daqing Gu & Jinyun Zhang's Algorithm
Fig. 5. 18 Reject probability of VTSE with BR and Daqing Gu & Jin yun Zhangs' algorithm
Fig.5.18 plots the erlang and packet loss rate of both algorithms. The erlang is defined as:
Fig.5.18 shows the VTSE with BR can support more VoIP services under certain packet period
n
(5.1)
loss rate.
Fig5.19 plots the throughput of both algorithms. Fig5.19 shows that the throughput of VTSE with BR is close to Daqing Gu & Jinyun Zhangs’ algorithm when less VoIP services requires to access the system. When the interarrival time of VoIP services decreases, the VTSE with BR accepts more VoIP services and it decreases the system throughput.
0.0 0.1 0.2 0.3 0.4 0.5
Erlang
0 10 20 30 40
Packet Loss Rate (%)
VTSE with BR
Daqing Gu & Jinyun Zhang's Algorithm
Fig. 5. 19 Erlang and packet loss rate of VTSE with BR and Daqing Gu & Jinyun Zhang' algorithm
8
Interarrival Time of VoIP Services
0 5
10 15
20 25
2 4 6
Throughput (Mbps)
0
VTSE with BR
Daqing Gu & Jinyun Zhang's Algorithm
Fig. 5. 20 System throughput of VTSE with BR and Daqing Gu & Jinyun Zhangs' algorithm
5.3 Conc
condition” c e
the capacity services. The
BR can support m . System
.
lusion
Based on the observation of scenario I and II, VTSE can predict the “unsatisfied losely. In scenario II, the influence of BR is examined. BR can increas of VoIP services and stabilize the delay jitter of VoIP
penalty of BR is the decrease of system throughput. In scenario III, the VTSE with ore VoIP services compared with an intuitive algorithm
throughput decreases when more VoIP services are allowed to access the system
Chapter 6 Conclusion
This chapter is the conclusion of the simulation works and the future works.
ection 6.1 is Conclusion and section 6.2 is future works.
.1 Conclusion
This thesis proposed a QoS based call admission control and bandwidth reservation to preserve QoS of real-time services in the system. An event driven simulation
is constructed to verify the proposed algorithm. The proposed call admission ontrol can prevent the QoS of real-time services from degrading and the bandwidth
servation can stabilize the delay jitter of the existing VoIP services in the system.
6.2 Future Works
Handoff process is an important issue now in the WLAN system. So call admission ontrol in the future has to concern how to resolve resources for handover users.
esides, MAC layer has to provide advanced resources allocation and bandwidth servation with multiple input multiple output (MIMO) technology in the PHY layer since MIMO is defined in IEEE 802.11n.
S
6
platform c
re
c B re
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