Analyse Network Performance

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This report analyses the network performance of three websites using Wireshark. Load distribution, throughput, time sequence, flow and window scaling graph analysis are used to evaluate the performance of each website. The report concludes that the websites are stable and have good performance for handling more users at a time.

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Running head: NETWORKED APPLICATIONS
Analyse Network Performance
Name of the Student
Name of the University
Author’s Note

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NETWORKED APPLICATIONS
Table of Contents
Introduction...........................................................................................................................................2
Task 1.....................................................................................................................................................2
Load Distribution.......................................................................................................................3
Load Distribution.......................................................................................................................6
Load Distribution.......................................................................................................................9
Throughput Graph.....................................................................................................................9
Task 2...................................................................................................................................................12
Throughput Graph...................................................................................................................12
Time Sequence Graph..............................................................................................................12
Conclusion...........................................................................................................................................13
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Introduction
The report is prepared for the analysis of the four website using the analytic skill and wireshark.
Packets are captured from the three websites and the performance of the website are analysed for
the preparation of the report. The three websites are evaluated in terms of the performance and the
distribution of the load is analysed with the help of creation of a throughput, time sequence, flow
and window scaling graph. The three websites are analysed using the wireshark network analysis
tool for the generation of different graphs used for the analysis of the network performance. The live
data packets are captured from the network that helps in identification of the response time and
generate the sequence graph. Different display filters are applied for narrowing the search for the
analysis of the website and generate the graph from the network. Monitoring of the data traffic is
done by inspecting the data packets captured between the client and the destination.
Task 1
The http and the tcp packets captured from the network for the analysis of the three websites are
analysed for identification of the throughput of the website, distribution of the load, flow graph,
windows scaling graph. The network statistics are created from the captured packets and the graphs
are attached in the report for the demonstration of the performance of each of the websites.
http://www.onlinenewspapers.com/australi.htm
Load Distribution
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The load distribution is used for the analysis of the network load on the server and the display filter
is used for opening the website.
Throughput Graph
The above screenshot shows the average throughput of the segment length for a window size of
1,000000.
Time Sequence Graph

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A stable time sequence graph is obtained from the packet that shows that the performance of the
server is good.
Flow Graph
The flow graph is used for the demonstration of the flow of the data packet flowing from the client
to the server for getting information about the website.
Window Scaling Graph
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The size of the window frame is used for demonstration of the window size and the time frame used
for sending and receiving the data packet in the network.
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http://www.cbsinteractive.com.au/
Load Distribution
The load on the http://www.cbsinteractive.com.au/ server is analysed from then captured packet on
the network. The percentage of the usage of the different servers can be analysed with the details of
the burts rate and the burst start time analysis.
Throughput Graph

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NETWORKED APPLICATIONS
The above screenshot shows the average throughput of the segment length for a window size of
1,000000 and the segment length ranges from 0 to 280.
Time Sequence Graph
The time sequence graph is created for the analysis of the sequence number and it ranges from 0 to
65000.
Flow Graph
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NETWORKED APPLICATIONS
The flow of the data traffic and the information is analysed for the development of the network
analysis report for the website http://www.cbsinteractive.com.au/.
Window Scaling Graph
The size of the window frame is used for demonstration of the window size and the time frame used
for sending and receiving the data packet in the network.
http://www.newspapers.com.au/
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NETWORKED APPLICATIONS
Load Distribution
The load distribution of the http://www.newspapers.com.au/ server is analysed form the packet
captured form the network interface.
Throughput Graph

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NETWORKED APPLICATIONS
The through put graph is created for the analysis of the through put of the
http://www.newspapers.com.au/ server. The length of the segment ranges from 0 to 5000 and it is
used as the average throughput.
Time Sequence Graph
The time sequence graph is created from the wireshark and from the analysis it is found that the
connection is stable and linear graph is obtained from the analysis.
Flow Graph
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NETWORKED APPLICATIONS
The flow graph is created for the analysis of the flow of the data traffic in the network for connecting
with the http://www.newspapers.com.au/ server.
Window Scaling Graph
The windows scaling graph is created for the analysis of the window size for the
http://www.newspapers.com.au/ and it ranges from 0 to 30000.
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NETWORKED APPLICATIONS
Task 2
Throughput Graph
Time Sequence Graph

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NETWORKED APPLICATIONS
Conclusion
From the above report it can be concluded that for the analysis of the website wireshark is an
effective tool that can help in identifying the flow of the data traffic in the network and analyse the
performance of the websites. The performance of the website are measured in terms of the ability
of distribution of the loads, throughput, rime sequence, flow graph and window scaling graph. The
website is opened and the live packets are captured using the wireshark and it is analysed for the
preparation of the report. BY analysing the performance of the four websites it has been found that
the sites are stable and have a good performance for handling more number of users at a time. The
analysis helps in finding the IP address of the server hosted by the website and different information
are gathered such as the window size, maximum size of the segment, windows scaling option and
values. The response time of the system can be analysed for the identification of the performance of
the website.
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Bibliography
[1]. Chappell, L. Wireshark 101: Essential Skills for Network Analysis-Wireshark Solution Series.
Laura Chappell University., 2017.
[2]. Sanders, C. Practical packet analysis: Using Wireshark to solve real-world network problems.
No Starch Press., 2017.
[3]. Ndatinya, V., Xiao, Z., Manepalli, V.R., Meng, K. and Xiao, Y. Network forensics analysis using
Wireshark. International Journal of Security and Networks, 10(2), pp.91-106., 2015.
[4]. Walnycky, D., Baggili, I., Marrington, A., Moore, J. and Breitinger, F. Network and device
forensic analysis of android social-messaging applications. Digital Investigation, 14, pp.S77-
S84., 2015.
[5]. Messier, R. Packet Capture and Analysis. Network Forensics, pp.81-112., 2017.
[6]. Cappers, B.C. and van Wijk, J.J. Semantic Network Traffic Analysis using Deep Packet
Inspection and Visual Analytics., 2017.
[7]. Quadrio, G., Bujari, A., Palazzi, C.E., Ronzani, D., Maggiorini, D. and Ripamonti, L.A. Network
analysis of the steam in-home streaming game system: poster. In Proceedings of the 22nd
Annual International Conference on Mobile Computing and Networking (pp. 475-476). ACM.,
2016, October.
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