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Analyse Network Performance

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Added on  2023/06/03

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This report analyses the performance of a network solution using Wireshark and identifies the loads and performance of the network. The report explains the data captured, significance of the project, and the output of the graphs in terms of network performance. The report includes different types of graphs such as load distribution, throughput, time sequence, flow graph and windows scaling graph for analysing the performance.

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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 1a – Explanation of the data captured..........................................................................................2
Task 1b – Significance of the project.....................................................................................................4
Task 2 – Explanation of the output of the graphs in terms of network performance..........................12
Conclusion...........................................................................................................................................12
References...........................................................................................................................................14
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NETWORKED APPLICATIONS
Introduction
Th report is prepared for the analysis of a network solution using the network monitoring
tool and identification of the loads and performance of the network. Wireshark is used for
identification of the performance parameters and development of the analytical skill for capturing
live data traffic from the network and generate graphs for the analysis of the protocols used for
communication. The performance of the distributed system should be analysed and the graphs and
the browsing data should be analysed for the justification of the effect. The protocols listed in the
protocol column are listed and appropriate screenshot are added in the report for its demonstration.
Three different websites are visited and the packet is captured using Wireshark for the analysis of
each of the website. The use of the Wireshark helps in analysis of the port number and the Ip
address of the source and the destination address and management of the flow of the data packet in
the network. It helps in analysis of the security and the network and can be used by the network
administrator for monitoring the data flow of the network. The interface of a client computer is used
for capturing the data packets and different types of graphs are generated for the identification of
the sequence, throughput, flow graph and scaling graph.
Task 1a – Explanation of the data captured
A. The three different types of protocols that are seen in the protocol column when the packet
list is unfiltered are as follows:
UDP
TCP, and
ARP
The following screenshot is given for supporting the answer
B. The time taken for the HTTP GET request to HTTP OK reply is given in the following frames.
The arrival time and the time delta for the previous packet can be fetched from the captured
packet with the details such as the frame number, packet length and the capture length.
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NETWORKED APPLICATIONS
The two frames i.e. one for the GET request and the one for the OK reply message is
analysed and the time is noted and they are subtracted for finding the time taken until the
HTTP OK reply message is received. Here the difference between the times are
.43960400 - .426032000
= 0.013572 sec
C. The internet address of gai.cs.umass.edu is 192.168.43.1
The internet address of the client computer is 192.168.43.173
This is analysed from the following frame of the packet captured
Frame 32: 77 bytes on wire (616 bits), 77 bytes captured (616 bits) on interface 0
Ethernet II, Src: HonHaiPr_f2:4c:ed (9c:30:5b:f2:4c:ed), Dst: VivoMobi_d1:30:ad
(dc:1a:c5:d1:30:ad)
Internet Protocol Version 4, Src: 192.168.43.173, Dst: 192.168.43.1
0100 .... = Version: 4
.... 0101 = Header Length: 20 bytes (5)
Differentiated Services Field: 0x00 (DSCP: CS0, ECN: Not-ECT)
Total Length: 63
Identification: 0x0055 (85)
Flags: 0x0000
Time to live: 128
Protocol: UDP (17)
Header checksum: 0x625a [validation disabled]
[Header checksum status: Unverified]
Source: 192.168.43.173
Destination: 192.168.43.1
User Datagram Protocol, Src Port: 64050, Dst Port: 53
Domain Name System (query)

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NETWORKED APPLICATIONS
Task 1b – Significance of the project
The performance of the following websites are analysed in terms of their load distribution,
throughput graph, time sequence graph, flow graph and window scaling graph. Each of the graphs
have different functionality such as:
Throughput graph – It is used for the analysis of the average throughput and the goodput
Window Scaling – It is used for the analysis of the window size and the outstanding bytes
Time sequence – it is used for the generation of a simple graph that is quite similar with the tcptrace
and includes the forward segments, selective acknowledgement, zero windows and the reverse
window size.
Flow Graph – It is used for the demonstration of the flow of the data packets and the messages
between the client and the server.
There are different filters that can eb applied in wireshark for getting more specific result and
optimizing the result of the analysis of the network performance.
https://www.sbs.com.au/news/
Load Distribution
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Throughput Graph
Time Sequence Graph
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Flow Graph (general and TCP flow)
Window Scaling Graph

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https://www.amazon.com.au
Load Distribution
Throughput Graph
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Time Sequence Graph
Flow Graph (general and TCP flow)
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NETWORKED APPLICATIONS
Window Scaling Graph
http://howeverythingworks.org/
Load Distribution

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Throughput Graph
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Time Sequence Graph
Flow Graph (general and TCP flow)
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Window Scaling Graph
Task 2 Explanation of the output of the graphs in
terms of network performance
TCP Stream Graph
The generation of the throughput graph helps in analysis of the stability of the website and
identification of any problem for transferring the data packets and media files between the client
and the server. In the right hand side of the graph the average throughput is displayed for the
identification of the bandwidth utilization of the current network.
Time Sequence Graph
The generation of the time sequence graph helps in identification of the tcp packet ranging
between 0 – 900 for a time limit of 0.6 sec.
Conclusion
After the analysis of the three websites it can be concluded that the performance of the
distributed system can be analysed and the effects of the different types of browsing data are
analysed using the graph and justification of its effects. Different types of graphs such as load
distribution, throughput, time sequence, flow graph and windows scaling graph are generated from

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NETWORKED APPLICATIONS
the captured packet of the different websites for analysing the performance. The time taken for
seeking the HTTP request and receiving of the reply from the server are analysed that helps in
gathering the details of the data flow and the screenshots are attached in the report for the
demonstration of the performance of the network. The wireshark can be used for analysis of
different types of data transmission such as audio streaming, media and information transmission. It
can be used as a web analytical tool and used for comparing the website performance with the
application of different filters and graphs.
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References
[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.
[8]. Armstrong, M.E., Jones, K.S., Namin, A.S. and Newton, D.C. What Vulnerability Assessment
and Management Cybersecurity Professionals Think Their Future Colleagues Need to Know.
In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (pp.
1082-1082). ACM., 2018, February.
[9]. Atwater, E., Bocovich, C., Hengartner, U. and Goldberg, I. Live Lesson: Netsim: Network
simulation and hacking for high schoolers. In 2017 {USENIX} Workshop on Advances in
Security Education ({ASE} 17). USENIX} Association}., 2017 August.
[10]. Cuppens, F. WirelessHART NetSIM: A WirelessHART SCADA-Based Wireless Sensor
Networks Simulator. In Security of Industrial Control Systems and Cyber Physical Systems:
First Workshop, CyberICS 2015 and First Workshop, WOS-CPS 2015 Vienna, Austria,
September 21–22, 2015 Revised Selected Papers (Vol. 9588, p. 63). Springer., 2016, June.
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