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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2 NETWORKED APPLICATIONS 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
3 NETWORKED APPLICATIONS 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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4 NETWORKED APPLICATIONS 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
5 NETWORKED APPLICATIONS 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.
6 NETWORKED APPLICATIONS http://www.cbsinteractive.com.au/ Load Distribution The load on thehttp://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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7 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
8 NETWORKED APPLICATIONS The flow of the data traffic and the information is analysed for the development of the network analysis report for the websitehttp://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/
9 NETWORKED APPLICATIONS Load Distribution The load distribution of thehttp://www.newspapers.com.au/server is analysed form the packet captured form the network interface. Throughput Graph
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10 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
11 NETWORKED APPLICATIONS The flow graph is created for the analysis of the flow of the data traffic in the network for connecting with thehttp://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.
13 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.
14 NETWORKED APPLICATIONS 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. InProceedings of the 22nd Annual International Conference on Mobile Computing and Networking(pp. 475-476). ACM., 2016, October.