Abstract
The internet is increasingly present in people’s lives, being used in diverse tasks, such as checking e-mail up to online gaming and streaming. The so-called "killer applications" are applications that, when not properly identified and prevented, have more impact on the network, making it slow. When these applications are used on networks with limited resources, as happens in rural networks, they cause a large load on the network, making it difficult its use for work purposes. It is important then to recognize and characterize this traffic to take action so that it does not cause network problems. With that in mind, the work presented in this paper describes the research and identification of cost free traffic analysis solutions that can help to overcome such problems. For that, we perform preliminary testing and a performance comparison of those tools, focusing on testing particular types of network traffic. After that, we describe the analysis and subsequent modification of the source code for storing important traffic data for the tests, as well as the test scenarios in laboratory and real-life environments. These tasks are aimed on collecting information that assists in taking action to improve the allocation of network resources to priority traffic.
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References
Internet World stats, “Usage and population statistics”, http://www.internetworldstats.com/stats.htm (date accessed, January 2014)
Liew, J.H., Yeo, A.W., Hamid, K.A., Othman, A.K.: Implementation of wireless networks in rural areas. Computer Science and Information Tech., Malaysia Univ., Sarawak (2004)
Feitosa, E., Souto, E., Sadok, D.H.: An orchestration approach for unwanted Internet traffic identification. Computer Networks 56(12), 2805–2831 (2012)
Mueller, M.L.: Convergence of control? Deep packet inspection and the future of the internet. Communications & Convergence Review 2(2), 92–103 (2010)
IANA, Protocol Numbers, http://www.iana.org/assignments/protocol-numbers/protocol-numbers.xml (date accessed, January 2014)
ntop, “ntop”, http://www.ntop.org/ (date accessed, January 2014)
Bujlow, T., Carela-Español, V., Barlet-Ros, P.: Comparison of Deep Packet Inspection (DPI) Tools for Traffic Classification. Technical Report, Universitat Politècnica de Catalunya (2013)
Gomes, J.V., Inácio, P.R.M., Pereira, M., Freire, M.M., Monteiro, P.P.: Detection and Classification of Peer-to-Peer Traffic: A Survey. ACM Computing Surveys 45(3), 1–40 (2013)
Wireshark, “Wireshark”, http://www.wireshark.org/ (date accessed, January 2014)
LinuxQuestions, “Tcpdump with cron”, http://www.linuxquestions.org/questions/linux-software-2/tcpdump-with-cron-121727/ (date accessed, January 2014)
Salvador, N., Filipe, V., Rabadão, C., Pereira, A.: Management Model for Wireless Broadband Networks. In: 3rd International Conference on Systems and Networks Communications, pp. 38–43. ICSNC (2008)
ntop, “ntopng”, http://www.ntop.org/ (date accessed, January 2014)
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© 2014 Springer International Publishing Switzerland
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Emiliano, R., Silva, F., Frazão, L., Barroso, J., Pereira, A. (2014). Traffic Management in Rural Networks. In: Marcus, A. (eds) Design, User Experience, and Usability. User Experience Design for Everyday Life Applications and Services. DUXU 2014. Lecture Notes in Computer Science, vol 8519. Springer, Cham. https://doi.org/10.1007/978-3-319-07635-5_44
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DOI: https://doi.org/10.1007/978-3-319-07635-5_44
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07634-8
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