Wireless Network Traffic Analysis and Troubleshooting using Raspberry Pi

  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract

    In the past five decades, computer network has kept up growing with the increases of its complexity. In such situation, the management, monitoring and maintenance of such computer network requires special attention to ensure optimal network access capability is achieved. Wireless network traffic analysis is a process of recording, studying and analyzing packets in wireless network for network performance analysis purposes. In some cases, the quality of network access performance can be very low without knowing the actual problem. Therefore, in this paper, the performance of wireless network traffic is proposed to be analyzed by using a Raspberry Pi which further able to send an alert to network admin to lessen the downtime. Raspberry Pi is a low cost, a small and portable size of a computer board that can be used to plug-in to monitor, keyboard, mouse, pen drive, etc. In this project, a MyTraceroute (MTR) program is installed on the Raspberry Pi to capture the IP of the Access Point (AP) and show packets loss percentage in the network. The results will be saved in the form of text file and sent to network admin by using email. The solution proposed in this paper is able to support solution to a problem on efficient monitoring, managing and maintaining wireless network traffics.  



  • Keywords

    Network Traffic Analysis; Raspberry Pi; Network Troubleshooting

  • References

      [1] Zhao, C. W. (2015). Exploring IOT Application Using Raspberry Pi. International Journal of Computer Network and Application, 27-34.

      [2] Maksimovic, V. V. (2014 ). Raspberry Pi as a Wireless Sensor node: Performances and Constraints. Information and Communication Technology, Electronics and Microelectronics (MIPRO), 27-34.

      [3] Ishida, Shigemi, et al. (2015). Wifi AP-RSS Monitoring using Sensor Nodes toward Anchor-free Sensor Localization. IEEE. Tokyo.

      [4] Tariq, A.K., ZIyad, A.T., & Abdullah, A.O. (2013). Arduino Wi-Fi network analyzer. Procedia Computer Science, 522-529.

      [5] Vamsikrishna, P., Kumar, S, D., Hussain, S. R., & Naidu, K.R. . (March, 2015). Raspberry Pi Controlled SMS-Update-Notification (Sun) System. IEEE International Conference (pp. 1-4). IEEE.

      [6] Zafar, S., & Carranza, A. (n.d.). Motion Detecting Camera Security System with Email Notifications and Live Streaming Using Raspberry Pi. Conference of American Society for Engineering Education, (pp. 1-5).

      [7] BIBLIOGRAPHY Biswas, J. (2014). An Insight to Network Traffic Analysis using Packet Sniffer. International Journal of Computer Applications Volume 94, 39-44.

      [8] Cecil, A. (n.d.). A Summary of Network Traffic Monitoring and Analysis Techniques. 1-8.

      [9] Danezis, G. (n.d.). Introducing Traffic Analysis Attacks, Defencs and Public Policy Issues. 1-12.

      [10] Dhillon, N. K. (2012). Enterprise Network Traffic Monitoring, Analysis and Reporting using WINPCAP Tool with JPCAP API. International Journal of Advanced Research in Computer Science and Software Engineering, 95-101.

      [11] Goldsmith, D. (1998). a Traceroute-Like Analysis of IP Packet

      Responses to Determine Gateway Access Control Lists. Cambridge Technology Partners, 1-14.

      [12] Hasan, M. K. (2012). IEEE 802.11b Packet Analysis to Improve

      Network Performance. JU Journal of Information Technology (JIT), Vol 1, 27 34.

      [13] Hasib, M. (2006). Analysis of Packet Loss Probing in Packet Networks. 1-180.

      [14] Patel, P. A. (2012). Network Traffic Analysis Using Packet Sniffer. International Journal of Engineering Research and Application, 854-856.

      [15] Qadeer, M. A. (2010). Network Traffic Analysis and Intrusion Detection using Packet Sniffer. Second International Conference on Communication Software and Networks, 313-317.




Article ID: 11213
DOI: 10.14419/ijet.v7i2.15.11213

Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.