Design and Analysis of a Network Traffic Analysis Tool: NetFlow Analyzer

  • Islam R
  • Patamsetti V
  • Gadhi A
  • et al.
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Abstract

A network analyzer can often comprehend many protocols, which enables it to display talks taking place between hosts over a network. A network analyzer analyzes the device or network response and measures for the operator to keep an eye on the network’s or object’s performance in an RF circuit. The purpose of the following research includes analyzing the capabilities of NetFlow analyzer to measure various parts, including filters, mixers, frequency sensitive networks, transistors, and other RF-based instruments. NetFlow Analyzer is a network traffic analyzer that measures the network parameters of electrical networks. Although there are other types of network parameter sets including Y, Z, & H-parameters, these instruments are typically employed to measure S-parameters since transmission & reflection of electrical networks are simple to calculate at high frequencies. These analyzers are widely employed to distinguish between two-port networks, including filters and amplifiers. By allowing the user to view the actual data that is sent over a network, packet by packet, a network analyzer informs you of what is happening there. Also, this research will contain the design model of NetFlow Analyzer that Measurements involving transmission and reflection use. Gain, insertion loss, and transmission coefficient are measured in transmission measurements, whereas return loss, reflection coefficient, impedance, and other variables are measured in reflection measurements. These analyzers’ operational frequencies vary from 1 Hz to 1.5 THz. These analyzers can also be used to examine stability in measurements of open loops, audio components, and ultrasonics.

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APA

Islam, R., Patamsetti, V. V., Gadhi, A., Gondu, R. M., Bandaru, C. M., Kesani, S. C., & Abiona, O. (2023). Design and Analysis of a Network Traffic Analysis Tool: NetFlow Analyzer. International Journal of Communications, Network and System Sciences, 16(02), 21–29. https://doi.org/10.4236/ijcns.2023.162002

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