Probabilistic classification of quality of service in wireless computer networks

SALAMA, Abdussalam and SAATCHI, Reza (2018). Probabilistic classification of quality of service in wireless computer networks. ICT Express.

[img]
Preview
PDF
Probabilistic Classification QoS in Wireless Computer Networks 17 09 2018 (2).pdf - Accepted Version
Creative Commons Attribution.

Download (915kB) | Preview
[img] PDF (Evidence of paper's acceptance)
Acceptance Confirmation.pdf - Additional Metadata
Restricted to Repository staff only

Download (349kB) | Contact the author
Official URL: https://www.journals.elsevier.com/ict-express
Link to published version:: https://doi.org/10.1016/j.icte.2018.09.001
Related URLs:

Abstract

There is an increasing reliance on wireless computer networks for communicating various types of time sensitive applications such as voice over internet protocol (VoIP). Quality of service (QoS) can play an important role in wireless computer networks as it can facilitate evaluation of their performance and can provide mechanisms to improve their operation. In this study probabilistic neural network (PNN) and Bayesian classification were developed to process delay, jitter and percentage packet loss ratio for VoIP traffic. Both methods successfully categorized the transmission of VoIP packets into low, medium and high QoS categories but overall the Bayesian approach performed more accurately than PNN. By accurately determining the network's QoS, an improved understanding of its performance is obtained.

Item Type: Article
Uncontrolled Keywords: Quality of service, wireless computer networks, Bayesian classification, probabilistic neural network
Research Institute, Centre or Group - Does NOT include content added after October 2018: Materials and Engineering Research Institute > Centre for Automation and Robotics Research > Mobile Machine and Vision Laboratory
Departments - Does NOT include content added after October 2018: Faculty of Science, Technology and Arts > Department of Engineering and Mathematics
Identification Number: https://doi.org/10.1016/j.icte.2018.09.001
Depositing User: Reza Saatchi
Date Deposited: 05 Oct 2018 14:51
Last Modified: 16 Nov 2018 12:05
URI: http://shura.shu.ac.uk/id/eprint/22739

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics