Salama, A.; Saatchi, R.; Burke, D. Fuzzy Logic and Regression Approaches for Adaptive Sampling of Multimedia Traffic in Wireless Computer Networks. Technologies2018, 6, 24.
Salama, A.; Saatchi, R.; Burke, D. Fuzzy Logic and Regression Approaches for Adaptive Sampling of Multimedia Traffic in Wireless Computer Networks. Technologies 2018, 6, 24.
Salama, A.; Saatchi, R.; Burke, D. Fuzzy Logic and Regression Approaches for Adaptive Sampling of Multimedia Traffic in Wireless Computer Networks. Technologies2018, 6, 24.
Salama, A.; Saatchi, R.; Burke, D. Fuzzy Logic and Regression Approaches for Adaptive Sampling of Multimedia Traffic in Wireless Computer Networks. Technologies 2018, 6, 24.
Abstract
Electronic-health applications rely on large computer networks to facilitate patients' information access and to communicate various types of medical data. To examine the effectiveness of these networks, the traffic parameters need to be analysed. Due to quantity of the information carrying packets, examining each packet's transmission parameters individually is not practical, especially when a real time operation is needed. Sampling allows a subset of packets that accurately represents the original traffic to be formed. In this study an adaptive sampling method based on regression and fuzzy inference system was developed. It dynamically updates the number of packets sampled by responding to the traffic variations. Its performance was found to be superior to the conventional non-adaptive sampling methods.
Keywords
e-health, computer network traffic sampling, multimedia transmission, quality of service.
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Comment 1
Received:
6 February 2018
The commenter has declared there is no conflict of interests.
Comment:
Adaptive sampling of network traffic is important technique. This article propose a novel adaptive sampling mechanism of network traffic that could change sampling interval based on traffic behaviour.
The commenter has declared there is no conflict of interests.