Fuzzy Logic and Regression Approaches for Adaptive Sampling of Multimedia Traffic in Wireless Computer Networks

Abdussalam Salama,Derek Burke,Reza Saatchi

doi:10.3390/technologies6010024

Abdussalam Salama, Derek Burke + Show 1 more

Open Access

https://doi.org/10.3390/technologies6010024

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Abstract

Organisations such as hospitals and the public are increasingly relying on large computer networks to access information and to communicate multimedia-type data. To assess the effectiveness of these networks, the traffic parameters need to be analysed. Due to the quantity of the data packets, examining each packet’s transmission parameters is not practical, especially in real time. Sampling techniques allow a subset of packets that accurately represents the original traffic to be examined and they are thus important in evaluating the performance of multimedia networks. In this study, an adaptive sampling technique based on regression and a fuzzy inference system was developed. The technique dynamically updates the number of packets sampled by responding to the traffic’s variations. Its performance was found to be superior to the conventional nonadaptive sampling methods.

Highlights

The growing availability of mobile wireless devices such as tablets, smartphones, and wearable monitoring sensors have resulted in innovative technologies dedicated for organisations and individuals
The Euclidean distance (ED) shown in Equation (6) was used to quantify the variation in the behaviour of the traffic associated with the pre- and post-sampling sections
The results demonstrate that the adaptive0.005 sampling approach has the lowest relative standard errors (RSE) compared with nonadaptive sampling methods

Summary

Introduction

The growing availability of mobile wireless devices such as tablets, smartphones, and wearable monitoring sensors have resulted in innovative technologies dedicated for organisations and individuals. Several technologies have been reported for improving information access, enhancing patients’. Experience, managing resources, and increasing the standard of treatment in healthcare environments. These include electronic health (eHealth), mobile health (mHealth), authentication and tracking, remote monitoring, consultation and diagnosis services, and mobile tele-monitoring [1]. These technologies and associated services are becoming increasingly real time and require computer networks with improved performance [2]. The transmission of multimedia traffic associated with these services over wired and wireless computer networks creates demands on bandwidth and other resources [2,3]

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Results

Conclusion