Traffic Model for Teleconsultation Based on the Service Characteristics

DOI

10.2991/cimns-18.2018.4How to use a DOI?

Keywords

service traffic model; video traffic; discrete autoregressive model; wavelet model

Abstract

The rapid development of numerous emerging network services poses a challenge to the network resources allocation with their bandwidth requirements and statistical characteristics. Network traffic modeling plays an important role in network resources allocation which can be used to guarantee Quality-of-Service (QoS) of these new services. In this study, we analyzed the service composition and traffic characteristics of the spreading teleconsultation service and establish a traffic model. The obtained experimental results show that the proposed methodology which combines discrete autoregressive model (DAR) and wavelet analysis provides good accuracy in teleconsultation service traffic modeling.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xin Yang
AU  - Ningbo Zhang
AU  - Guixia Kang
PY  - 2018/11
DA  - 2018/11
TI  - Traffic Model for Teleconsultation Based on the Service Characteristics
BT  - Proceedings of the 2018 3rd International Conference on Communications, Information Management and Network Security (CIMNS 2018)
PB  - Atlantis Press
SP  - 15
EP  - 19
SN  - 2352-538X
UR  - https://doi.org/10.2991/cimns-18.2018.4
DO  - 10.2991/cimns-18.2018.4
ID  - Yang2018/11
ER  -