QoS Evaluation Based on Fuzzy Neural Networks

DOI

10.2991/iccia-16.2016.84How to use a DOI?

Keywords

Neural Network; Fuzzy theory; Fuzzy neural networks; QoS Evaluations.

Abstract

In order to improve the Quality of service (QoS) and the Quantity of user Experience, overlay network visualized the network application and underlay structure. An algorithm named MOO-GSON is proposed uses Multi-Objective Optimization (MOO) to construct the General Service overlay network (GSON) topology. With the MOO model, this algorithm has taken into account the reusing of nodes and links and matched the physical network. Visual topology decreases the cost of signal links and the overall network. A series of experimental simulation is designed to analyze the Algorithm performance. The results show that the algorithm has a better tradeoff in running time and performance than similar algorithms.

Copyright

© 2016, 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  - Khurrum Jalil
AU  - Khurrum Hussain
AU  - Asad Ahmad
AU  - Xiaolin Gui
PY  - 2016/09
DA  - 2016/09
TI  - QoS Evaluation Based on Fuzzy Neural Networks
BT  - Proceedings of the 2016 International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2016)
PB  - Atlantis Press
SP  - 454
EP  - 460
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-16.2016.84
DO  - 10.2991/iccia-16.2016.84
ID  - Jalil2016/09
ER  -