QoS Evaluation Based on Fuzzy Neural Networks
Khurrum Jalil, Khurrum Hussain, Asad Ahmad, Xiaolin Gui
Available Online September 2016.
- https://doi.org/10.2991/iccia-16.2016.84How to use a DOI?
- Neural Network; Fuzzy theory; Fuzzy neural networks; QoS Evaluations.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - 2016 International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2016) PB - Atlantis Press SN - 2352-538X UR - https://doi.org/10.2991/iccia-16.2016.84 DO - https://doi.org/10.2991/iccia-16.2016.84 ID - Jalil2016/09 ER -