QoS Evaluation Based on Fuzzy Neural Networks

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.