# Customer-Oriented Quality of Service Management Method for the Future Intent-Based Networking
## 5 Discussion  
In fact, modeling the influence of context parameters on customer satisfaction and their display on a single QoE scale is a complex process, which is due to the presence of a large number of objective and subjective factors. Some of these factors can be measured, while others can be hidden and have an effect indirectly. In this case, these factors are often considered either separately, or their display on different scales. Evolutionary development of social and economic processes and information technologies impose time constraints on the relevance of QoE models. The question of taking into account the non-stationarity of needs and expectations of customers of information and telecommunication services when assessing QoE is open. Thus, due to the shift of emphasis on technical issues to business issues and the need to take into account the dominant nature of qualitative, uncertain, and vague factors in forming an opinion on the level of quality of network services, the use of methods of intellectual data analysis is justified and expedient in our future work. The results are obtained during the simulation of the traditional network, with the introduction of the controller, which:  
* Provides billing to customers;
* Collects network statistics;
* Collects statistics about service quality. The main disadvantages of using traditional networks are:  
* Weak integration with the billing system;
* Slow response to changing network topology;
* Slow response (or not at all) to the network's load, which is dependent on system administrators;
* There is no way to \"conduct\" a session in the controller;
* Unnecessary signal traffic that floods the network, and others. Figure 32: The average waiting time for TCP/UDP services using the proposed method. Almost all problems are related to the time of establishing the network's consistency in its aspects. Consider the problems of traditional networks when deciding on routing using the proposed method (balancer). Since it is proposed to store not only the best route to a certain network, but all possible (without loops) and corresponding loading of this routes, this load is displayed as the highest load on all transitions. The advantages of this method are: we share the boot network on several interfaces and share, if possible, the ways of serving UDP traffic and TCP. The main problem with the use of this method in traditional networks is the time of setting the consistency. Since the decision must be taken immediately, the network may miss some kind of peak change of traffic. The solution will be based on load from the routing table, but for the time the information goes to this router, the load bandwidth of the path may increase, causing the corresponding problems (path overloading, packet buffering, rejection, and re-send). This example is depicted in Figure 33.  
This graphic shows the schedule of served traffic on the network. Circles show the time when the decision is made. Accordingly, in this case, the network can \"skip\" changes in load, and not make the best decisions. All of these problems are solved in the transition to new generation networks, for example IBN; the controller collects statistics from each node. To set the consistency of the information, a minimum amount of time is required, which in turn improves the work of the balancer (there will be no more cases of \"spikes\" of peaks), allows us to \"conduct\" the session (the possibility of rejecting the permitted number of packets in the sending process, if necessary), makes the network susceptible to changes in topology, and others. Further development of the proposed method is carried out in the direction of improving the machine learning algorithms and methods of forming statistical samples characterizing the network parameters with known assessments of QoE. The algorithms of machine learning developed in the future work will form the decisive rules allowing to predict, in real-time, the desired level of QoE for customers automatically.