# Customer-Oriented Quality of Service Management Method for the Future Intent-Based Networking
## 1 Introduction
The FN (Future Network) should memorize and analyze the state of the network and the corresponding evaluation of the quality of services by the customer and be able to adjust the network configuration based on the experience gained [8]. This approach can be implemented by introducing AI (Artificial Intelligence) into the SMS (Service Management System) [9; 10]. The main idea of using AI is to change the paradigm of the network infrastructure: it is no longer the customer with their application that adjusts to the possibilities of the network, but the network changes its settings to suit the requirements of the customer. The network configuration and functionality of the network equipment automatically change according to customer requirements [11]. The network not only responds to current customer requests, but also analyzes the customer's preferences and current environment, providing relevant information to the SMS. One of the effective approaches to AI implementation in intellectual electronic services management is application of modern methods--fuzzy logic and neural networks [12; 13; 14]. The most important advantage of neural networks is the possibility of their learning and adaptation, as well as the fact that full knowledge about the object of control (for example, its mathematical model) is not required. On the basis of input and set (reference) signals, the neural network can learn how to control the object. Neural networks can include a huge number of interconnected simple processing elements (neurons), which as a result, give enormous computational power when using parallel processing of information [15]. Fuzzy Control is currently one of the most promising intellectual technologies that allows the creating of high-quality control systems. The main advantage of the fuzzy logic method is the possibility to represent subjective categories in mathematical form. The system makes decisions based on rules recorded in the form of IF-THEN implication [16]. The simplest approach to the design of such systems consists of the formulation of control rules and an accessory function on the basis of results of the observation of the control process carried out by a person or already existing regulator, with further evaluation of correctness of such system functioning. If the project turns out to be unsuccessful, the function of the accessory and/or control rules can be easily modified. Implementation of quality management is carried out at the service and transport levels. At the same time, it is necessary to provide interaction with the management system both of new service providers, information providers, and consumers. The use of these approaches will allow, on the one hand, to bring the learning ability and computational power of neural networks into the SMS, and on the other hand, to use vague rules of decision making, which are peculiar to the \"human\" way of thinking. However, at present, the heads of telecommunication technology development and communications departments, responsible for the infrastructure and operation of information networks, have come to the conclusion that the large number, complexity, and frequency of introduction of new functions in the communication network needed a new approach that will radically change all aspects of network creation, service provision, and operational management. According to their conclusion, the capabilities of traditional networks are limited, do not meet modern requirements, and are a limiting factor on the way of innovative info-communication services. There was a need to move from a conservative approach of information networks deployment, which was used for a long time and provided for a small list of electronic services with standard methods of service quality management, to the creation of a new platform, which allows the introduction of a wide range of non-traditional services and provides an opportunity to adapt their quality of perception to individual customer requirements.