Quality of service management for an intent-based heterogeneous network using mobile QoE application

Abstract

Traditional Service Level Agreement (SLA) based on the quality of service (QoS) management methods are insufficient to ensure quality-related contracts between service providers and users. This article proposes a user-centric method for QoS management in heterogeneous mobile networks. Based on a new QoE metric on a scale of 1 to 5, this method considers the commercial value of electronic services to end-users. With this approach, the configuration and functionality of the network automatically change depending on the requirements of the end-users. The work proposes a conceptual model for constructing an intent-based software-defined heterogeneous network, which effectively manages shared resources and adapts to users’ needs. A prototype of a mobile and operator application for adaptive client-oriented service delivery in a heterogeneous network has been developed, which makes it possible to obtain the ordered QoE based on the feedback between the user and the network operator. Using this approach will allow network operators to provide individualization of service users with a certain level of QoS by analyzing their estimates of QoE (ordered through the developed mobile application). And the use of machine learning algorithms will allow to react to unfavorable combinations of values of quality indicators and prevent the situation when the user is not satisfied with the quality of services received for adaptive prediction of the moment of network reconfiguration. We propose a method for managing the QoS provision in a heterogeneous wireless network using Big Data technology and a mobile QoE application, which considers and analyzes the estimates of the ordered QoE and allows users QoS improvement according to the demand. It is demonstrated that using the proposed method in a heterogeneous wireless network allows reducing the number of dissatisfied users with the quality of service by up to 60% using an experimental study.