Quality Control of Mobile Communication Management Services in a Hybrid Environment

There is an integration of telecommunication systems and distributed computing environment, resulting in a single hybrid environment for telecommunication services. The hybrid environment has the ability to control the information flow process at each stage and ensure compliance with high quality standards. Providing the quality of service to end-users of communication networks depends on quality control at all stages of the provision of the service. Today, due to the dynamically changing service structure provided to end users, constantly changing requirements for service quality indicators, with increasing traffic volumes, there is a growing need for well-scalable communication systems that meet the needs of end-users, gaining special significance service management systems. In the article the features of quality control service servicing of flows of the mobile communication network are investigated with the use of partial virtualization of network functions. An architectural solution is proposed for organization of service flows in a hybrid environment, which includes a telecommunication communication network and cloud computing resources that provide maintenance of virtualized functions involved in the organization of service flows. The solution for improvement of the PCRF system as well as a number of procedures that allow ensuring quality control of servicing streams as well as controlling the computing resources of a hybrid system, whose work affects the quality of service of service flows of the system, is proposed

An overview of machine learning and 5G for people with disabilities

Currently, over a billion people, including children (or about 15% of the world’s population), are estimated to be living with disability, and this figure is going to increase to beyond two billion by 2050. People with disabilities generally experience poorer levels of health, fewer achievements in education, fewer economic opportunities, and higher rates of poverty. Artificial intelligence and 5G can make major contributions towards the assistance of people with disabilities, so they can achieve a good quality of life. In this paper, an overview of machine learning and 5G for people with disabilities is provided. For this purpose, the proposed 5G network slicing architecture for disabled people is introduced. Different application scenarios and their main benefits are considered to illustrate the interaction of machine learning and 5G. Critical challenges have been identified and addressed.This work has been supported by the Agencia Estatal de Investigación of Ministerio de Ciencia e Innovación of Spain under project PID2019-108713RB-C51 MCIN/ AEI /10.13039/501100011033.Postprint (published version

Mecanismos para la gestión eficiente del plano de control y del plano de datos en redes móviles 5G

En los últimos años, el incremento exponencial del tráfico de datos móviles, unido al despliegue de nuevos servicios sobre las redes actuales, han propiciado que los operadores de telecomunicaciones busquen nuevos mecanismos que permitan una gestión eficiente de la red. En este contexto, uno de los procesos involucrados en la gestión de la red es el soporte a la movilidad, cuyo principal objetivo es mantener las comunicaciones activas mientras los usuarios se mueven entre redes diferentes. A tal efecto, se han estandarizado protocolos para la gestión de movilidad centralizada (CMM) y distribuida (DMM), pero debido a la densificación de celdas producida por el incipiente desarrollo de 5G, se está produciendo un incremento de tráfico de señalización usado para gestionar la movilidad, que debe ser tenido en cuenta por los operadores de red. Partiendo de esta situación, en esta tesis se proponen tres nuevos mecanismos para mejorar el rendimiento de las redes móviles desde tres perspectivas diferentes. Nuestra primera propuesta, TEDMM, permite llevar a cabo una gestión eficiente del plano de control. La segunda propuesta, SRDMM, combina SDN con DMM para mejorar el proceso de gestión de la movilidad desde el punto de vista del plano de datos. Nuestro tercer mecanismo (LNA) propone una estrategia de asociación entre estaciones base y la red de acceso para mejorar el rendimiento del plano de control y del plano de datos.In recent years, the world has witnessed an explosion of mobile communications due to the wide penetration of handheld mobile devices generating an unprecedented amount of data traffic. As the number of mobile users grows rapidly, 5G networks are evolving to match this growth and to ensure emerging services and applications according to the specific demands of mobile users. In such a challenging environment, effective mobility management mechanisms are needed and they are expected to serve mobile users with distinct mobility profiles The mobility management mechanisms provide seamless mobility support at the network level by maintaining ongoing communications while the users roam among different access networks. However, this mobility management protocols introduce signaling overhead for supporting seamless session continuity of the mobile nodes by using control messages between mobility agents. This aspect, together with the cell densification produced by 5G, will increase total signaling traffic, degrading the QoS and QoE requirements. Thus, the operators are seeking innovative solutions to the optimization of mobility management procedures within the 5G evolved architecture. In this Thesis, we propose three mechanisms in order to improve the performance of mobility management protocols. First, we propose a novel mechanism, called TE-DMM, to improve the performance of the control plane by reducing the signaling traffic. Then, taking advantage of the benefits that SDN brings, we present a novel mobility management solution to improve the performance of the data plane. Finally, we propose a novel link-network assignment strategy to enhance the overall performance of the mobility protocols