Analysis of Technology for Building 5G Communication Network Infrastructure and Providing Artificial Intelligence Based Services
Students Name: Lavriv Mykola Mykolaiovych
Qualification Level: magister
Speciality: System Administration of Telecommunications Networks
Institute: Institute of Telecommunications, Radioelectronics and Electronic Engineering
Mode of Study: part
Academic Year: 2022-2023 н.р.
Language of Defence: ukrainian
Abstract: Fifth generation communication networks 5G/IMT-2020 and new types of services is particularly relevant research topic of the last 5-6 years, with the result of research and development on a global scale was a smooth transition to the concept of communication networks 2030 [1,2 ]. This transition has taken place due to the large number of new types of services emerging based on the Internet of Things concept. In turn, the concept of the Internet of Things has spawned other concepts, within which its own requirements for communication networks have been formed. At the moment, the "course" directly affecting the development of communication networks and services is the direction of "Artificial Intelligence in communication networks"[3]. Topics of Artificial Intelligence (AI) in communication networks in the world of scientific research has appeared quite recently and causes more and more interest from the side of scientific works and projects, as well as business and industry. At the moment, most of the works are on communication networks of the fifth generation, new services, Internet of Things technologies. However, the question of artificial intelligence in communication networks is a fairly recent research topic. Thus, the problems of building communication networks and services on the basis of Artificial Intelligence technologies, taking into account available developments in the field of AI, still not enough attention is paid [4,5]. In this area there is a number of high-level problems, one of which is the problem of identification of traffic in communication networks, load forecasting for the network and its devices, effective distribution of computing resources and tasks in the communication network. These tasks require the development of appropriate methods based on AI technologies, taking into account especially the requirements of the quality of service of prospective communication network services, the necessary speed of service services and knowledge of the predicted data. Thus, it is relevant to study the methods of building infrastructure and service provision of mobile communication networks using artificial intelligence technologies. The object of the study is the fifth generation communication networks 5G/IMT2020. The subject of the research is the peculiarities of the construction of these networks and services based on artificial intelligence technology. The aim of master’s qualification work is to study the process of building the infrastructure and services of communication networks using artificial intelligence technology. To achieve these goals in the work it is necessary to solve the following tasks: 1. to carry out a review of the features of the functioning of modern mobile communication networks; 2. to analyze the process of identification of traffic services in communication networks of the fifth generation; 3. to carry out a study of the interaction of fog and limit computation with the support of microservice architecture of services; 4. to present a method for predicting congestion on the controllers of softwareconfigured networks based on artificial intelligence technologies. Research Methods. To solve the problems we used methods of machine learning, optimization theory and simulation modeling. The scientific novelty of the results is to develop a framework for the interaction of distributed computing with microservices to combine cloud structures of multilevel edge computing and fog computing, as well as network infrastructure based on SDN/NFV technologies, which can reduce the distance between the user and the service to a minimum by placing service functions in the form of microservices on the Fog devices in terms of network and computing resources. The practical significance of the results is the possibility of their use in mobile communication networks to improve the quality of service for users.