Machine Learning and Data Networks: Perspectives, Feasibility, and Opportunities
Autor: | Pablo Lozada-Yánez, Raúl Lozada-Yánez, Fernando Molina-Granja, Jonny Guaiña-Yungan |
---|---|
Rok vydání: | 2020 |
Předmět: |
Computer science
business.industry 020206 networking & telecommunications 02 engineering and technology Machine learning computer.software_genre Field (computer science) 020202 computer hardware & architecture Network planning and design Network congestion Traffic classification Workflow Work (electrical) 0202 electrical engineering electronic engineering information engineering Key (cryptography) Artificial intelligence business computer Interdisciplinarity |
Zdroj: | Trends and Innovations in Information Systems and Technologies ISBN: 9783030456900 WorldCIST (2) |
Popis: | Currently, Machine Learning has become a research trend around the world and its application is being studied in most fields of human work where it is possible to take advantage of its potential. Current computer networks and distributed computing systems are key infrastructures that have allowed the development of efficient computing resources for Machine Learning. The benefits of Machine Learning mean that the data network itself can also use this promising technology. The aim of the study is to provide a comprehensive research guide on networking (networking) assisted by machine learning to help motivate researchers to develop new innovative algorithms, standards, and frameworks. This article focuses on the application of Machine Learning for Networks, a methodology that can stimulate the development of new network applications. The article presents the basic workflow for the application of Machine Learning technology in the field of networks. Then, there is also a selective inspection of recent representative advances with explanations of its benefits and its design principles. These advances are divided into several network design objectives and detailed information on how they perform at each step of the Machine Learning Network workflow is presented. Finally, the new opportunities presented by the application of Machine Learning in the design of networks and collaborative construction of this new interdisciplinary field are pointed out. |
Databáze: | OpenAIRE |
Externí odkaz: |