Machine Learning and Data Analytics for Communication Networks in the 5G Era

Dear Colleagues,

The next generation (5G) of communication networks will target unprecedented performance, in terms of network capacity, Quality of Service, network availability, user-experience, etc. In this context, the cloud computing and Network Function Virtualization (NFV) paradigms, together with the support of optical networking, play key roles, which are expected to enable 5G networking.

Advanced mathematical tools, such as those in the field of Machine Learning (ML) and Big Data Analytics, also represent an extremely important opportunity to help telecom operators with the design, operation and maintenance of their networks, especially if considering the continuous increase in network complexity. As a matter of fact, thanks to the possibility of efficiently leveraging large amounts of data, ML tools are expected to improve 5G networks through automation and self-optimization.

The scope of this Special Issue is on the most recent applications of ML and Big Data Analytics on the design and operation of next-generation networks. Topics accepted in the Special Issue include (but are not limited to) the following:

• Use of ML and data analytics in the Cloud, Mobile Edge Computing and Data Center Networks
• Network Function Virtualization and Service Function Chaining with ML
• Network telemetry, monitoring and data collection
• Applications of ML to next-generation wired/wireless networks
• ML for 5G-services traffic classification and forecast
• Resource allocation using ML
• Cross-layer network optimization with ML
• Failure prediction, detection and management with ML
• Reinforcement learning for network control

Dr. Francesco Musumeci
Dr. José Alberto Hernández
Dr. Ignacio de Miguel
Guest Editors

Manuscript Submission Information

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