An Approach to Data Analysis in 5G Networks

Abstract

5G networks expect to provide significant advances in network management compared to traditional mobile infrastructures by leveraging intelligence capabilities such as data analysis, prediction, pattern recognition and artificial intelligence. The key idea behind these actions is to facilitate the decision-making process in order to solve or mitigate common network problems in a dynamic and proactive way. In this context, this paper presents the design of Self-Organized Network Management in Virtualized and Software Defined Networks (SELFNET) Analyzer Module, which main objective is to identify suspicious or unexpected situations based on metrics provided by different network components and sensors. The SELFNET Analyzer Module provides a modular architecture driven by use cases where analytic functions can be easily extended. This paper also proposes the data specification to define the data inputs to be taking into account in diagnosis process. This data specification has been implemented with different use cases within SELFNET Project, proving its effectiveness.

Big Data in 5G Distributed Applications

“…Such traffic volume is not supported with nowadays cellular networks. Thus, practical deployment of 5G networking systems, in addition to traditional technology drivers, needs some new critical issues to be resolved on different areas such as: (1) coordination mechanism [3], (2) power consumption [4], (3) networking behavior prediction [5], (4) positioning and location-awareness [6] etc. Some operators already start their deployments and the standards process forward.…”

Data Mining on 5G Technology IOT

“…Through research and data analysis, there are expectations that complexity of these networks will be overcome and it will be possible to carry out dynamic management and operation activities. In order to full comprehend the particulars of 5G network, there are certain kind of information that should be gathered by network components in order to be analyzed by a data mining scheme [1] Mobile networks are already part of our daily lives, but what we expect from them is ever changing. Transforming today's networks to 5G is key to keeping pace with the demands of an evolving Networked Society, where opportunities span new high-bandwidth applications, low latency powered Internet of Things (IoT) services and beyond.…”

“…Through research and data analysis, there are expectations that complexity of these networks will be overcome and it will be possible to carry out dynamic management and operation activities. In order to full comprehend the particulars of 5G network, there are certain kind of information that should be gathered by network components in order to be analyzed by a data mining scheme [1]…”

“…However, a challenge that exists between the two drawing from the current research is that most of the studies focus on data mining algorithms to be employed in cellular mobile communications. However, they rarely produce detailed examples of the necessary information that ought to be collected, the frequency of time that the information should be collected and the mechanisms that can be used in the course of minimizing the data that needs to be exchanged among network constituents and functions [1].…”

Managing and Optimizing Quality of Service in 5G Environments Across the Complete SLA Lifecycle

“…The above-mentioned concept not only enables the main storage of the 5G infrastructure, but also, promotes the management and the exploitation of this information. As a result, recommendations mechanisms, or even predicting tools can be developed, providing the most suitable SLAs for the selected by the customers network service [12].…”