Traffic Prediction with Network Slicing in 5G: A Survey

Abstract

In modern communication systems there are heterogeneous service request from the applications like mobile devices, virtual reality, automatic driving cars, IoT devices. These devices have different QoS requirements in which network slicing enabler plays a vital role in 5G. Network Slicing unfolds a new paradigm for the providers as well as for the users. In this context the resource management has gained importance in the field of networking. Since a huge data is been generated by these devices, it is very difficult to deliver high performance with resource utilization. In such situation these traditional monitoring techniques will not be able to handle such a huge data. Towards this, the researchers have started applying with Deep learning techniques with the network monitoring system. This paper focuses on the work done towards one of the key components of network analysis (i.e.) traffic prediction. This study has reviewed the articles, which have proposed the deep learning techniques for traffic prediction towards resource management in network slicing.*CRITICAL: Do Not Use Symbols, Special Characters, Footnotes, or Math in Paper Title or Abstract. (Abstract)