Machine Learning and Its Applicability in Networking
Amit Jain, Anand Nayyar
Abstract
Machine learning (ML) plays an all-important role in applications that involve problem-solving and enabling automation in different areas. The main reason behind this turnaround is the voluminous amount of data availability, vast modifications in ML techniques along with development in computational strategies as a whole. Out of all these, ML is enormously having key importance in several common and complex issues coming up in operations and management in networking. As of date, several studies have been undertaken in relation to various upcoming fields of research in networking or for particular technologies related to it. In this chapter, quite a few applications of ML have been discussed in relation to important fields of networking in association with emerging technologies in it. The readers of this chapter will be benefited from a novel insight into the concepts of web network analysis by going through several principle and theories of ML and their application in networking. This includes traffic prediction, congestion control, routing, and classification, resource management, and fault management along with network security as major concepts of learning. Also, this study will focus on the challenges in research and provide insight into future aspects to look into rising prospects of applying ML in networking. Hence, this will act as an apt involvement towards the issues and challenges of ml in networking in relation to the analysis of web-based networking. This will enable carrying forward the study to new 58heights by studying the several aspects related to automated operations in networking and their related management.