Enhancing latency performance through intelligent bandwidth allocation decisions: A survey and comparative study of machine learning techniques

Abstract

Converged access networks consolidating 5G and beyond and fixed optical fiber access are expected to support future latency-sensitive human-To-machine applications over the Tactile Internet. Making intelligent bandwidth allocation decisions among end users/machines/robots of the converged network is thus crucial to meeting stringent latency requirements. The recent renewed interest in machine learning (ML) has contributed towards a plethora of undeniable performance improvements in communication networks. Current insights into how ML can be exploited to provide intelligent bandwidth allocation decisions to enhance latency performance, along with guidance on the most suitable ML technique in ..