Achieving Low-Latency H2M Communications through Predicting Bandwidth Demand: A Comparative Study of Statistical Prediction and Machine Learning Techniques

Bandwidth demand prediction is crucial in reducing uplink latency of human-to-machine traffic in future converged networks. A comprehensive review of existing statistical prediction and state-of-the-art machine learning techniques is presented.

Computer Science Engineering

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Achieving Low-Latency H2M Communications through Predicting Bandwidth Demand: A Comparative Study of Statistical Prediction and Machine Learning Techniques

Semantic Scholar · Computer Science · 2019

Abstract

Bandwidth demand prediction is crucial in reducing uplink latency of human-to-machine traffic in future converged networks. A comprehensive review of existing statistical prediction and state-of-the-art machine learning techniques is presented.

Source of record · Semantic Scholar

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