吞吐量
计算机科学
机器学习
人工智能
深度学习
计算
预测建模
延迟(音频)
数据建模
无线网络
无线
电信
算法
数据库
作者
Dongwon Lee,Joohyun Lee
标识
DOI:10.1109/icufn49451.2021.9528756
摘要
Wireless communication contains many fluctuations than wired networks. In this paper, we present several machine learning and deep learning models to predict future network throughput, which is crucial for reducing latency in online streaming services. This paper explains the main components of the throughput prediction system. The throughput prediction model includes data input, data training, and prediction computation parts. This model accepts network throughput for the training data of the model and forecasts future data. We also present the advantages and limitations of utilizing AI models for throughput prediction. Finally, we believe that this study highlights the impact of deep learning techniques for throughput prediction.
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