no code implementations • 3 Jun 2019 • Amin Azari, Panagiotis Papapetrou, Stojan Denic, Gunnar Peters
In this paper, we study the problem of network traffic traffic prediction and classification by employing standard machine learning and statistical learning time series prediction methods, including long short-term memory (LSTM) and autoregressive integrated moving average (ARIMA), respectively.
no code implementations • 9 May 2019 • Amin Azari, Panagiotis Papapetrou, Stojan Denic, Gunnar Peters
Traffic prediction plays a vital role in efficient planning and usage of network resources in wireless networks.