Comparative Study of Forecasting Schemes for IoT Device Traffic in Machine-to-Machine Communication

Abstract

We present a comparative study of Autoregressive Integrated Moving Average (ARIMA), Multi-Layer Perceptron (MLP), 1-Dimensional Convolutional Neural Network (1-D CNN), and Long-Short Term Memory (LSTM) models on the problem of forecasting the traffic gene