Prediction of information propagation in a drone network by using machine learning

Abstract

Drones cooperate with each other by transmitting and receiving packets. Therefore, it is important to conjecture the packet transmission rates within the network. However, the conventional methods are not suitable to describe the transmission patterns with satisfactory computing speed and accuracy. In this paper, we demonstrated that machine learning can successfully predict the transmission patterns in drone network. The packet transmission rates of a communication network with twenty drones were simulated, of which results were used to train the linear regression and Support Vector Machine with Quadratic Kernel (SVM-QK). We found out SVM-QK can precisely predict the communication between drones.