Abstract
A scheduler is a key component of Internet of Things and edge computing. Some scholars and papers proposed many schedulers and scheduler algorithms. In this paper, we propose a smart scheduling algorithm based on Long-Short Term Memory (LSTM) of deep learning. After experimental testing of the positions of the moving object and server performance, the algorithm we proposed in here can efficiently predict the positions of the moving object in the near future and the server performance at the new location. This greatly solves the problem of communication and computing bottleneck in the Internet of Things and edge computing.