Traffic Prediction Based Transmission in Satellite-Terrestrial Networks

Abstract

AbstractThis part considers the resource allocation problems for video transmission in space based information networks. The queueing system analyzed in this work is constituted by multiple users and a single server. The server is operated as a cloud that can sense the traffic arrivals to each user’s queue, and then allocates the transmission resource and service rate for users. The objectives are to make configurations over time to minimize the time average cost of the system, and to minimize the waiting time of packets after they enter the queue. Meanwhile, the constraints on the queue stability of the system must be satisfied. In this part, we introduce a predictive backpressure algorithm, which considers the future arrivals with a certain prediction window size, into the consideration of resource allocation to make decision on which packets to be served first. In addition, this part designs a multi-resolution wavelet decomposition based backpropagation network for the prediction of video traffic, which exhibits the long-range dependence property. Simulation results indicate that the delay of the queueing system can be reduced through this prediction based resource allocation, and the prediction accuracy for the video traffic is improved according to the proposed prediction system.KeywordsSpace-based Information NetworksResource AllocationVideo Traffic PredictionCloud ServiceQueueing TheoryPredictive Backpressure