On Optimization of Short Video Data Dissemination in Edge Networks

To optimize short video data dissemination in edge networks, we propose a novel 3-layered network model. Based on the model, we investigate the optimal edge caching node selection problem, which is proved NP-hard. We also analyzed the upper and lower bounds of the data dissemination range in our proposed model. We developed the graph-attention-based cache propagation for degree calculation (GACPD) to predict the dissemination scale of short video data for each caching node, and the graph embedding and GAT-based caching node selection (GEG) algorithm to select the optimal caching nodes. We implement the GEG algorithm and evaluate its performance on both real and simulated data sets. It is found that GEG can reduce the backbone network traffic by 30% to 50%, as well as with 18% to 30% network bandwidth utilization improvement, compared with the existing ICS and CDA algorithms.