Title
Deep learning-based predictive analytics for decentralised content caching in the hierarchical edge network
Abstract
A content-centric network is a state-of-the-art networking architecture for content distribution and content caching. However, it is inefficient to cache every content in each network devices. The modern edge computing technology opens the door for content caching in the edge of the network. However, we still have to decide which contents we should cache and which content we should replace from the cache. The deep learning based predictive analytics can play an important role in selecting content for caching purposes. In this research, we will use LSTM based recurrent neural network for predictive content caching at the edge of the network.
Dataset