Cache-Aided Interactive Multiview Video Streaming in Small Cell Wireless Networks

The emergence of interactive multimedia applications with high data rate and low latency requirements has led to a drastic increase in the video data traffic over wireless cellular networks. Locally caching some of the contents at the small base stations of a macro-cell is a promising technology to cope with the increasing pressure on the backhaul connections, and to reduce the delay for demanding video applications. In this work, delivery of an interactive multiview video over an heterogeneous cellular network is studied. Differently from existing works that ignore the video characteristics, the caching and scheduling policies are jointly optimized, taking into account the quality of the delivered video and the video delivery time constraints. We formulate our joint caching and scheduling problem via submodular set function maximization and propose efficient greedy approaches to find a well performing joint caching and scheduling policy. Numerical evaluations show that our solution significantly outperforms benchmark algorithms based on popularity caching and independent scheduling

Cache-Aided Interactive Multiview Video Streaming in Small Cell Wireless Networks

The emergence of interactive multimedia applications with high data rate and low latency requirements has led to a drastic increase in the video data traffic over wireless cellular networks. Locally caching some of the contents at the small base stations of a macro-cell is a promising technology to cope with the increasing pressure on the backhaul connections, and to reduce the delay for demanding video applications. In this work, delivery of an interactive multiview video over an heterogeneous cellular network is studied. Differently from existing works that ignore the video characteristics, the caching and scheduling policies are jointly optimized, taking into account the quality of the delivered video and the video delivery time constraints. We formulate our joint caching and scheduling problem via submodular set function maximization and propose efficient greedy approaches to find a well performing joint caching and scheduling policy. Numerical evaluations show that our solution significantly outperforms benchmark algorithms based on popularity caching and independent scheduling