An Efficient and Adaptive Content Delivery System Based on Hybrid Network

Nowadays, Content Delivery Network (CDN) is widely used for its convenience in providing services. However, the increasing demand for bandwidth puts tremendous pressure on CDN. Inspired by the great potential of periodic broadcasting to save bandwidth, we suggest an Efficient and Adaptive Content Delivery System (EACDS) to decrease traffic and shorten video content delivery delays. Specifically, we propose the Peak cutting and Valley filling for VBR (PVV) and the Exhaustive Periodic Broadcasting algorithm (EPB) to process videos and arrange slices with low bandwidth and delay. Furthermore, we introduce an enhanced version of EPB that supports Fast-Forwarding, namely FFB. To effectively deal with the constantly changing Internet, we also demonstrate an adaptive decision model that switches distribution schemes according to the online user scale. Extensive experiments show that the EACDS is excellent in many aspects. The PVV and decision model can save up to 57% of bandwidth and 54.7% of traffic respectively. Compared with some existing schemes, EPB allows the most negligible delay with the same bandwidth, and FFB supports fast-forwarding in periodic broadcasting.