NeuroCast: adaptive multi-source P2P video streaming application for wireless networks

Abstract

Streaming consists in distributing media to large audiences over a computer network. Providing a streaming service for wireless mobile nodes presents many challenges. A peer-to-peer (P2P) solution has the big advantage of seamlessly scaling to arbitrary population sizes, as every node that receives the video, while consuming resources, can at the same time offer its own upload bandwidth to serve other nodes. In this paper we present the design and implementation of NeuroCast: an unstructured P2P application for video streaming. NeuroCast implements a robust scheduling algorithm which minimizes the scheduling delay. Moreover, given heterogeneous contents, delays and bandwidths. Thus, NeuroCast becomes suitable for wireless scenarios due to its capability to adapt to changing network conditions.