Analyzing streaming performance in crowdsourcing-based video service systems

Abstract

Crowdsourcing-based video service systems, e.g., Thunder Crystal, are novel content distribution platforms composed by a large number of agent devices, acting like miniservers. Most agents are normal Internet users who would like to earn rewarded cash by uploading content through their devices. Compared with CDN, the bandwidth cost is much cheaper; while compared with Peer-to-Peer(P2P), the bandwidth supply is more stable. In this work, we create a stochastic model to analyze the live and VoD streaming performance in such crowdsourcing-based video service systems. Simulation is conducted to validate the accuracy of our analytical results.