Fog-Based Transcoding for Crowdsourced Video Livecast

Recent years have witnessed the booming popularity of CLS platforms, through which numerous amateur broadcasters live stream their video contents to viewers around the world. The heterogeneous qualities and formats of the source streams, however, require massive computational resources to transcode them into multiple industrial standard quality versions to serve viewers with distinct configurations, and the delays to the viewers of different locations should be well synchronized to support community interactions. This article attempts to address these challenges and to explore the opportunities with new generation computation paradigms, in particular, fog computing. We present a novel fog-based transcoding framework for CLS platforms to offload the transcoding workload to the network edge (i.e., the massive number of viewers). We evaluate our design through our PlanetLab-based experiment and real-world viewer transcoding experiment.