Cloud-assisted solution for crowdsourced live streaming systems

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The advances in personal and mobile computing make it increasingly convenient for people to be connectedwith each other via various social media network services, and share images and videos over these networks. Inparticular, crowdsourced live streaming via mobile devices has become a popular application, where any usercan broadcast live videos through the network, and other users can watch these videos and interact with thecontent providers or other viewers. Some popular events in these networks could easily attract thousands oreven millions of viewers. This has posed several major challenges to the service providers of crowdsourcedlive streaming. First, crowdsourced contributors are geo-distributed. Second, the crowdsourcers are often muchmore dynamic than dedicated content providers. Third, the quality of service (QoS) of end-users is difficult tobe guaranteed due to heterogeneous user device and network conditions.In this project, we will work with our industrial partner and develop a cloud-assisted solution for crowdsourcedlive streaming system by taking full advantage of cloud computing and video coding technologies. First, wewill design a generic cost-effective framework for crowdsourced live streaming to support large scalegeo-distributed video crowdsourcers. Second, the heterogeneity of both broadcasters and the viewers are takeninto consideration to design transcoding and bit-rate adaption strategies for the system. Third, rate control andplay buffer optimization will be employed to further improve the QoS of end-users. Last, we will explore ahybrid cloud and peer-to-peer system as a possible approach for improving performance of crowdsourced livestreaming.