In recent years, live streaming has become a popular application, which uses TCP as its primary transport protocol. Quick UDP Internet Connections (QUIC) protocol opens up new opportunities for live streaming. However, how to leverage QUIC to transmit live videos has not been studied yet. This paper first investigates the achievable quality of experience (QoE) of streaming live videos over TCP, QUIC, and their multipath extensions Multipath TCP (MPTCP) and Multipath QUIC (MPQUIC). We observe that MPQUIC achieves the best performance with bandwidth aggregation and transmission reliability. However, network fluctuations may cause heterogeneous paths, high path loss, and bandwidth degradation, resulting in significant QoE deterioration. Motivated by the above observations, we investigate the multipath packet scheduling problem in live streaming and design 4D-MAP, a multipath adaptive packet scheduling scheme over QUIC. Specifically, a linear upper confidence bound (LinUCB)-based online learning algorithm, along with four novel scheduling mechanisms, i.e., Dispatch, Duplicate, Discard, and Decompensate, is proposed to conquer the above problems. 4D-MAP has been evaluated in both controlled emulation and real-world networks to make comparison with the state-of-the-art multipath transmission schemes. Experimental results reveal that 4D-MAP outperforms others in terms of improving the QoE of live streaming.
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