Abstract

Simultaneous access to multiple interfaces (e.g., WiFi and cellular networks) can significantly improve the users’ quality of experience (QoE) in video streaming. However, some interfaces could be more expensive to use and less energy efficient. Therefore, in this paper, we propose a preference-aware multipath video streaming algorithm over HTTP using multipath TCP (MPTCP). First, we formulate the quality decisions of the video chunks and the chunk’s download policy subject to the chunk’s deadlines, the available bandwidth of the different paths, and the link preferences as a non-convex optimization problem. The objective is to optimize a novel QoE metric that maintains a tradeoff between maximizing the quality of every video’s chunk and ensuring quality fairness among all chunks for the minimum re-buffering (stall) duration, and without violating the link preference constraint. Second, we develop a polynomial time complexity algorithm to solve the proposed optimization problem, and provide guarantees for the proposed algorithm. We further propose a sliding window based online algorithm where several challenges including short bandwidth prediction with prediction errors are addressed. Extensive emulated experiments with real bandwidth traces of public datasets reveal the robustness of our scheme and demonstrate its significant performance improvement compared to the state-of-the-art multi-path streaming algorithms.