Abstract
Cloud gaming is promising yet poses big challenges to wireless communications, due to its stringent requirements for low latency and high reliability. In this paper, we propose a predictive frame transmission scheme (PFT) in cloud gaming, to predict and pre-transmit future game frames to users. The PFT scheme takes full advantage of good network states to transmit the predicted frames, which consequently reduces the frame loss rate (FLR) against the network dynamics. We firstly model a FLR minimization problem with the PFT scheme, that allocates packets to carry the predicted frames. The upper and lower bounds of FLR are derived respectively. Then, we study the system with Markovian property, and derive the optimal packet allocation policy via Markov Decision Process. We further propose a near-optimal and low-complexity policy. Finally, we extend the policy to fit the scenario without direct knowledge of the network state by exploiting the packet loss rate estimation. We set up a practical testbed to evaluate the proposed PFT scheme, showing the capability of decreasing the mean FLR from 7% to 1%.
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