PROJECT TITLE :
Enabling Adaptive Cloud Gaming in an Open-Source Cloud Gaming Platform
We have a tendency to study the matter of optimally adapting ongoing cloud gaming sessions to maximise the gamer expertise in dynamic environments. The thought of problem is kind of difficult because: 1) gamer experience is subjective and exhausting to quantify; a pair of) the existing open-source cloud gaming platform does not support dynamic reconfigurations of video codecs; and three) the resource allocation among concurrent gamers leaves an enormous room to optimize. We rigorously address these three challenges by: one) conducting a crowdsourced user study over the live Internet for an empirical gaming experience model; 2) enhancing the cloud gaming platform to support frame rate and bitrate adaptation on-the-fly; and 3) proposing optimal nevertheless efficient algorithms to maximize the general gaming expertise or guarantee the fairness among gamers. We tend to conduct in depth trace-driven simulations to demonstrate the deserves of our algorithms and implementation. Our simulation results show that the proposed efficient algorithms: 1) outperform the baseline algorithms by up to forty six% and thirty%; 2) run quick and scale to large (≤8000 gamers) issues; and three) achieve the user-specified optimization criteria, such as maximizing average gamer experience or maximizing the minimum gamer experience. The ensuing cloud gaming platform will be leveraged by many researchers, developers, and gamers.
Did you like this research project?
To get this research project Guidelines, Training and Code... Click Here