MOMD: A multi-object multi-dimensional auction for crowdsourced mobile video streaming
Crowdsourced mobile video streaming enables nearby mobile video users to aggregate their network resources to improve the video streaming performance. However, users are often selfish and may not be willing to cooperate without proper incentives. Designing an incentive mechanism for such a scenario is challenging due to the users' asynchronous downloading behaviors as well as their private valuations for multi-bitrate encoded videos. In this work, we propose a multi-object multi-dimensional auction-based incentive framework, through which users can download multiple video segments with different bitrates for multiple nearby users (and themselves). Based on this incentive framework, we propose a Vickrey-score auction, which is the first multi-object multi-dimensional auction that achieves both truthfulness and efficiency. Simulations with real traces show that crowdsourced mobile streaming outperforms noncooperative streaming by 48.6% (on average) in terms of social welfare. We further implement our proposed auction mechanism in a demostration system, and show that the crowdsourced framework together with the auction mechanism can substantially increase mobile user's welfare and video service stability.