Delay-Constrained Utility Maximization for Video Ads Push in Mobile Opportunistic D2D Networks

It is a significant challenge for device-to-device (D2D) networks to deliver mobile videos among mobile users due to the highly nondeterministic and intermittent connectivity. In this paper, we propose to integrate the random mobility of users in mobile opportunistic D2D networks with crowdsourcing to push mobile video Ads. Incentives are key to the success of video Ads push as it heavily depends on how actively mobile users participate in it. To stimulate users to perform mobile video Ads push tasks, we model the interaction between depositories and the Ad provider as a reverse auction. More specifically, we try to maximize the utility of Ad provider by selecting a subset of depositories before a specified deadline. We first propose an online auction (OA) algorithm, which runs efficiently in polynomial time, guarantees individual rationality, profitability. However, it does not guarantee truthfulness and thus limits its practicality. We then introduce two truthful OA algorithms, i. e., TOA and TOA-MM. We carry out trace-driven simulation to verify the three OA algorithms. The simulation results corroborate that the proposed algorithms have superior performance and efficiently stimulate mobile users to make contribution to video Ads push.