TaxiCast: Efficient Broadcasting of Multimedia Advertisements in Vehicular Ad-hoc Networks

Traditional vision based vehicular advertising methods can only support planar advertisements. If there are obstacles blocking the line-of-sight between the advertiser and customers, the efficiency drops quickly. With the proliferation of vehicular ad-hoc networks (VANETs), advertisements can be disseminated through wireless means. However, the utility of advertisements still decay over time so that the advertiser will require fast delivery to achieve higher rewards. In this paper, we consider a taxi based multimedia advertisements broadcasting scenario where the taxis act as the advertising sources. To solve the contradiction between limited communication capacity and big data size, we propose TaxiCast which can achieve very good performance. It first applies signal strength based coding and decoding to obtain the demandings of the surrounding vehicles. Then it solves the advertisements selection process as a knapsack problem. We also consider the reward decay of advertisements and conflicts between the taxis. We conduct simulations in both fixed reward case and decayed reward case. The result shows that our scheme achieves better performance than the existing strategies.