School of Informatics, Xiamen University, Xiamen 361005, China.
Sensors (Basel). 2020 Nov 19;20(22):6625. doi: 10.3390/s20226625.
As a key technology of intelligent transportation systems (ITS), vehicular ad hoc networks (VANETs) have been promising to provide safety and infotainment for drivers and passengers. To support different applications about traffic safety, traffic efficiency, autonomous driving and entertainment, it is important to investigate how to effectively deliver content in VANETs. Since it takes resources such as bandwidth and power for base stations (BSs) or roadside units (RSUs) to deliver content, the optimal pricing strategy for BSs and the optimal caching incentive scheme for RSUs need to be studied. In this paper, a framework of content delivery is proposed first, where each moving vehicle can obtain small-volume content files from either the nearest BS or the nearest RSU according to the competition among them. Then, the profit models for both BSs and RSUs are established based on stochastic geometry and point processes theory. Next, a caching incentive scheme for RSUs based on Stackelberg game is proposed, where both competition sides (i.e., BSs and RSUs) can maximize their own profits. Besides, a backward introduction method is introduced to solve the Stackelberg equilibrium. Finally, the simulation results demonstrate that BSs can obtain their own optimal pricing strategy for maximizing the profit as well as RSUs can obtain the optimal caching scheme with the maximum profit during the content delivery.
作为智能交通系统（ITS）的关键技术，车对车自组织网络（VANETs）有望为驾驶员和乘客提供安全和信息娱乐服务。为了支持与交通安全、交通效率、自动驾驶和娱乐相关的各种应用，研究如何在 VANETs 中有效地传递内容非常重要。由于基站（BSs）或路侧单元（RSUs）传递内容需要消耗带宽和功率等资源，因此需要研究 BSs 的最优定价策略和 RSUs 的最优缓存激励方案。本文首先提出了一种内容传递框架，其中每辆移动车辆可以根据它们之间的竞争，从最近的 BS 或最近的 RSU 中获取小体积的内容文件。然后，基于随机几何和点过程理论建立了 BSs 和 RSUs 的利润模型。接下来，提出了一种基于 Stackelberg 博弈的 RSUs 缓存激励方案，其中竞争双方（即 BSs 和 RSUs）都可以最大化自己的利润。此外，还引入了反向引入方法来求解 Stackelberg 均衡。最后，仿真结果表明，BSs 可以获得最优的定价策略来最大化利润，RSUs 可以在内容传递过程中获得最大利润的最优缓存方案。
