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Dynamic Pricing and Capacity Allocation of UAV-provided Mobile Services

机译:无人机提供的移动服务的动态定价和容量分配

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Due to its agility and mobility, the unmanned aerial vehicle (UAV) is a promising technology to provide high-quality mobile services (e.g., fast Internet access, edge computing, and local caching) to ground users. Major Internet Service Providers (ISPs) want to enable UAV-provided services (UPS) to improve and enrich the current mobile services for additional profit. This profit-maximization problem is not easy as the UAV has limited energy storage and needs to fly closely to serve users, requiring an optimal energy allocation for balancing both hovering time and service capacity. When hovering in a hotspot, how the UAV should dynamically price its capacity-limited UPS according to randomly arriving users with private service valuations is another question. We prove that the UAV should ask for a higher price if the leftover hovering time is longer or its service capacity is smaller, and its expected profit approaches to that under complete user information if the hovering time is sufficiently large. As the hotspot's user occurrence rate increases, a shorter hovering time or a larger service capacity should be allocated. Finally, when the UAV faces multiple hotspot candidates with different user occurrence rates and flying distances, we prove that it is optimal to deploy the UAV to serve a single hotspot. With multiple UAVs, however, this result can be reversed with UAVs' forking deployment to different hotspots.
机译:由于其敏捷性和移动性,无人机是一种有前途的技术,可以为地面用户提供高质量的移动服务(例如,快速的互联网访问,边缘计算和本地缓存)。主要的互联网服务提供商(ISP)希望启用无人机提供的服务(UPS)来改善和丰富当前的移动服务,以获取额外的利润。利润最大化的问题并不容易,因为无人机的能量存储有限,需要紧密飞行以为用户服务,因此需要最佳的能量分配以平衡悬停时间和服务能力。当悬停在热点上时,UAV如何根据随机到达的具有私人服务估值的用户动态为其容量受限的UPS定价。我们证明,如果剩余的悬停时间较长或服务容量较小,则无人机应要求更高的价格;如果悬停时间足够长,则其预期利润将接近完整用户信息下的预期利润。随着热点的用户出现率增加,应分配更短的悬停时间或更大的服务容量。最后,当无人机面对具有不同用户发生率和飞行距离的多个热点候选者时,我们证明了部署无人机服务单个热点是最佳选择。但是,使用多个无人机时,可以通过将无人机分叉部署到不同的热点来逆转这一结果。

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