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Dynamic Pricing and Capacity Allocation of UAV-provided Mobile Services

机译:无人驾驶能力的动态定价与容量分配

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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,无人驾驶飞行器(UAV)是一个有前途的技术,提供高质量的移动服务(例如,快速互联网接入,边缘计算和本地缓存)到地面用户。主要互联网服务提供商(ISP)希望能够使UAV提供的服务(UPS)提供改进和丰富当前的移动服务以获得额外的利润。这种利润最大化问题并不容易,因为无人机的能量存储有限,需要密切运用用户,需要最佳的能量分配来平衡徘徊时间和服务能力。在热点悬停时,UAV如何根据随机到达的用户私人服务估值的用户来动态地价格限制UPS是另一个问题。如果剩余的悬停时间更长或者其服务能力较小,则无人机应该要求更高的价格,如果徘徊时间足够大,则其预期的利润方法在完整的用户信息下。随着热点的用户出现速率增加,应分配更短的悬停时间或更大的服务能力。最后,当UAV面对具有不同用户出现率和飞行距离的多个热点候选者时,我们证明它是最佳部署UAV以服务单个热点。但是,使用多个无人机,此结果可以将UAV的分叉部署与不同的热点倒转。

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