论文标题

Neural Myerson拍卖,用于真实和节能的自动空中数据传递

Neural Myerson Auction for Truthful and Energy-Efficient Autonomous Aerial Data Delivery

论文作者

Lee, Haemin, Kwon, Sean, Jung, Soyi, Kim, Joongheon

论文摘要

成功部署无人机为监视系统提供了理想的解决方案。使用无人机进行监视可以提供对人类或陆地车辆可能难以或无法触及的区域的访问,从而收集了特定目标的图像或视频记录。因此,我们引入了数据输送无人机,以在严酷的通信条件下传输收集的监视数据。本文提出,在监视系统中,在限制电池限制和长期飞行约束的监视系统中,在空中分布式数据平台中,基于迈森拍卖的数据传递。在本文中,多个交付无人机竞争将数据传输到单个固定地点监视无人机。我们提出的基于迈尔森拍卖的算法,该算法将真实的第二价格拍卖(SPA)作为基准,是为了最大程度地利用卖方的收入,同时满足了几个理想的财产,即个人合理性和激励性兼容性,同时追求真实的业务。除了这些基于水疗中心的操作之外,基于深度学习的框架是为了改善交付性能的设计。

A successful deployment of drones provides an ideal solution for surveillance systems. Using drones for surveillance can provide access to areas that may be difficult or impossible to reach by humans or in-land vehicles gathering images or video recordings of a specific target in their coverage. Therefore, we introduces a data delivery drone to transfer collected surveillance data in harsh communication conditions. This paper proposes a Myerson auction-based asynchronous data delivery in an aerial distributed data platform in surveillance systems taking battery limitation and long flight constraints into account. In this paper, multiple delivery drones compete to offer data transfer to a single fixed-location surveillance drone. Our proposed Myerson auction-based algorithm, which uses the truthful second-price auction (SPA) as a baseline, is to maximize the seller's revenue while meeting several desirable properties, i.e., individual rationality and incentive compatibility while pursuing truthful operations. On top of these SPA-based operations, a deep learning-based framework is additionally designed for delivery performance improvements.

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