大海捞针:无人机任务感知数据包转发的搜索空间限制

Mahdi Asadpour, Mario Burger, Fabian Schuiki, K. Hummel
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引用次数: 1

摘要

微型飞行器可以建立一个智能传感器物体的集合,在民用任务中合作,如搜索和救援,农田监测或监视。无线连接是将图像和其他传感器数据传输到地面的先决条件。虽然飞行器可以自行建立多跳无线网络,但飞行器的移动会导致无线信号质量的频繁变化和间歇性连接,这给端到端数据传输带来了挑战,使传统的路由方法变得不切实际。我们通过包含容忍延迟的数据包转发来解决这个问题。此外,我们使转发任务感知,即意识到未来的位置和连接机会衍生自mav的任务的航路点。由此产生的数据包转发路径选项打开了一个巨大的搜索空间。提出了一种基于$ a ^*$搜索算法的高效寻径方案。我们研究了我们的任务感知算法的性能,并将其与具有IEEE 802.11n空中链路的四轴飞行器的模拟和地理路由的延迟容忍变体进行了比较。我们的第一个结果表明,对于简单的场景,任务感知转发的好处是有限的,然而,在更复杂的场景中,任务感知转发可以缓解低效的转发并提高性能。
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Needle in a Haystack: Limiting the Search Space in Mission-aware Packet Forwarding for Drones
Micro aerial vehicles may build a collective of smart sensor objects cooperating in civilian missions such as search and rescue, farmland monitoring, or surveillance. Wireless connectivity is a prerequisite for transferring images and other sensor data to the ground. Though aerial vehicles may set up a multi-hop wireless network on their own, vehicle movement causes frequent changes of the wireless signal quality and intermittent connectivity, which poses challenges to end-to-end data delivery and renders traditional routing approaches impractical. We address this problem by including delay-tolerant packet forwarding. Further, we make forwarding mission-aware, i.e., aware of future positions and connection opportunities derived from the waypoints of the MAVs' mission. The resulting path options for packet forwarding open a vast search space. We present a solution to find a path efficiently based on the $A^*$ search algorithm. We study the performance of our mission-aware algorithm compared to a delay-tolerant variant of geographic routing in simulation and in a testbed of quadcopters with IEEE 802.11n aerial links. Our first results reveal that for simple scenarios, the benefit of mission-aware forwarding is limited, yet, in more sophisticated scenarios, mission-aware forwarding can alleviate inefficient forwarding and improve performance.
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