一种用于无人机信息处理的雾云计算分析框架
A Framework for Analyzing Fog-Cloud Computing Cooperation Applied to Information Processing of UAVs
摘要：
无人机（UAV）是一项相对较新的技术。它们的应用往往涉及复杂和看不见的问题。例如，它们可以在地面站的监督下在一个以合作为基础的环境中工作，以加快关键的决策过程。然而，在飞行器和地面站之间交换的信息量受到长距离、低带宽大小、受限的处理能力和能量约束的限制。这些缺点限制了诸如大面积检查的大规模操作。新的分布式最先进的处理架构，如雾计算，可以通过不同级别的数据采集、处理和存储来改善延迟、可扩展性和效率，以满足时间限制。根据这些修正，本研究工作提出了一个数学模型来分析分布式无人机的拓扑结构和雾云计算框架的大规模任务和搜索操作。测试成功预测了延迟和其他操作限制，允许分析雾计算相对于传统云计算架构的优势。
英文摘要：
Unmanned aerial vehicles (UAVs) are a relatively new technology. Their application can often involve complex and unseen problems. For instance, they can work in a cooperative-based environment under the supervision of a ground station to speed up critical decision-making processes. However, the amount of information exchanged among the aircraft and ground station is limited by high distances, low bandwidth size, restricted processing capability, and energy constraints. These drawbacks restrain large-scale operations such as large area inspections. New distributed state-of-the-art processing architectures, such as fog computing, can improve latency, scalability, and efficiency to meet time constraints via data acquisition, processing, and storage at different levels. Under these amendments, this research work proposes a mathematical model to analyze distribution-based UAVs topologies and a fog-cloud computing framework for large-scale mission and search operations. The tests have successfully predicted latency and other operational constraints, allowing the analysis of fog-computing advantages over traditional cloud-computing architectures.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
