基于雾架构的物联网无人机群搜索传感器数据分析方案

V. Dovgal
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摘要

与物联网(IoT)相关设备的广泛引入,使得可穿戴设备和应用的功能范围以及物联网应用处理的数据量都有可能显著扩展。目前,已经可以谈论通过物联网设备大规模引入处理大数据的方法。随着连接到互联网的设备数量的不断增加,在云中实时、低延迟地进行高速数据处理,这比将信息存储在有限的存储空间或使用小型设备的弱计算资源更可取。雾计算似乎有助于云技术,并为网络边缘的最终用户提供灵活的资源和服务,似乎是有效数据处理的一个有前途的解决方案。然而,使用物联网设备和相关应用的解决方案数量的增长,例如一群无人驾驶飞行器(uav)的飞行,已经产生了对可扩展,具有成本效益的平台的需求,这些平台可以提供分布式数据分析,优化资源分配并最小化响应时间。本文提出了一种基于雾计算的方法来解决执行搜索任务或观察空间中无人机群的重要任务之一。
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A Scheme of Data Analysis by Sensors of a Swarm of Drones Performing a Search Mission Based on a Fog Architecture Using the Internet of Things
The widespread introduction of devices related to the Internet of Things (IoT) makes it possible to significantly expand both the scope of functions of wearable devices and applications, as well as the amount of data processed by IoT applications. Currently, it is already possible to talk about the mass introduction of methods for processing big data by IoT devices. The increasing growth in the number of devices connected to the Internet causes problems of high-speed data processing in the cloud in real time with low latency, which is preferable to storing information in limited storage or using weak computing resources of small devices. Fog computing, which appeared to help cloud technologies and provide flexible resources and services to end users at the edge of the network, seemed to be a promising solution for efficient data processing. However, the growth in the number of solutions using IoT devices and related applications, such as the flight of a swarm of unmanned aerial vehicles (U A V s), has created a need for scalable, cost-effective platforms that can provide distributed data analysis, optimizing resource allocation and minimizing response time. The article presents a way to solve one of the important tasks of carrying out search missions or observing a swarm of unmanned aerial vehicles in space, based on foggy calculations.
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