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A novel big data architecture in support of ADS-B data analytic

机译：支持ADS-B数据分析的新型大数据架构

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The first building block of the Federal Aviation Administration's (FAA) Next Generation Air Transportation System (NextGen) initiative to modernize the US national airspace system (NAS) was the implementation of the Automatic Dependent Surveillance-Broadcast (ADS-B) ground infrastructure. A primary aspect of the ADS-B program design is the terrestrial radio station infrastructure. It determined the terrestrial radio stations layout throughout the US and was optimized to meet system performance, safety and security in the NAS. In March 2014, the FAA completed the nationwide infrastructure upgrade, enabling air traffic controllers to track aircraft with greater accuracy and reliability, while giving pilots more information in the cockpit. More than 650 ADS-B radios communicate with equipped aircraft, supporting the new satellite-based surveillance system. Currently, the ADS-B system ingests processes and stores large data sets, while operating at ten percent capacity. As aircraft avionics equipage increases, the volume of data and storage needs will increase beyond our existing system's capacity and processing capability. A new, Hadoop-based architecture was tested to ingest and analyze billions of CAT033 reports in minutes. This paper presents the “Big Data” approach that was adopted to support fast analytics of large ADS-B data volume.
机译：联邦航空管理局（FAA）下一代航空运输系统（NEXTGEN）倡议将美国国家空域系统（NAS）现代化的第一代楼层是实施自动依赖监视广播（ADS-B）地基基础设施的实施。 ADS-B节目设计的主要方面是地面无线电站基础设施。它确定了整个美国的地面无线电台布局，并经过优化，以满足NAS中的系统性能，安全性和安全性。 2014年3月，美国联邦航空局完成了全国范围的基础设施升级，使空中交通管制员能够以更高的准确性和可靠性跟踪飞机，同时在驾驶舱内提供更多信息。超过650个ADS-B收音机与配备飞机沟通，支持新的基于卫星的监控系统。目前，ADS-B系统摄取流程并存储大数据集，同时以10％的容量运行。随着飞机航空石装备的增加，数据和存储需求的数量将超出我们现有的系统容量和处理能力。在几分钟内测试了一个新的Hadoop的架构，以在几分钟内摄取和分析数十亿个Cat033报告。本文介绍了支持大型ADS-B数据量快速分析的“大数据”方法。

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