空管时空数据分布式存储与快速查询  

Distributed Storage and Fast Query of Air Traffic Control Spatiotemporal Data

作　　者：王小乐 陈曦 田云钢 梁永胜 葛昊 WANG Xiaole;CHEN Xi;TIAN Yungang;LIANG Yongsheng;GE Hao(State Key Laboratory of Air Traffic Management System,Nanjing 210023,China)

机构地区：[1]空中交通管理系统全国重点实验室,南京210023

出　　处：《指挥信息系统与技术》2024年第5期53-59,共7页Command Information System and Technology

基　　金：国家重点研发计划(2022YFB2602404);国家自然科学基金民航联合基金(U2033215)资助项目。

摘　　要：针对空管监视等海量时空数据因缺乏有效的分布式存储模型,而无法有效支持快速检索查询的问题,首先,引入空间编码S2,建立空管监视分布式存储模型(PS2⁃HBase);然后,优化了时空多边形查询和K近邻(KNN)查询算法策略,搭建了空管时空数据分布式存储和查询系统原型;最后,在真实数据集中进行了试验,并与传统ST⁃Hash方法进行了对比。试验结果表明,该方法在2种查询情况下要优于ST⁃Hash策略。Aiming at the massive spatiotemporal data of air traffic control monitoring lack of effective distributed storage models,and cannot effectively support fast retrieval and queries.Firstly,spatial en⁃coding S2 is imported,and a distributed storage model of air traffic control monitoring(PS2-HBase)is established.Then,the spatiotemporal polygonal query and k-nearest neighbor(KNN)query algo⁃rithm strategies are optimized,a prototype of a distributed storage and query system for air traffic con⁃trol spatiotemporal data is built.Finally,the experiments are conducted on real datasets.Compared with the traditional ST-Hash method,the results show that the method is tested to be superior to the ST-Hash strategy in two query scenarios.

关 键 词：时空数据 分布式存储模型 时空范围查询 KNN查询 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]