摘要
建立了云计算的海量数据处理数学模型和算法,并将Hadoop分布式计算方法引入到了数据库处理系统中,实现了数据库数据的自动分区和主从节点的设置,以及数据的分布式计算功能,得到了数据的处理速度、容量和传输速率等系统性能参数;结合农业生产中联合收割机应用越来越广泛,加之农田小路比较狭窄,给农田交通运输带来了的巨大压力等问题,提出了一套能够提供定位、监控、导航、车况采集等综合服务的联合收割机远程监控系统。通过对系统的测试,证明云存储平台在联合收割机监控系统中具有良好的表现,并具有很好的扩展性,为现代化的农业收割机监控系统提供了优越的条件。
It established a mathematical model of data processing and algorithm of cloud computing, and Hadoop.And the distributed computing method was introduced into the database processing system, which realized the automatic data partition database and master-slave node set, realizes the data distributed computing function.Then, it obtained processing speed, data transmission rate and capacity the system performance parameters.Secondly, it is more and more widely used combining harvester in agricultural production.In addition, the farmland path is narrow, which brings the huge pressure to the farmland transportation and so on.It put forward a set of positioning and monitoring, navigation, vehicle acquisition and other integrated services combine remote monitoring system.Finally, through the test of the system, the cloud storage platform has good performance in the combine monitoring system, and it has a good scalability, modernization The vehicle monitoring system provides superior conditions for agricultural harvester.
出处
《农机化研究》
北大核心
2017年第12期185-189,共5页
Journal of Agricultural Mechanization Research
基金
河南省教育厅重点项目(ZJA15134)
关键词
联合收割机
远程监控
云平台
Hadoop
combine harvester
remote monitoring
Hadoop
cloud platform
