| 摘要: |
| 大数据处理技术按照时效性可分为批处理与流处理两种模式。大量航天器工程测量数据经过测控设备的解码、译码等处理后形成原始数据发往测控中心，带有时间戳的这些原始数据、过程数据、处理结果数据及软件状态信息组成了时序大数据。通过对航天测控中心智能化决策模型的研究，设计了一种基于流式计算技术在航天测控中心系统的应用方法，指出了当前消息队列系统的瓶颈，并提出采用Kafka的消息通信机制来解决任务数量受限的问题。 |
| 关键词: 航天测控中心 实时系统 流式计算 时序大数据 |
| DOI：10.20079/j.issn.1001-893x.211212003 |
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| 基金项目:装备军内科研项目（TJ20203C010083） |
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| Application of time series big data based on stream computing in space TT&C center system |
| FU Yedan,ZHANG Fangyuan,DANG Qi,SUN Hongmei |
| (1.College of Information System and Management,National University of Defense Technology,Changsha 410073，China;2.State Key Laboratory of Astronautic Dynamics,Xi’an 710043,China) |
| Abstract: |
| According to timeliness,big data processing technology can be divided into batch processing and stream processing.A large number of spacecraft engineering survey data is decoded and decoded by the TT&C equipment to form the original data and be sent to the TT&C center.These original data,process data,processing result data and software status information with time stamp constitute the time series big data.Through the research of intelligent decision-making model of space TT&C center,an application method based on flow computing technology in space TT&C center system is designed.The bottleneck of current message queue system is pointed out,and the message communication mechanism of Kafka is proposed to solve the problem of limited number of tasks. |
| Key words: space TT&C center real-time system flow calculation time series big data |
《电讯技术》编辑部 