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氣象大數據云平臺仿真環(huán)境容器調度性能優(yōu)化研究
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國家氣象信息中心信息網(wǎng)絡(luò )安全與“信創(chuàng )”技術(shù)研發(fā)創(chuàng )新團隊(NMIC-202011-05)攻關(guān)任務(wù)與廣東省氣象局科學(xué)技術(shù)研究項目(GRMC2022Z05, GRMC2021XQ03)項目資助


Research on Optimization of Docker Scheduling Performance for Simulation Environment of Meteorological Big Data Cloud Platform
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    摘要:

    為實(shí)現2025年氣象關(guān)鍵核心技術(shù)自主可控的目標,氣象大數據云平臺(簡(jiǎn)稱(chēng)天擎)建立了基于海光X86服務(wù)器和麒麟操作系統的仿真環(huán)境。在仿真平臺運行中發(fā)現,基于容器技術(shù)的產(chǎn)品加工與流水線(xiàn)子系統容器調度性能較差,不能滿(mǎn)足用戶(hù)融入算法的時(shí)效要求。針對此問(wèn)題,本文采用對比分析法,選取天擎仿真環(huán)境和業(yè)務(wù)環(huán)境的3種CPU芯片服務(wù)器和3種操作系統為研究對象,設計了一系列組合對比測試用例,找到了影響容器調度性能的關(guān)鍵因素—操作系統內核,并進(jìn)一步分析了操作系統內核設置對系統實(shí)時(shí)性和吞吐量的影響以及適用的業(yè)務(wù)場(chǎng)景。最后給出了麒麟操作系統內核調整方法,通過(guò)調整內核設置,容器調度性能大幅提高,滿(mǎn)足了產(chǎn)品加工系統的時(shí)效要求,為實(shí)現天擎的關(guān)鍵核心技術(shù)自主可控奠定基礎。

    Abstract:

    In order to achieve the goal of independent and controllable key core technologies for Meteo by 2025, the Meteo Big Data Cloud Platform (referred to as Tianqing) establishes a simulation environment based on Hygon X86 CPU and Kylin OS. However, in the operation of simulation platforms, it finds that the docker scheduling performance of data processing and assembly line subsystems based on Kubernetes is poor, which cannot meet the timeliness requirements of user integration algorithms. In response to this issue, this article adopts a comparative analysis method, selecting servers based on three types of CPU and three types of operating systems from the simulation environment and business environment for Tianqing as the research objects. A series of combined comparative test cases are designed. It finds that the kernel is the key factor affecting docker scheduling performance. Further analysis is conducted on the impact of operating system kernel settings on real-time and throughput, as well as the suitable business scenarios. Finally, a method for adjusting the Kylin OS kernel is provided. By adjusting the kernel settings, the docker scheduling performance significantly improves, meeting the timeliness requirements of the data processing system and laying the foundation for achieving self-supporting of the key core technology of Tianqing.

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吳鵬,韓同欣,陳士旺,聶元丁,鄭曉志.氣象大數據云平臺仿真環(huán)境容器調度性能優(yōu)化研究[J].氣象科技,2024,52(3):340~346

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  • 收稿日期:2023-06-02
  • 定稿日期:2024-01-12
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  • 在線(xiàn)發(fā)布日期: 2024-06-25
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