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基于分布式流式計(jì)算的蛋雞養(yǎng)殖實(shí)時(shí)監(jiān)測(cè)與預(yù)警系統(tǒng)
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“十二五”國(guó)家科技支撐計(jì)劃項(xiàng)目(2014BAD08B05)


Real-time Monitoring and Early Warning System Based on Stream Computing for Laying Hens Raise
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    摘要:

    為實(shí)現(xiàn)蛋雞養(yǎng)殖生產(chǎn)過程參數(shù)實(shí)時(shí)監(jiān)測(cè)與預(yù)警,,研發(fā)了基于分布式流式計(jì)算框架DataCanal的蛋雞養(yǎng)殖實(shí)時(shí)監(jiān)測(cè)與預(yù)警系統(tǒng)。DataCanal是面向數(shù)據(jù)流的分布式計(jì)算框架,使用控制流集中、數(shù)據(jù)流分散的模型,,以分布式文件系統(tǒng)為中間結(jié)果的存儲(chǔ),,支持異地多數(shù)據(jù)源的實(shí)時(shí)采集和處理。系統(tǒng)以DataCanal為基礎(chǔ)設(shè)施,在具有一定擴(kuò)展性的情況下,,保證實(shí)時(shí)性。系統(tǒng)采用Brower/Server模式,,用戶通過瀏覽器即可訪問,,提升了信息共享的便捷性。系統(tǒng)實(shí)現(xiàn)了規(guī)?;半u生產(chǎn)過程實(shí)時(shí)數(shù)據(jù)采集與展示,、生產(chǎn)信息管理、實(shí)時(shí)預(yù)警,、決策分析和系統(tǒng)管理功能,,對(duì)蛋雞養(yǎng)殖全生命周期進(jìn)行了全方位的管理。運(yùn)行效果表明,,該系統(tǒng)可以解決規(guī)?;半u生產(chǎn)過程中產(chǎn)生海量數(shù)據(jù)信息化和實(shí)時(shí)處理問題,在部署8臺(tái)機(jī)器的情況下,,DataCanal集群的處理能力峰值達(dá)到160MB/s,,延遲在分鐘級(jí)別,在線上實(shí)驗(yàn)環(huán)境中,,DataCanal集群每天處理約25GB的數(shù)據(jù),而且系統(tǒng)后期維護(hù)和升級(jí)都極為便利,。

    Abstract:

    With the rapid development of computer technology, its possible to process multitype and mass data realtimely. In order to achieve realtime monitoring and early warning in laying hen raise, a system based on a distributed streaming computing framework “DataCanal” was developed. DataCanal is a data flow oriented distributed computing framework with the control flow and data flow dispersion model, which using the distributed file system as the storage of intermediate result, supporting realtime acquisition and processing multiple remote data sources. DataCanal is the basic facility of the system, which ensures the extend and realtime processing of system. The system was developed in Browser/Server mode. The users can access the system through the browser, which improves the convenience of informatization sharing. The system realizes realtime data acquisition and display, production information management, early warning, decision analysis, and system management functions. The result shows that the system solves the problem of information and realtime processing of mass data in laying hens raise. In the case of eight machines, the highest throughput of DataCanal cluster reaches 160MB/s, and the delay is at the minute level. In the online experiment, the DataCanal cluster processeed about 25GB of data every day. The maintenance and upgrade of system are convenient. Further research will be done on the mobile client.

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陳紅茜,滕光輝,邱小彬,孟超英,曹晏飛,汪成.基于分布式流式計(jì)算的蛋雞養(yǎng)殖實(shí)時(shí)監(jiān)測(cè)與預(yù)警系統(tǒng)[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2016,47(1):252-259. Chen Hongqian, Teng Guanghui, Qiu Xiaobin, Meng Chaoying, Cao Yanfei, Wang Cheng. Real-time Monitoring and Early Warning System Based on Stream Computing for Laying Hens Raise[J]. Transactions of the Chinese Society for Agricultural Machinery,2016,47(1):252-259.

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  • 收稿日期:2015-07-13
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  • 在線發(fā)布日期: 2016-01-10
  • 出版日期: 2016-01-10
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