金属矿山 ›› 2013, Vol. 42 ›› Issue (12): 90-93.
• 机电与自动化 • 上一篇 下一篇
高广飞,姚军
出版日期:
发布日期:
Gao Guangfei,Yao Jun
Online:
Published:
摘要: 针对矿井指纹匹配定位算法离线数据库大的特点,为了更加高效地处理离线数据库,获得更为精确的井下人员定位服务,提出了一种基于云计算服务模式,利用Hadoop技术架构在大数据处理上的优势,将定位匹配过程分散到分布式集群的各个节点上进行并行处理,设计出矿井人员定位方案,并论证了此方案的可靠性和高效性。
关键词: 云计算平台, 离线数据, 指纹匹配定位, Hadoop, 分布式
Abstract: According to the feature of a large offline database based on mine fingerprint matching location algorithm,in order to more efficiently handle the offline database to obtain more accurate underground personnel positioning services,a cloud-based service model was proposed.With the use of the advantage of Hadoop technology architecture in the large data processing,the match positioning process was decentralized to the various nodes of a distributed cluster to parallel processing.By this method,the program of mine personnel positioning was designed and the reliability and efficiency of this program was demonstrated.
Key words: Cloud computing platform, Off-line data, Fingerprint-based localization, Hadoop, Distributed
高广飞, 姚军. 基于Hadoop云平台的矿井指纹定位算法研究[J]. 金属矿山, 2013, 42(12): 90-93.
GAO Guang-Fei, YAO Jun. Study of Underground Mines Fingerprint-based Localization Algorithms based on Hadoop Cloud Computing Platform[J]. Metal Mine, 2013, 42(12): 90-93.
/ 推荐
导出引用管理器 EndNote|Ris|BibTeX
链接本文: http://www.jsks.net.cn/CN/
http://www.jsks.net.cn/CN/Y2013/V42/I12/90