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Research on Partition of Marine Data with Strong Correlation

HUANG Dongmei 1,SUI Hongyun 1,HE Qi 1,ZHAO Danfeng 1,DU Yanling 1,SU Cheng 2   

  1. (1.College of Information,Shanghai Ocean University,Shanghai 201306,China; 2.East Sea Forecast Center,State Oceanic Administration,Shanghai 200136,China)
  • Received:2015-08-12 Online:2016-05-15 Published:2016-05-13

强关联海洋数据划分研究

黄冬梅1,随宏运1,贺琪1,赵丹枫1,杜艳玲1,苏诚2   

  1. (1.上海海洋大学信息学院,上海 201306; 2.国家海洋局东海预报中心,上海 200136)
  • 作者简介:黄冬梅(1964-),女,教授、博士生导师,主研方向为云存储、分布式计算;随宏运(通讯作者),硕士研究生;贺琪,副教授、博士;赵丹枫,博士;杜艳玲,博士研究生;苏诚,高级工程师。
  • 基金资助:
    国家自然科学基金资助项目(61272098);国家海洋公益性行业科研专项基金资助项目(201105034-6)。

Abstract: Marine monitoring data has the characteristics of large scale and strong correlation.How to effectively layout the data and how to improve the execution efficiency of data management and application are the keys in current marine data research.With the integration of Internet-plus and digital ocean,a marine monitoring data layout strategy in cloud environment based on the correlation of monitoring data is proposed.In view of the characteristics of marine monitoring data in digital ocean,a strong correlation matrix is established according to the correlation of monitoring tasks,monitoring points and monitoring data.This brings data with high correlation together in the matrix arrangement.It divides the data based on the correlation matrix.Consequently,the data in different group can be distributed to different data center based on the capacity.Experimental results show that the strategy reduces the running time of the algorithm and the response time of marine monitoring data access.Besides,the strategy provides an effective method to the management and layout of marine monitoring data in digital ocean.

Key words: digital marine, marine monitoring data, Internet-plus, data partition, cloud environment, strong correlation matrix

摘要: 海洋监测数据具有海量、强关联性的特点,对海洋监测数据进行合理布局,进而提高数据管理和应用的执行效率,是目前海洋数据研究领域的关键。将“互联网+”和“数字海洋”进行有机融合,提出一种强关联海洋监测数据布局策略。针对数字海洋中海洋监测数据的特点,根据监测任务、监测站位和监测数据的关联建立强关联矩阵。将矩阵中相似的元素聚集在一起,把具有较高关联度的数据划分为一类子数据集,并根据数据中心的存储容量进行布局。实验结果表明,该策略可降低算法的运行时间和用户访问海洋监测数据的响应时间,是数字海洋中海洋监测数据管理和存储的一种有效布局策略。

关键词: 数字海洋, 海洋监测数据, 互联网+, 数据划分, 云环境, 强关联矩阵

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