Application and Implementation of Private Cloud in Agriculture Sensory Data Platform

文献类型： 外文期刊

第一作者： Jiang, Shuwen

作者： Jiang, Shuwen;Chen, Tian'en;Dong, Jing;Jiang, Shuwen;Chen, Tian'en;Dong, Jing;Jiang, Shuwen;Chen, Tian'en;Dong, Jing;Jiang, Shuwen;Chen, Tian'en;Dong, Jing

作者机构：

关键词： Internet of things;Private cloud;Big data;Hadoop;HDFS

期刊名称：COMPUTER AND COMPUTING TECHNOLOGIES IN AGRICULTURE IX, CCTA 2015, PT II

ISSN： 1868-4238

年卷期： 2016 年 479 卷

页码：

收录情况： SCI

摘要： With the explosive development of the Internet of things technology in recent years, the Internet of things technology is also used more and more widely in modern agricultural production. For mass sensor data was produced by the Internet of things in agricultural production, While big data bring many benefits and unprecedented challenges to users. The Internet of things in agriculture production produces some complexity problem which are mass sensor data's Scale, sensor data's heterogeneity and mass sensor data's operation, distribution of sensor, high concurrency of data is written etc. In the presence of these problems, this paper put forward a kind solution of agricultural private cloud sensor data Platform, which is named "Sensor PrivateClouds Platform" (SPCP). The Private cloud platform including following modules, All of these are distributed sensor data caching module based on cluster of memercached and Nginx load (SensorCache); heterogeneous data adapter of sensor module (SensorAdpter), distributed computing storage module based on hadoop' HDFS (SensorStorage), efficient query module of sensor data warehouse based on the Hive (SensorStore), management module of sensor metadata (SensorManager), parallel sensor data analysis module (SensorNum) based on the map-reduce of the hadoop, cloud service of sensor data module (SensorPublish) based on webservice. The experimental results show that SPCP have had the abilities which are mass sensor data storage, cleaning of heterogeneous sensor data, real-time query and processing of mass sensor data. These abilities provides a feasible solution for the heterogeneous data storage and mass sensor data's query in the Internet of things of agriculture production.

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