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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 problemes, 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,realtime 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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With involvement and the popularization of the Internet of things and cloud computing technology in the modern information agriculture, RDBMS has been difficult to resolve perception storage and analysis of mass data in Internet of things.big data storage and computing are a hotspot and difficulty of research on agriculture cloud computing in recent years. This article is based on agricultural cloud Paas platform, rural areas and farmers services to designe and implemente a distributed storage of large-scale data of perception using the DSM and distributed file system. While providing services of vast agricultural data of perception storage and analysis through agriculture Paas platform, while implementing agricultural cloud computing. DSM is designed based on Hbase as a mass of NoSql database which provides real-time efficient reading and writing, high scalability and high availability. DSM is deploied on the distributed file system of Hadoop which is based on HDFS. While MapReduce of hadoop can provide high-speed large file analysis and processing. Experiments indicate that the DSM technology based on application of agricultural Paas can meet requirement of the perceptive big data, strong scalability and so on.