Since compressed wireless sensor network data based on Swing Door Trending ( SDT) is scattered,unified management and query are difficult to handle,meanwhile the data would be moved frequently for the goal of loading balancing. MongoDB,as a new non-relational database,is famous for flexible storing configuration and high query efficiency,which is suitable for storage and management of sensor data. By studying the MongoDB storage features and space allocation mechanism,taking advantage of the ability to cloud com-puting platform,a compressed and efficient storage scheme of sensor network data is proposed. The sensing data compressed by sensors is decompressed in the cloud using the least squares fitting,getting the complete data set on time granularity,and a common storage format applies to the time domain senor data is designed to put the data into the MongoDB,a high-performance NoSQL database. Experimental results show that the scheme recoveries compressed data better and promotes the database query efficiency,and the flexible storage mode of MongoDB plays a significant advantage in sensing data applications.%传感网络数据经旋转门压缩后是零散分布的，压缩后的数据直接在云中存储，将导致其难以统一管理和查询，集群为了负载均衡会频繁移动数据。 MongoDB数据库是一种新型的非关系数据库，其存储结构灵活，查询效率高，适合传感数据的存储和管理。通过研究MongoDB的存储特点和空间分配机制，利用云平台的计算能力，设计针对传感数据的压缩和高效存储方案。先将传感器压缩后的传感数据在云中使用最小二乘法拟合进行解压缩处理，得到时间粒度上的完整数据集，设计一种针对时域性传感数据的通用存储格式，将数据集存储到高性能的NoSQL数据库MongoDB中。实验结果表明，该方案可以更好地恢复有损压缩后的数据并提高数据的查询效率，体现了MongoDB灵活的存储模式在传感数据中应用的显著优势。
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