Research And Application In Distributed Storage Of Sensor Data Base On MongoDB

With the development of Internet technology, especially the rapidly growing popularity ofmobile Internet，users produce large amounts of data in the day-to-day use. In addition, with thepopularity of GPS, sensors, automatic tracking and monitoring system, these new data source alsoproduced large amounts of data，which bring the new opportunities and challenges to the datastorage, data analysis and data processing. In the case of a large number of sensors be used, somenew problems are brought in the use of traditional relational database to store sensor data, such as:with the rapid growth of the data, the traditional database couldn’t meet needs of the data storageand management which has the high concurrency and large data volume characteristics, the sensoris usually collecting data in interval of few seconds, the data collected take with great dataredundancy and so on. Therefore, the new sensors data storage solution which has high efficiency ofdata storage becomes a research topic in the application of the Internet of Things.To meet the need of the high concurrency and large data volume of sensor data storage, the mainworks of this thesis are design and implement the services interface based on the MongoDBdatabase using MongoDB automatic segment technology. In the interface implementation,MongoDB database operation is encapsulated firstly, secondly the data compression model is addedinto the data storage processing, finally store the data in the form of virtual interface is provided tothe user.In this thesis, the cloud data management technology is described, including cloud computing,NoSQL system and NoSQL database firstly. Then, the popular NoSQL data storage is studied. Onthe basis of existing data storage technology, the requirements and characteristics of the sensor datastorage are analyzed. At the same time based on MongoDB document databases, WebServiceinterface for sensor data storage is developed to meet the needs of high concurrency, cross-platformstorage and fast query of sensor data. Finally, the Swinging Door compression algorithm which iswidely used in the real-time database is studied. According to the characteristics of huge amounts ofsensor data, the compression algorithm and secondary filtering method are used in data compressionmodule of the WebService interface. Thus higher compression ratio and removing the sensor dataredundancy are achieved.