Storage method and storage system for monitoring big data of Internet of Things

Abstract

The invention provides a storage system and a storage method for monitoring big data of the Internet of Things. The storage system includes a global data center, at least one regional data center, at least one terminal gateway and at least one IoT monitoring terminal, wherein the terminal gateway is used to collect data collected by at least one connected IoT monitoring terminal, and The regional data center is used to gather and receive the data of at least one connected terminal gateway and store it, and the global data center is used to determine the connected regional The corresponding data stored in the data center is transmitted to the global data center for storage. The storage system and storage method of the present invention can store a full amount of data and improve storage performance.

Description

technical field [0001] The invention relates to the field of big data of the Internet of Things, in particular to a storage method and a storage system for monitoring big data of the Internet of Things. Background technique [0002] In recent years, with the development of Internet of Things technology, monitoring equipment has generated a large amount of real-time data, and making full use of these data for data mining analysis and early warning has important practical value. The Internet of Things network has a huge number of monitoring devices, and each device needs to monitor many indicators in real time, and the total amount of monitoring data in a short period of time is also large. For example, for a power monitoring IoT network, it has tens of thousands of monitoring points, and each monitoring point can monitor thousands of indicators per second, and the total amount of data per second can reach GB level. Taking vehicle GPS information collection as an example, Alt...

AI Technical Summary

Problems solved by technology

Traditional real-time database technology or streaming data processing technology often adopts a strategy of saving part of the data when dealing with such large-scale time series data, such as saving only sampling data, only saving data of current concern, or only saving statistical data. Strategies will lead to deviations in the final statistical analysis or real-time early warning results

With the development of cloud computing and other technologies, it has gradually become a trend to fully store the raw data of IoT devices and perform full data analysis. However, the current storage mode of a single cloud data center is bound to be limited by network performance and cannot cope with high concurrency and high throughput. Demand for real-time storage of IoT monitoring data

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