Parallel mass data transmitting middleware of Internet of things and working method thereof

Abstract

The present invention discloses parallel mass data transmitting middleware of Internet of things and a working method thereof. The invention includes: a data collection module, for forwarding data collected from different types of sensors to an application interaction module after analysis; the application interaction module, for achieving communication between the parallel mass data transmitting middleware of the Internet of things and an application system of the Internet of things, analyzing a control command of the application system of the Internet of things, transmitting to the data collection module, and further transmitting the analyzed sensor data to a data management module; the data management module, for performing data screening, fusion, conversion on the mass data analyzed by the application interaction module, and finally storing the calculated data into the application system of the Internet of things; and a developing regulation module, for setting out a protocol plug-in regulation, a communication channel plug-in regulation, a service field metadata plug-in regulation, etc. The present invention can meet high concurrency access and management of the large scale sensing apparatus of different application fields, various communication channels and various communication protocols.

Description

technical field [0001] The invention relates to an Internet of Things parallel massive data transmission middleware and a working method thereof. Background technique [0002] The Internet of Things has become one of the strategic commanding heights of the new round of economic and technological development in the world. The development of the Internet of Things has important practical significance for promoting economic development and social progress. With the rapid development of IoT applications, how to efficiently and real-time transmit, analyze, and manage massive and heterogeneous sensing data has become a key support for the continuous, stable, and orderly development of IoT services. [0003] There are a variety of sensors in the Internet of Things, and each type of sensor has different uses in different Internet of Things application systems. These sensors have different structures and performances, and the data structures they collect are also different. The diver...

AI Technical Summary

Problems solved by technology

[0006] The development of existing data perception and processing platforms is only aimed at specific fields and does not have good versatility, and there are currently a lot of repetitive construction, making the design and development of the platform the focus of current work, resulting in manpower , Repeated investment and waste of technical resources have seriously slowed down the development of IoT applications

[0007] (2) It is too tightly bound with business applications and lacks independence

[0008] Existing data perception and processing platforms are developed for IoT application systems, and generally adopt a tightly coupled deployment model. Their transmission protocols, instruction sets, and control methods are inseparable from the business model of the application system. The adjustment of the platform under the mode will affect the normal business processing function, and at the same time, problems in the business processing system will also cause the existing platform to fail to operate, thus affecting the normal operation of the overall business of the Internet of Things

[0009] (3) Insufficient real-time perception and processing capabilities of massive data

[0010] With the continuous advancement of the industrialization of the Internet of Things, the perception data of the Internet of Things applications has grown geometrically and has reached the level of massive data. The existing data perception and processing platforms can no longer meet the real-time processing requirements of high concurrency and large-capacity data. , becoming a bottleneck restricting the business expansion of the Internet of Things

[0011] (4) Lack of visual monitoring capabilities

[0012] Existing data perception and processing platforms still monitor the real-time operating status and communication efficiency of communication channels and sensor devices at a relatively low level, and the analysis of operating status is mainly realized through various query statistics. This method is neither intuitive nor real-time. nature, the overall communication situation is not effectively supervised

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