Software-defined data gateway

Abstract

The invention provides a software-defined data gateway. The software-defined data gateway comprises an equipment layer, a gateway layer and an application layer, wherein all physical devices form a device layer, the data gateway body comprises a management node and a gateway node, the management node is deployed in an application layer, and the gateway node is deployed in a gateway layer; the gateway layer further comprises a sensing node; the physical equipment of the equipment layer reports the data to the sensing node and receives a control instruction issued by the sensing node; the sensing node uploads the data to the gateway node, and transmits a data analysis result to the physical equipment in a downlink manner; the gateway node performs high-speed caching and persistent storage onthe acquired data according to application requirements, and forwards the data to other gateway nodes needing to use the data; the management node detects all gateway nodes, monitors load conditionsand health states of the gateway nodes, and controls starting, stopping and load balancing of the gateway nodes; and data synchronization is performed among the management nodes. According to the software-defined data gateway, industrial Internet-of-things data acquisition, storage and forwarding are realized in a software definition mode.

Description

technical field [0001] The invention relates to the technical field of data middleware in the field of industrial physical network, in particular to a software-defined data gateway. Background technique [0002] The Industrial Internet of Things developed from the traditional cyber-physical system. Driven by the demand for big data and artificial intelligence technology, the traditional working method of sending control information from the information system to the physical system is changed, and the information is realized through sensing technology. The system collects the industrial big data of the physical system as the main body, and realizes the data-driven application based on this. Currently, for such scenarios, different data collection methods usually need to be designed for different devices. Such traditional methods cannot hide the differences in communication protocols of different devices; the collected data cannot be automatically cached or stored persistent...

AI Technical Summary

Problems solved by technology

Such traditional methods cannot hide the differences in communication protocols of different devices; the collected data cannot be automatically cached or stored persistently to meet the needs of real-time control of devices and analysis of big data applications; Unified forwarding mechanism causes great inconvenience to the use of data

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