Edge Node Architecture for Low-Latency Industrial Cloud Collaboration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional cloud computing systems fail to meet the real-time operability and fine-grained production capabilities required by manufacturing enterprises, with issues including high latency, inefficient communication, and insufficient data privacy and security, particularly in industrial production environments.
Innovation Solution
A node-type edge computing system with modules for service governance, CI/CD, and security, utilizing microservices, CI/CD, observation, and security modules, along with edge node management components supporting edge-edge and edge-central cloud communication, and collaborative AI frameworks, enabling localized data processing and secure, efficient operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If centralized cloud computing is used for resource management and control, then unified management and scheduling can be achieved, but real-time operability and response latency are insufficient
Solution Approach 1:
The patent divides the centralized cloud computing system into distributed edge computing nodes that are segmented and deployed closer to production equipment. Each edge node independently handles local real-time computing tasks, while the central cloud manages non-time-critical operations. This segmentation enables simultaneous achievement of unified management (through central coordination) and real-time responsiveness (through local edge processing).
Solution Approach 2:
The patent introduces a spatial dimension by deploying edge computing nodes at multiple locations between the central cloud and production equipment. This creates a multi-layered architecture (central cloud → edge nodes → equipment) that adds geographical distribution as a new dimension, allowing data to be processed either centrally or locally depending on latency requirements.
2Reliability
If data is processed and transmitted to centralized cloud, then comprehensive analysis can be performed, but data privacy and security risks increase
Solution Approach 1:
The patent extracts sensitive data processing capabilities from the centralized cloud and places them at the edge nodes. Edge nodes perform local data processing and filtering, extracting only essential information for transmission to the cloud. This extraction approach maintains data privacy by keeping sensitive data local while still enabling comprehensive analysis through selective data transmission to the central cloud.
Solution Approach 2:
The patent implements different data processing qualities at different locations: edge nodes provide high-security local processing for sensitive data, while the central cloud provides comprehensive analytical processing for aggregated data. This local quality differentiation allows simultaneous achievement of data privacy protection and comprehensive analysis capability.
3Productivity
If industrial management software is used for automation, then production control can be achieved, but functional overlap and communication inefficiency occur
Solution Approach 1:
The patent introduces edge computing nodes as intermediary components between industrial management software and production equipment. These edge nodes serve as mediators that handle real-time control communications locally, reducing the communication burden on industrial management software and eliminating functional overlap by providing a dedicated real-time processing layer.
Data Source
Figure 1
Figure 2
AI summary
Provided in the present invention is a node-type edge computing system. The system comprises a micro-service module, a CI/CD module, an application management module, an observation module and a security module. The node-type edge computing module in the present invention has the characteristics of having a low network delay, supporting mass data access, having an elastic infrastructure, etc. Moreover, in addition to reducing the transmission delay, the advantages brought about by shortening a spatial distance further comprise the delay of various PLCs, gateways, routing-transfer, and network device processing in a complex network is also reduced. In addition, since the probability of network link contention is greatly reduced, the overall delay can be significantly reduced. By means of the node-type edge computing module, a distributed capability is added to a traditional cloud center, some service logic is deployed on an edge side, and related data processing is completed, such that the pressure of transmitting data back to a center cloud can be greatly relieved. The node-type edge computing module can also provide an elastic virtualization capability, such as calculation, networking and storage, based on an edge location, and can truly realize "cloud-edge collaboration".