Application Runtime Partitioning for Cloud-Edge Control Latency
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Solution Overview
Problem
In industrial automation and production systems, processes like PID control require immediate execution but are often hindered by data communication delays and fluctuations, and existing development environments struggle with security and safety by requiring individual design and compilation of application programs for each process hierarchy in cloud computing environments.
Innovation Solution
The application development environment provides a system that classifies process contents based on requirements, generating divided program execution files for each classification, allowing for efficient development and execution in cloud computing environments by utilizing a hierarchical structure with the spinal node for immediate processes and the intelligence node for non-immediate ones, ensuring promptness, security, and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If cloud computing is used for industrial automation systems, then system integration and remote access are improved, but data communication delays and fluctuations occur affecting control processes
Solution Approach 1:
The system is segmented into multiple execution environments (cloud computing environment and edge computing environment) that can independently execute different processes. Time-critical control processes are executed in the edge computing environment closer to the devices, while non-time-critical processes run in the cloud, thereby reducing communication delays for critical operations while maintaining system integration benefits.
Solution Approach 2:
An intermediary execution mechanism is introduced that allows processes to be dynamically assigned to different execution environments based on their time-criticality requirements. This intermediary layer manages the distribution of processes between cloud and edge environments, ensuring that time-sensitive operations are handled with lower latency while maintaining overall system coordination.
2Reliability
If individual application programs are designed and compiled for each process hierarchy, then security and safety are improved, but development complexity and time increase
Solution Approach 1:
A universal application program is introduced that can execute across multiple execution environments (cloud and edge) without requiring separate compilation for each hierarchy. The system maintains security and safety by allowing the same application program to run in different environments with appropriate access controls and execution policies, thereby reducing development complexity while preserving reliability.
Solution Approach 2:
Different security and execution policies are applied locally to different execution environments based on their specific requirements. The edge computing environment receives applications with policies suitable for time-critical execution, while the cloud environment receives applications optimized for resource-intensive tasks. This local differentiation maintains security without requiring complete redesign of applications for each environment.
3Productivity
If processes are executed in cloud computing environment, then resource utilization is improved, but promptness of control processes deteriorates
Solution Approach 1:
The system segments processes based on their speed requirements and assigns them to appropriate execution environments. Time-critical control processes are segmented and executed in the edge computing environment where they can run with lower latency, while non-time-critical processes are executed in the cloud computing environment to maximize resource utilization. This segmentation resolves the contradiction by matching process characteristics with execution environment capabilities.
Solution Approach 2:
The system adds a spatial dimension to execution by distributing processes across different physical locations (cloud data centers vs. edge devices). This dimensional change allows the system to optimize for both resource utilization (cloud) and speed (edge) simultaneously by placing processes in the most appropriate location based on their requirements.
Data Source
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AI summary
An application development environment provision system that provides a development environment for application programs via a network. The network includes a first network and a second network, said first network housing at least one device and being in communication connection with said device and said second network being in communication connection with the first network. The application development environment provision system has a program development unit that: separates processing included in the application program into processing executed in the first network and processing executed in the second network, separating same on the basis of prescribed determination conditions; and generates a first program execution file executed in the first network and a second program execution file executed, in conjunction with the first program execution file, in the second network.