Distributed Industrial Controller Resource Allocation
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Solution Overview
Problem
Industrial controller systems face challenges in efficient resource distribution and coordination across multiple processors, leading to manual and inefficient deployment, testing, and configuration processes, especially in distributed manufacturing environments where some controllers operate at peak capacity while others are lightly loaded.
Innovation Solution
A flexible application distribution framework that includes a query component to determine system resources, a distribution component to automate resource deployment and configuration, and an analysis component to support decision-making, utilizing artificial intelligence techniques and XML schema for efficient data processing and protocol management across networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual deployment and configuration processes are used for distributed controllers, then flexibility in deployment is maintained, but productivity and efficiency deteriorate due to time-consuming manual intervention
Solution Approach 1:
The system enables automated self-service deployment where the distribution component autonomously queries controller resources, analyzes system state, and distributes applications without manual intervention. The controller system serves itself by automatically detecting available resources and allocating workloads based on current system conditions, eliminating the need for manual deployment while maintaining adaptability.
Solution Approach 2:
The deployment process transitions from static manual configuration to dynamic automated distribution. The system continuously monitors controller resource availability and dynamically adjusts application distribution in real-time based on changing system conditions, allowing both efficiency and flexibility to coexist through adaptive resource allocation.
2Power
If applications are distributed across multiple controllers, then system capacity is improved, but coordination and resource management complexity increases
Solution Approach 1:
The distribution component acts as an intermediary between multiple controllers, centralizing the coordination function. It queries resource availability across all controllers, makes centralized deployment decisions, and manages application distribution, thereby simplifying coordination complexity while enabling scalable system capacity across distributed controllers.
Solution Approach 2:
The distribution component performs multiple functions including resource querying, system analysis, application distribution, and configuration management through a single unified mechanism. This multi-functional approach consolidates coordination tasks and reduces overall system complexity while maintaining the ability to manage distributed processing across multiple controllers.
3Reliability
If controllers operate independently with isolated integration processes, then individual controller reliability is maintained, but overall system coordination and performance balancing deteriorate
Solution Approach 1:
The system implements feedback mechanisms where the distribution component continuously queries controller resource status and monitors system state. Based on this feedback, it dynamically adjusts application distribution to balance workloads across controllers, ensuring both individual controller reliability and optimal overall system resource utilization through continuous monitoring and adaptive redistribution.
Solution Approach 2:
The system performs preliminary resource assessment by querying controller availability before deploying applications. This preliminary action allows the distribution component to proactively allocate workloads to appropriate controllers based on predicted resource availability, preventing overload conditions and maintaining controller stability while optimizing overall system productivity through advance planning.
Data Source
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AI summary
The present invention relates to a system and methodology facilitating flexible resource distribution in an industrial control environment. A query component is provided to determine one or more system resources from a networked industrial controller system, wherein the resources can include listings of applications, configurations, variable settings, and performance capabilities associated with a controller. Upon receiving available resource listings from various control devices, a distribution component can update the devices based in part on the resource listings and according to various criteria. A configuration component can be utilized in the controller system to provide network updates of controller parameters and to facilitate automated protocol selections when interacting with out-of-network devices. An analysis component can interact with the query, distribution, and configuration components to support higher-level decision-making in the resource distribution and allocation process.