Distributed Process Control Redundancy Without Duplicate Backups
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Solution Overview
Problem
Conventional process control systems require exact duplicate backup components, leading to increased costs and complexity due to the one-to-one redundancy relationship, which limits adaptability and efficiency in managing changing system demands.
Innovation Solution
A distributed computing environment where compute nodes with varying hardware and operating systems collaborate to provide redundancy, using allocation algorithms to distribute data and applications, allowing for immediate takeover by alternate nodes and reducing the need for reconfiguration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If exact duplicate backup components are used in conventional process control systems, then reliability is improved through redundancy, but device complexity and cost increase due to one-to-one redundancy relationships
Solution Approach 1:
The patent implements a many-to-one redundancy model where a single backup compute node can assume the role of multiple primary compute nodes. The backup node maintains application images and execution environments for multiple applications, allowing it to take over for any failed primary node. This universal backup approach eliminates the need for dedicated backup nodes for each primary node, reducing system complexity while maintaining reliability.
Solution Approach 2:
The patent combines multiple backup functions into a single backup compute node. Instead of having separate backup nodes for each primary node, the system merges the backup capabilities into one shared resource that can serve multiple primaries. This consolidation reduces the total number of components needed and simplifies the redundancy architecture.
2Reliability
If exact duplicate backup components are used in conventional process control systems, then reliability is improved through redundancy, but cost increases due to additional hardware requirements
Solution Approach 1:
The backup compute node is designed to universally support multiple primary compute nodes by maintaining application images and execution environments for various applications. This multi-functional capability allows a single backup node to replace what would traditionally require multiple dedicated backup nodes, reducing hardware quantity while preserving reliability.
Solution Approach 2:
The system uses virtualization to create virtual copies of compute node functionality within the backup node. Instead of requiring physical duplicate hardware for each backup relationship, the backup node contains virtualized environments that can be instantiated as needed to match any failed primary node, reducing hardware requirements while maintaining functional equivalence.
3Reliability
If conventional process control systems use one-to-one redundancy, then reliability is maintained, but adaptability decreases when system demands change
Solution Approach 1:
The redundancy system is made dynamic through the use of virtualization and software-based configuration. The backup compute node can dynamically assume different roles and configurations based on which primary node fails. Additionally, the system can dynamically allocate resources and reconfigure the distributed computing environment without requiring physical reconfiguration, enabling adaptability while maintaining reliability.
Solution Approach 2:
The system allows parameter changes in the redundancy configuration through software rather than hardware modifications. The backup node's operational parameters (which application it backs up, its communication interfaces, its processing allocation) can be changed dynamically through software configuration, enabling the system to adapt to changing demands while maintaining the reliability guarantee of having a backup ready.
4Productivity
If additional primary and backup components are added to increase process control system resources, then system capacity is improved, but device complexity and cost increase
Solution Approach 1:
When additional resources are needed to increase system capacity, the patent allows the new compute node to join the distributed environment and immediately participate in both primary and backup roles. The universal redundancy model means the new node can back up multiple existing primaries and be backed up by the existing backup infrastructure, increasing capacity without proportionally increasing redundancy complexity.
Solution Approach 2:
The system performs preliminary configuration of the backup compute node with multiple application images and execution environments pre-loaded. This preliminary action enables the backup node to immediately assume any primary role without requiring time-consuming reconfiguration when a failure occurs, thus increasing system capacity and responsiveness while keeping redundancy management simple.
5Adaptability or versatility
If conventional process control systems are reconfigured to meet changing demands, then system adaptability is improved, but time and cost increase due to laborious rewiring
Solution Approach 1:
The patent replaces the mechanical rewiring process with software-based reconfiguration. In the distributed computing environment, changing which nodes serve as primary or backup, or changing application assignments, is accomplished through software configuration and virtualization management rather than physical rewiring of hardware connections. This substitution dramatically reduces reconfiguration time and enables rapid adaptation to changing system demands.
Data Source
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AI summary
High availability and data migration in a distributed process control computing environment. Allocation algorithms distribute data and applications among available compute nodes (130), such as controllers in a process control system (100). In the process control system (100), an input/output device, such as a fieldbus module (120), can be used by any controller. Databases (114, 116) store critical execution information for immediate takeover by a backup compute element. The compute nodes (130) are configured to execute algorithms for mitigating dead time in the distributed computing environment.