OPC UA Aggregation Server On-Demand Data Caching
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Solution Overview
Problem
In OPC UA systems, the initial startup time is significantly prolonged due to the need to aggregate hundreds or thousands of nodes, with clients often handling excessive irrelevant data, which can be time-consuming and resource-intensive, especially when only a subset of data is needed by operators.
Innovation Solution
An OPC UA aggregation server is configured to aggregate data on demand, utilizing a cache and configuration files to store and retrieve only the necessary data, reducing bandwidth and startup time by transmitting data only when requested, and implementing data reduction and redundancy mechanisms to provide a unified, pre-processed view of data from multiple servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all nodes in the remote address space are aggregated during startup, then complete data availability is achieved, but startup time is significantly prolonged
Solution Approach 1:
The system performs preliminary actions by pre-aggregating and caching node information, type information, and reference data during idle periods or previous sessions. This preliminary preparation ensures that when the system needs to access data, the aggregation process has already been partially or fully completed, eliminating the need to aggregate all nodes during startup.
Solution Approach 2:
The address space aggregation is divided into segments or parts that can be processed independently. Instead of aggregating all nodes simultaneously during startup, the system segments the aggregation process into manageable portions that can be handled at different times, with critical segments pre-processed and less critical segments aggregated on-demand.
2Reliability
If complete address space data is transmitted to clients, then data availability is ensured, but bandwidth consumption and processing load increase
Solution Approach 1:
The system extracts and transmits only the specific data portions that clients actually need, rather than transmitting the complete address space. The server identifies and extracts relevant nodes, type information, and reference data based on client requests, filtering out unnecessary data to reduce bandwidth consumption while ensuring all required data is available.
Solution Approach 2:
The system implements partial aggregation by providing exactly the amount of data needed by the client - no more, no less. This partial action approach avoids the excessive transmission of complete address space data while ensuring sufficient data availability for client operations.
3Speed
If all nodes are aggregated in memory, then fast access is achieved, but memory consumption increases
Solution Approach 1:
The address space data structure is segmented into multiple components (nodes, type information, references) that can be stored and managed separately. This segmentation allows the system to load only the necessary segments into memory based on access patterns, rather than loading the entire address space, thus reducing memory consumption while maintaining fast access to frequently used data.
Solution Approach 2:
The system implements local quality by optimizing the memory representation of address space data according to local access requirements. Frequently accessed nodes and type information are kept in memory with optimized data structures, while less frequently accessed data can be stored in cache or on disk, providing fast access where needed while minimizing overall memory consumption.
Data Source
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AI summary
The invention relates to an OPC UA aggregation server (100) for aggregating at least one OPC UA server (120) in a remote address space (121), wherein the at least one OPC UA aggregation server (100) is configured to support data reduction and/or redundancy mechanisms.