Interdependent Binding Activation Using Dependency-Graph Load Order
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Solution Overview
Problem
Existing systems for controlling industrial processes using data bindings often produce false results due to the random initiation of bindings without considering dependencies, leading to inefficiencies and unnecessary processing and network loads.
Innovation Solution
A system generates and analyzes a dependency graph before initiating binding configurations, ensuring that each binding is configured only after the results from its dependencies are ready, thereby avoiding the use of invalid data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If bindings are initiated in random order without considering dependencies, then the system can start processing immediately, but false results are produced and unnecessary processing and network loads occur
Solution Approach 1:
The system performs preliminary analysis of binding dependencies before initiating bindings. A dependency graph is constructed and analyzed to determine the correct initiation order, ensuring that bindings are started only after their dependencies are satisfied, thus preventing false results while maintaining efficient processing
Solution Approach 2:
The system uses feedback from the dependency graph analysis to dynamically control the binding initiation process. By monitoring which bindings have completed and which are still pending, the system can determine when it's appropriate to initiate subsequent bindings, ensuring data validity without unnecessary delays
2Loss of time
If bindings are initiated without waiting for dependency results, then processing can proceed in parallel, but invalid data is used as input
Solution Approach 1:
The system performs preliminary dependency analysis to identify which bindings can be initiated immediately and which must wait. This allows maximum parallelization of independent bindings while ensuring that dependent bindings are only started when their input data is guaranteed to be valid
Solution Approach 2:
The binding initiation process is segmented into multiple phases based on the dependency graph. Bindings are grouped into initiation waves where each wave contains bindings whose dependencies are satisfied, allowing parallel processing within each wave while maintaining data accuracy across waves
3Reliability
If the system waits for all dependency results before initiating bindings, then data validity is ensured, but processing efficiency decreases
Solution Approach 1:
The system performs preliminary dependency graph construction and analysis to identify the critical path and parallelizable sections. This allows the system to wait only for the minimum necessary dependencies before initiating each binding, ensuring accuracy while maximizing throughput through intelligent scheduling
Solution Approach 2:
The binding initiation schedule is dynamically adjusted based on the actual completion status of dependencies. Rather than following a rigid sequential order or initiating all bindings simultaneously, the system adapts the initiation timing of each binding based on when its dependencies are actually satisfied, optimizing both accuracy and throughput
Data Source
AI summary
A system for efficiently configuring bindings based on a dependency graph is described. The system may generate or access a graph comprising a set of nodes. Each node may represent a binding and is associated with a component property of a component hierarchy corresponding to a hierarchical structure of a data model. Each node of the graph may be connected to at least one other node with an edge representing a dependency in the hierarchical structure of the data model. The system may receive a request to generate a view associated with the set of bindings. The system may determine an order to load the set of bindings based on the graph, and may load the set of bindings based on the determined order.