Asset Hierarchy Interface Using Search-Driven Control Determination
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Solution Overview
Problem
Analyzing and searching massive quantities of machine-generated data from diverse sources poses challenges due to the complexity and volume of data types and formats, requiring efficient processing and storage solutions to facilitate real-time operational intelligence.
Innovation Solution
The implementation of an event-based data intake and query system, such as the SPLUNK® ENTERPRISE system, which uses a late-binding schema to collect, index, and search machine-generated data from various sources, enabling flexible data processing and analysis by applying extraction rules at search time, and employing techniques like parallel processing and keyword indexing to enhance query efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is collected and stored from diverse machine sources with different formats and types, then the quantity and variety of available data increases, but the complexity of processing and searching the data increases
Solution Approach 1:
The patent implements a universal data model that can represent multiple data types and formats from diverse machine sources through a common schema. This allows the system to handle various data sources (sensors, logs, databases) uniformly, reducing processing complexity while maintaining data variety. The common data model serves as a multi-functional framework that adapts to different input formats without requiring separate processing pipelines for each source type.
Solution Approach 2:
The patent introduces an intermediary layer (data intake and query system) that sits between diverse data sources and the analysis tools. This intermediary standardizes data ingestion, applies extraction rules, and transforms heterogeneous data into a unified format suitable for searching and analysis. The intermediary handles format conversion and data normalization, isolating the complexity from both the data sources and the analysis tools.
2Adaptability or versatility
If extraction rules are applied at search time rather than data collection time, then flexibility in data processing improves, but processing time during queries increases
Solution Approach 1:
The patent applies extraction rules during the data intake phase rather than during query execution. This preliminary processing transforms and standardizes data as it enters the system, creating pre-processed, searchable indexes. When queries are executed, the system searches these pre-processed indexes rather than applying complex extraction rules in real-time, significantly reducing query processing time while maintaining flexibility in how data is ingested and organized.
Solution Approach 2:
The patent implements a dynamic system where extraction rules can be configured and modified without requiring system redesign. The data model allows flexible schema definitions that can adapt to new data types and formats. This dynamic configuration capability enables the system to handle evolving data requirements while maintaining efficient query performance through pre-established extraction patterns.
3Productivity
If parallel processing and keyword indexing techniques are employed, then query efficiency improves, but system resource requirements increase
Solution Approach 1:
The patent divides the data processing system into segmented components that can operate in parallel. The data intake system, indexing system, and query processing system are separated into distinct modules. Keyword indexes are created as separate data structures from the main data storage, allowing independent optimization and parallel access. This segmentation enables multiple queries to be processed simultaneously without interfering with data ingestion or index maintenance operations.
Data Source
AI summary
An asset monitoring and reporting system (AMRS) implements an interface to establish an asset hierarchy to be monitored and reported against. The interface employs a search query of extant asset data from which definitional aspects of the asset hierarchy can be identified, and therefrom the interface automatically determines control information reflective of the asset hierarchy to direct the ongoing operation of the AMRS.