Edge Query Processing Using Summary Statistics in Value Chain Networks
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Solution Overview
Problem
The proliferation of data from IoT sensors and other sources in value chain networks overwhelms traditional centralized data collection methods, leading to complexity and inefficiencies in data transmission and automated decision-making.
Innovation Solution
A method for processing queries in a distributed database using edge devices, where queries are stored on a dynamic ledger, generating approximate responses based on summary data, and transmitting these responses, with the option to use a neural network for probability distribution modeling and query planning across edge devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If centralized data collection methods are used to gather data from IoT sensors in value chain networks, then complete data availability is achieved, but network overhead and complexity increase significantly
Solution Approach 1:
The patent segments the centralized data collection architecture into distributed edge computing nodes deployed across the value chain network. Each edge device independently processes and stores data locally, eliminating the need for continuous centralized data transmission while maintaining data availability through the distributed ledger technology.
Solution Approach 2:
The patent introduces a distributed ledger as an intermediary layer between edge devices and central systems. The ledger stores query definitions and summary statistics, enabling edge devices to respond to queries autonomously without direct centralized coordination, thus reducing network overhead while preserving data accessibility.
2Reliability
If all raw data is transmitted to centralized systems for processing, then accurate decision-making is enabled, but transmission time and processing delays increase
Solution Approach 1:
The patent implements preliminary action by pre-computing and storing summary statistics, aggregates, and metadata in the distributed ledger before queries are executed. When queries arrive at edge devices, responses can be generated immediately using pre-prepared data structures, eliminating the need for time-consuming data aggregation and processing at query time.
Solution Approach 2:
The patent applies partial action by storing and processing only summary statistics and aggregated data at edge devices rather than complete raw datasets. This approach provides sufficient information for most decision-making scenarios while dramatically reducing data volumes and processing requirements, with full raw data available on-demand if needed.
3Productivity
If edge devices generate approximate responses using summary data, then response time is reduced, but data precision may be compromised
Solution Approach 1:
The patent implements dynamics by making the data precision adaptive based on query requirements. The system can dynamically switch between returning approximate summary statistics for routine queries and retrieving exact raw data for critical analyses. The distributed ledger stores both summary data for speed and references to complete datasets for accuracy when needed.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system monitors query patterns, data usage, and decision outcomes to continuously improve summary statistic generation. The distributed ledger tracks query performance and data accuracy metrics, enabling iterative refinement of aggregation methods and precision levels based on actual system performance and user needs.
Data Source
AI summary
A method for processing a query for data stored in a distributed database includes receiving, at an edge device, the query for data stored in the distributed database from a query device. The query is a request for data stored at the edge device and for data stored at other edge devices. The method includes executing, by the edge device, the query to find partial query results comprising the data stored at the edge device. The method includes generating, by the edge device, statistical information based on the partial query results. The method includes determining, by the edge device, a statistical confidence associated with the partial results based on the statistical information. The method includes generating, by the edge device, an approximate response to the query based on the statistical information. The method includes transmitting the approximate response to the query device.