Edge Query Processing With Dynamic Ledger Approximate Responses
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Solution Overview
Problem
The proliferation of data from distributed sensors and devices in value chain networks overwhelms the ability to transmit and process data effectively, leading to complexity and inefficiencies in centralized decision-making.
Innovation Solution
A method for processing queries in a distributed database using edge devices, involving dynamic ledgers and probability distribution models to generate approximate responses based on summary data, reducing the need for full data transmission and enhancing data processing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is transmitted from distributed sensors to centralized systems for processing, then complete data analysis is achieved, but network bandwidth is overwhelmed and transmission time increases
Solution Approach 1:
The patent implements edge computing nodes distributed throughout the sensor network that perform local data processing and analysis. Each edge node processes data from nearby sensors locally, providing region-specific data insights without requiring all raw data to be transmitted to a centralized system. This resolves the contradiction by maintaining data analysis completeness through distributed processing while significantly reducing network bandwidth consumption.
Solution Approach 2:
The patent divides the centralized data processing system into multiple distributed edge computing nodes. Each node handles a specific segment of the network, processing data locally and independently. This segmentation allows the system to maintain comprehensive data analysis capabilities across the entire network while each segment operates with reduced bandwidth requirements, thus resolving the contradiction between complete analysis and bandwidth consumption.
2Loss of information
If all sensor data is transmitted to centralized systems, then comprehensive insights are obtained, but processing time and system complexity increase
Solution Approach 1:
The patent segments the centralized processing architecture into multiple distributed edge nodes, each handling local data processing independently. This segmentation maintains comprehensive insight generation by distributing analytical capabilities across the network while reducing system complexity at any single point, as each edge node operates autonomously with its own processing resources.
Solution Approach 2:
The patent transitions from a single-dimensional centralized processing model to a multi-dimensional distributed architecture. Edge nodes are deployed across spatial dimensions of the network, creating a three-dimensional processing structure (multiple nodes × multiple data types × multiple processing layers). This dimensional transformation enables comprehensive data insight generation while distributing system complexity across multiple dimensions, preventing any single point from becoming overwhelmed.
3Measurement precision
If centralized processing is used for all queries, then accurate results are achieved, but response time increases due to data transmission delays
Solution Approach 1:
The patent implements preliminary data processing and aggregation at edge nodes before queries are executed. Edge nodes pre-process sensor data, maintain local data summaries, and prepare aggregated information in advance. When queries arrive, the edge nodes can quickly retrieve and process relevant pre-prepared data locally, achieving accurate results without the time penalty of transmitting raw data from centralized systems, thus resolving the contradiction between accuracy and response time.
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 method includes causing, by the edge device, the query to be stored on a dynamic ledger maintained by the distributed database. The method includes detecting, by the edge device, that summary data has been stored on the dynamic ledger. The method includes generating, by the edge device, an approximate response to the query based on the summary data stored on the dynamic ledger. The method includes transmitting, to the query device, the approximate response.