Asset Application Datastacks for Low-Overhead Data Sharing
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Solution Overview
Problem
Existing systems face challenges in sharing and managing data across multiple applications effectively, particularly in cloud and fog computing environments, where sharing datapoints can lead to inefficiencies and resource wastage, and require improvements to achieve meaningful results.
Innovation Solution
The implementation of a method and system for generating and sharing metadata stacks between applications, which include metadata strings based on asset operations, enabling access and reference without transmitting all datapoints, allowing for efficient data accumulation and analysis across applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all datapoints are transmitted between applications, then data completeness is improved, but network resource usage and computing overhead increase
Solution Approach 1:
The patent extracts only the essential metadata components (metadata strings, unique identifiers, timestamps) from the complete datapoints and transmits only these extracted elements between applications. This allows applications to reference and access complete datapoints locally without transmitting the entire data set, thereby maintaining data completeness while significantly reducing network resource usage.
Solution Approach 2:
Instead of transmitting actual datapoints, the system creates and transmits metadata copies that reference the original datapoints. Each metadata stack contains metadata strings and unique identifiers that act as references to the complete datapoints stored locally in each application, enabling data sharing without physical data transmission.
2Adaptability or versatility
If multiple applications access the same datapoints, then data analysis capability is improved, but computing resource consumption increases
Solution Approach 1:
The patent introduces metadata stacks as an intermediary layer between multiple applications and the underlying datapoints. Each application maintains local copies of datapoints and uses metadata stacks to reference and coordinate access to shared data. This intermediary mechanism enables multiple applications to analyze the same datapoints simultaneously without requiring centralized data management, thereby improving data analysis capability while distributing computing resource consumption across multiple local systems.
3Loss of energy
If data is shared between applications via metadata stacks, then resource efficiency is improved, but system complexity increases
Solution Approach 1:
The patent segments the data sharing system into distinct modular components: metadata strings for data description, unique identifiers for data reference, timestamps for data context, and metadata stacks for data organization. This segmentation allows each component to be independently managed and processed, reducing the complexity of managing the entire data sharing system while maintaining resource efficiency benefits.
Data Source
AI summary
A system, device, method, and datastack for managing applications that manage operation of assets are provided. In the method, data is shared between the applications. The method includes generating, by a first application of the applications, one or more metadata stacks associated with one or more assets. The one or more metadata stacks include at least one metadata string generated based on operation of the one or more assets. Access to the one or more metadata stacks is enabled. A second application of the applications is capable of accessing the one or more metadata stacks and datapoints associated with the one or more metadata stacks.