Hierarchical Data Store for IoT Network Cost Reduction
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Solution Overview
Problem
Current systems for managing mass data generated by IoT devices face challenges in reducing infrastructure construction costs, network costs, and ensuring real-time data upload, especially due to limitations in bandwidth and accessibility.
Innovation Solution
A data management system utilizing a hierarchical data store with both an original data store and a lightweight data store, where original data is converted into lightweight data through lightweighting processing and uploaded to the lightweight data store, reducing network costs and enabling real-time data upload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If mass data is uploaded to cloud storage, then user accessibility is improved, but infrastructure construction costs and network costs increase
Solution Approach 1:
The patent segments the data storage system into two distinct components: a lightweight data store for frequently accessed data and an original data store for archiving. This segmentation allows users to access commonly needed data from the lightweight store without requiring expensive cloud infrastructure for the entire dataset, thereby reducing overall infrastructure costs while maintaining accessibility for critical data.
Solution Approach 2:
The patent creates lightweight copies of original data in a compressed or summarized format. These copies are stored in the lightweight data store and can be accessed quickly without retrieving the full original data from expensive cloud storage. This copying approach maintains user accessibility for essential information while significantly reducing the infrastructure costs required for storing and accessing the complete dataset.
2Ease of operation
If mass data is uploaded to cloud storage, then data availability is improved, but network costs increase
Solution Approach 1:
The patent implements local quality by placing a lightweight data store locally or in a low-latency location that provides fast access to frequently needed data. This eliminates the need to continuously transfer large amounts of data over the network, thereby reducing network costs while maintaining data availability for common operations. The original data remains in cloud storage but is only accessed when necessary.
3Speed
If continuously generated mass data is uploaded in real time, then data freshness is improved, but network bandwidth limitations prevent successful upload
Solution Approach 1:
The patent creates lightweight copies of incoming data that can be uploaded quickly to the lightweight data store. These compressed or summarized copies are generated in real-time and transmitted over the network with minimal bandwidth consumption, while the full original data is stored locally or in batch mode. This approach maintains data freshness for critical information without being constrained by network bandwidth limitations.
4Manufacturing precision
If original data is downloaded for processing, then processing accuracy is improved, but network costs increase
Solution Approach 1:
The patent implements local quality by keeping the original high-fidelity data in the original data store (local or cloud) and only transferring lightweight copies when processing is required. For routine operations, processing is performed on the lightweight data locally, avoiding network transfers. When high precision is needed, the system selectively retrieves only the specific original data required, minimizing network costs while maintaining processing accuracy.
Data Source
AI summary
The present invention provides a system for managing data based on a hierarchical data store and a method of operating the same. The data management system according to one embodiment of the present invention may include a data uploader for obtaining original data from one or more data sources, converting the obtained original data into corresponding lightweight data through lightweighting processing, and uploading the lightweight data to a lightweight data store and a data tracer for updating the upload location of specific original data in a mapping table in response to detecting that the specific original data is uploaded to an original data store. The data management system may efficiently reduce network costs required for data upload and infrastructure construction costs required for data sharing.