Navigation Data Generalization Factor for Storage Optimization
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Solution Overview
Problem
Navigation data stored locally in devices is large due to varying zoom levels, leading to increased bandwidth and memory requirements, and incremental updates are inefficient in maintaining data freshness.
Innovation Solution
A method to determine a generalization factor for navigation data elements based on usage information, allowing for varying levels of detail in generated data elements, which reduces storage size and update patch sizes by prioritizing detail in frequently used areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If navigation data is stored locally at the terminal with high detail for all zoom levels, then navigation quality and user experience are improved, but the size of locally stored navigation data increases significantly
Solution Approach 1:
The patent applies local quality by determining different generalization factors for different data elements based on their specific usage information. Frequently accessed regions receive higher detail (lower generalization factor) while less accessed regions receive lower detail (higher generalization factor), optimizing the balance between navigation quality and data size on a local, region-by-region basis
Solution Approach 2:
The patent changes the parameter of data detail level dynamically by adjusting the generalization factor based on usage information. The system modifies the level of detail for different map regions according to their access frequency and importance, rather than maintaining uniform high detail across all regions
2Reliability
If incremental updates are provided to prevent navigation data from becoming outdated, then data freshness is maintained, but the transmission bandwidth and memory requirements increase
Solution Approach 1:
The patent applies local quality to update transmission by sending incremental updates only for specific regions that have changed, rather than redistributing entire navigation data sets. The system identifies and transmits only the affected data elements with their appropriate generalization factors, reducing unnecessary transmission of unchanged high-detail data
Solution Approach 2:
The patent implements partial action by providing incremental updates that cover only the necessary portions of navigation data that have changed or need refreshing. Instead of performing complete data redistribution, the system applies updates selectively to specific regions and data elements based on change detection and usage patterns
3Adaptability or versatility
If navigation data includes data for different zoom levels, then navigation functionality across various scales is improved, but the size of navigation data increases
Solution Approach 1:
The patent applies local quality by applying different generalization factors to data elements at different zoom levels based on their specific usage information. Frequently accessed regions maintain high detail across multiple zoom levels, while less accessed regions use higher generalization factors at lower zoom levels, optimizing the balance between multi-scale functionality and data size
Data Source
AI summary
A method is disclosed comprising: determining, using a processor, a generalization factor associated with a data element of a database comprising navigation data, the generalization factor depending on a usage information associated with the data element, wherein the generalization factor is indicative to a level of details of a new data element to be generated based on the data element. Further disclosed are a corresponding apparatus, a corresponding system and a corresponding computer readable storage medium.