Map Data Pre-fetching for Offline Routing Efficiency
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Solution Overview
Problem
Existing map rendering systems on mobile devices face inefficiencies in data management due to the large amounts of network data required for mapping applications, leading to prolonged download times and high bandwidth and processor usage, especially when intermittent connections and limited computing resources are involved.
Innovation Solution
A method for pre-fetching map data tiles by determining secondary routes and corresponding map data tiles based on primary routes, storing them in local memory before they are needed, which includes accessing map data tiles from a map database and storing them in local memory before initiating a function to generate or display a route, optimizing data retrieval and processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all map data tiles are downloaded to ensure complete coverage and availability, then data availability is improved, but download time and bandwidth consumption increase significantly
Solution Approach 1:
The system performs preliminary actions by pre-fetching map data tiles along predicted routes before the user actually needs them. The route prediction module anticipates future location needs and triggers data retrieval in advance, so that when the user travels along the predicted route, the map data is already cached locally, eliminating download delays during actual use.
Solution Approach 2:
Instead of downloading all map data tiles at once, the system segments the complete map dataset into individual tiles and selectively retrieves only those corresponding to predicted routes. This segmentation allows the system to manage bandwidth consumption by loading only necessary portions of data while maintaining availability for the user's anticipated path.
2Loss of time
If map data is pre-fetched for predicted routes, then download time is reduced and bandwidth efficiency is improved, but data management complexity increases
Solution Approach 1:
The pre-fetching mechanism serves multiple functions simultaneously: it reduces download time, optimizes bandwidth usage, enables offline access during intermittent connections, and anticipates user needs through route prediction. By consolidating these functions into a single automated pre-fetching process, the system manages complexity through multi-functionality rather than requiring separate systems for each purpose.
Solution Approach 2:
The system performs self-service by automatically predicting routes and fetching map data without requiring manual user intervention. The route prediction module analyzes historical data and user behavior patterns to autonomously determine which routes are most likely to be needed, and the pre-fetching mechanism automatically retrieves and caches the corresponding map tiles, freeing the user from manual data management tasks.
3Reliability
If map data is cached locally for offline access, then availability during intermittent connections is improved, but storage requirements increase
Solution Approach 1:
Instead of uniformly caching all map data, the system applies local quality by selectively storing only map tiles corresponding to predicted routes in the local cache. This targeted approach ensures that high-value data (routes the user is likely to traverse) is available offline while minimizing the total storage footprint by excluding tiles for locations the user is unlikely to visit.
Solution Approach 2:
The system performs preliminary route prediction and data selection before caching occurs. By anticipating which routes the user will take based on historical patterns and current context, the system pre-identifies the subset of map data that needs to be cached for offline availability, rather than caching everything and filtering later.
4Device complexity
If conventional route generation is used without pre-fetching, then processing simplicity is maintained, but data retrieval efficiency deteriorates
Solution Approach 1:
The system performs preliminary route prediction and data preparation before the actual data retrieval and display operations. By analyzing historical route data and predicting future routes in advance, the system prepares map data tiles for efficient retrieval, separating the prediction function from the execution function to maintain processing simplicity while dramatically improving retrieval efficiency.
Solution Approach 2:
The pre-fetching mechanism establishes continuity by maintaining a persistent cache of predicted route data that is continuously updated and ready for immediate access. Rather than performing data retrieval on-demand which creates interruptions, the system continuously maintains available data in the cache, ensuring seamless user experience during intermittent connections without adding significant processing complexity.
Data Source
AI summary
The present application describes techniques for fetching map data as a selected subset of entire map data available, by selecting map data tiles corresponding to an area that encompasses a first route and to an area encompassing a secondary route based on the first route. An amount of map data accessed may be adjusted based on a priority of the secondary route.