In-Vehicle Application QoS via Predictive Coverage Caching
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Solution Overview
Problem
Current QoS tuning techniques for in-vehicle applications react to current network conditions and fail to prevent service outages in areas with uneven cellular coverage.
Innovation Solution
A system that uses historical and current network speed data from remote actors to predict and map network coverage ahead of a vehicle, caching application data before entering poor coverage zones to maintain quality of service.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current QoS tuning techniques are used, then the system can react to current network conditions, but it cannot prevent service outages in areas with uneven cellular coverage
Solution Approach 1:
The system performs preliminary actions by mapping historical network speed data along the road ahead of the vehicle to identify bad network coverage zones before the vehicle reaches them. This allows proactive caching of application data in advance, preventing service outages rather than reacting to them after they occur.
2Measurement precision
If historical network speed data from multiple remote actors is collected and processed, then network coverage prediction accuracy improves, but system complexity increases
Solution Approach 1:
The system segments the road into multiple road segments and collects network speed data for each segment from multiple remote actors. This segmentation allows the complex task of predicting network coverage along the entire road to be broken down into manageable units, improving accuracy while enabling systematic processing.
Solution Approach 2:
The system uses historical network speed data copied from multiple remote actors who have previously traversed the same road. By aggregating and mapping this copied data, the system can predict future network conditions without requiring the current vehicle to continuously measure every parameter in real-time.
3Reliability
If application data is cached before entering bad network coverage zones, then service outages are prevented, but data storage requirements increase
Solution Approach 1:
The system determines the amount of time the vehicle will spend in bad network coverage zones and calculates the corresponding data volume to cache in advance. This preliminary calculation ensures that only the necessary amount of data is cached, balancing reliability with storage requirements.
Data Source
AI summary
A method for maintaining network quality of service (QoS) for in-vehicle applications includes receiving historical network speed data from a plurality of remote actors and mapping a network speed along the road ahead of the host vehicle using the historical network speed data from the plurality of remote actors and identifying a bad network coverage zone along the road ahead of the host vehicle. The method further includes determining an amount of time that the host vehicle will spend in the bad network coverage zone, determining an amount of application data to cache as a function of the amount of time that the host vehicle will spend in the bad network coverage zone, and caching the amount of application data before the host vehicle reaches the bad network coverage zone.