Vehicle Task Allocation Using QoS-Based Cloud Fallback
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Solution Overview
Problem
Vehicles connected to remote computing systems face disruptions when wireless connectivity degrades, leading to unavailability of cloud or edge-hosted functionality, which can impact vehicle computing tasks and battery range.
Innovation Solution
Implementing a system that uses cold standby backup processes on vehicles to execute primary and secondary computing tasks, with adaptive QoS measurements to adjust the allocation of tasks between the vehicle and the remote computing system, ensuring energy efficiency and extended battery range by shifting tasks based on connectivity quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If vehicle computing tasks are performed on cloud/edge servers, then energy consumption on vehicle is reduced and battery range is extended, but cloud functionality becomes unavailable when wireless connectivity degrades
Solution Approach 1:
The system performs preliminary actions by maintaining cold standby backup processes on the vehicle that can be activated when connectivity degrades. The vehicle controller keeps backup processes ready in advance, so when wireless connectivity deteriorates, these pre-positioned resources can immediately take over without interruption to critical vehicle functions.
Solution Approach 2:
The system dynamically changes operational parameters by adjusting the allocation of computing tasks between vehicle and cloud based on connectivity quality metrics. When connectivity quality falls below thresholds, the system transitions tasks from cloud-execution mode to vehicle-execution mode, changing the operational state to maintain reliability while managing energy consumption.
2Reliability
If computing tasks are executed on vehicle controller, then functionality is always available, but energy consumption increases reducing battery range
Solution Approach 1:
The system applies partial action by selectively executing only critical vehicle computing tasks on the vehicle controller when connectivity degrades, rather than all tasks. Non-critical tasks continue to be executed on cloud servers, so the vehicle maintains essential functionality with reduced energy consumption compared to running all tasks locally.
Solution Approach 2:
The system segments computing tasks into different categories (critical vs. non-critical) and allocates them to different execution locations based on connectivity conditions. Critical tasks are segmented for local execution on the vehicle controller to ensure availability, while non-critical tasks remain on cloud servers to conserve energy.
3Productivity
If wireless connectivity is monitored in real time, then task allocation can be optimized, but system complexity increases
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring wireless connectivity quality metrics and using this information to dynamically adjust task allocation decisions. The vehicle controller receives feedback on connectivity status and automatically adjusts which tasks execute locally versus remotely, optimizing productivity through real-time adaptation without requiring complex manual intervention.
Data Source
AI summary
A method for performing a plurality of vehicle computing tasks includes determining the plurality of vehicle computing tasks that need to be performed and monitoring a wireless connectivity between a vehicle and a remote computing system. Monitoring the wireless connectivity between the vehicle and the remote computing system includes measuring, in real time, at least one quality of service (QoS) measurement of the wireless connectivity between the vehicle and the remote computing system. The method further includes determining whether to perform at least one of the plurality of vehicle computing tasks in at least one of the remote computing system or a vehicle controller of the vehicle based on at least one QoS measurement.