Value-Anticipating Task Offloading for Vehicle Processing
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Solution Overview
Problem
Vehicles with less powerful processing capabilities struggle to accurately detect and track objects due to processor-intensive algorithms, leading to a need for efficient offloading of computationally complex tasks to external systems with more resources.
Innovation Solution
A system and method for value-anticipating task offloading, which includes a task manager module that determines a utility score for computational tasks using a state vector and utility function, deciding whether to offload tasks to an external system, process locally, or discard them, based on the potential improvement in application performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If vehicles with less powerful processing capabilities execute object detection and tracking algorithms locally, then processing can be performed without external dependencies, but the accuracy and effectiveness of object detection and tracking deteriorate due to processor limitations
Solution Approach 1:
The patent extracts the computationally intensive object detection and tracking algorithms from the vehicle's local processor and relocates them to external servers with superior processing capabilities. This allows the vehicle to maintain reliable object detection and tracking functionality without being constrained by its own limited processing power, effectively resolving the contradiction between local processing independence and detection accuracy.
Solution Approach 2:
The patent introduces communication networks and external servers as intermediaries between the vehicle and the object detection/tracking processing. Instead of the vehicle processor directly performing all computations, the system uses an intermediary infrastructure to handle the computationally intensive tasks, enabling high-accuracy detection and tracking while preserving the vehicle's autonomy in making processing decisions.
2Measurement precision
If vehicles offload computationally complex tasks to external systems, then processing accuracy improves, but system complexity and dependency on external infrastructure increase
Solution Approach 1:
The patent creates a universal offloading framework that can handle multiple types of computational tasks (object detection, object tracking, and other processor-intensive operations) through a single standardized system architecture. This multi-functional approach reduces overall system complexity by providing a unified solution rather than requiring separate specialized systems for each computational task.
Solution Approach 2:
The patent dynamically adjusts offloading decisions based on changing system parameters such as network availability, external server status, and vehicle computational needs. By making the offloading system adaptive rather than static, the patent reduces complexity in challenging situations while maintaining high tracking accuracy when conditions are favorable.
3Use of energy by moving object
If vehicles use lighter weight versions of algorithms to conserve processing resources, then energy consumption and computational load decrease, but detection and tracking accuracy deteriorates
Solution Approach 1:
The patent extracts the computationally intensive algorithms from the vehicle's local processor and relocates them to external servers with superior processing capabilities. This allows the vehicle to maintain reliable object detection and tracking functionality without being constrained by its own limited processing power, effectively resolving the contradiction between local processing independence and detection accuracy.
Solution Approach 2:
The patent implements a hybrid approach where the vehicle executes lighter weight versions of algorithms locally for basic functionality and energy efficiency, while offloading specific computationally intensive sub-tasks to external servers when enhanced accuracy is needed. This partial offloading strategy allows the system to balance energy consumption with detection accuracy dynamically.
Data Source
AI summary
A system, method, and non-transitory computer-readable medium allows for value-anticipating task offloading. The system may include one or more processors and a memory having a task manager module. The task manager module causes the one or more processors to receive a task identifier of a computational task for an application being utilized by a vehicle processor of a vehicle and a state vector describing at least one state of the vehicle and determine, using a utility function, a utility score of the computational task using the task identifier and the state vector which represents an improvement in a functioning of the application if the computational task is offloaded to an external system for processing. Based on the utility score, the one or more processors may offload the computational task to the external system, process the computational task by the vehicle processor of the vehicle, or discard the computational task.