Scheduling Device Task Allocation via Environment Matching
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Solution Overview
Problem
Existing methods for executing image analysis tasks are inefficient as they require manual allocation of tasks to execution devices, leading to high attempt failure probabilities and low execution efficiency due to mismatched execution environments.
Innovation Solution
A method and apparatus that utilize a scheduling device to acquire a target algorithm and execution environment conditions, determine a suitable execution device based on these conditions, and send a control message for task execution, optimizing task allocation and execution by matching algorithms with compatible devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual allocation of tasks to execution devices is used, then task execution can be performed, but execution efficiency is low and attempt failure probability is high due to environment mismatch
Solution Approach 1:
The system enables automatic self-service task allocation where the scheduling device autonomously matches tasks with suitable execution devices based on environment compatibility, eliminating the need for manual allocation and reducing both inefficiency and failure rates
Solution Approach 2:
The system implements feedback mechanisms by evaluating execution environment information and compatibility before task allocation, allowing the scheduling device to learn from past execution outcomes and continuously improve task distribution decisions
2Productivity
If automatic scheduling based on environment matching is implemented, then task execution efficiency improves, but system complexity increases
Solution Approach 1:
The scheduling device serves as an intermediary between task sources and execution devices, centralizing the complex environment matching logic in a dedicated component that manages compatibility evaluation and task distribution without requiring changes to execution devices
Solution Approach 2:
The system segments the task execution framework into distinct functional components: task submission module, environment evaluation module, compatibility matching module, and task distribution module, allowing independent development and maintenance of each function
3Measurement precision
If environment evaluation is performed for all execution devices, then task allocation accuracy improves, but time consumption increases
Solution Approach 1:
The system performs preliminary evaluation of execution device environments and pre-calculates compatibility metrics before tasks arrive, storing environment profiles and compatibility results in advance to enable rapid task matching without real-time evaluation delays
Solution Approach 2:
The system transforms detailed environment evaluation parameters into simplified compatibility scores and classification categories, converting continuous environment metrics into discrete matching criteria that enable faster comparison and decision-making
Data Source
AI summary
A method for executing a task by a scheduling device, belonging to the technical field of electronics. The method includes: acquiring a target algorithm corresponding to a target task to be executed; acquiring an execution environment condition for a target algorithm, and current execution environment information of various execution devices; in the execution devices, determining a target execution device of which the execution environment information satisfies the execution environment condition; and sending a control message for executing the target task to the target execution device.