Computer system service optimization scheduling method for photoelectric system

Through task characteristic perception, resource modeling and adaptive scheduling strategies, the scheduling problems of dynamic task changes and resource uncertainty in optoelectronic systems are solved, efficient matching of tasks and resources and continuous optimization of system performance are achieved, and response speed and resource utilization are improved.

CN120610792AInactive Publication Date: 2025-09-09CHANGZHOU WANTUO OPTOELECTRONICS TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202510701736.X
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-05-28
Publication Date
2025-09-09
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

Existing optoelectronic system scheduling methods are unable to cope with the dynamic changes of tasks and the uncertainty of system resource status. They lack the ability to coordinately optimize the task dependency structure and resource topology structure, and are unable to comprehensively consider the communication density between tasks, the scheduling hierarchy, and the structural matching relationship of computing resources, resulting in task delays, low resource utilization, and system performance fluctuations.

Method used

By adopting the methods of task characteristic perception, resource modeling, priority evaluation, dynamic mapping and scheduling strategy adjustment, combined with machine learning and reinforcement learning technologies, an adaptive scheduling system is constructed. Through task feature extraction, resource status prediction and structured mapping, efficient matching of tasks and resources and continuous optimization of scheduling strategies are achieved.

Benefits of technology

It improves the response speed and resource utilization efficiency of tasks in the optoelectronic system, ensures the priority execution of key tasks, enhances the stability and sustainability of the system in high-density task environments, and adapts to dynamic environments and multi-task heterogeneous challenges.

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Abstract

The invention discloses a computer system service optimization scheduling method for a photoelectric system, and particularly relates to the technical field of computer service optimization, which comprises the following steps of: sensing and extracting information such as task types and time constraints through task characteristics, and constructing a multi-dimensional resource model such as processing capability and idle degree by combining resource modeling; a weighting mechanism is used for evaluating task priorities and generating a scheduling queue, tasks are dynamically mapped to matched resources, a scheduling strategy is adjusted according to system loads and feedback, model parameters are optimized through service feedback, and efficient, self-adaptive and intelligent optimization of task scheduling of the photoelectric system is achieved; according to the method, a dynamic scheduling mechanism based on task characteristics and resource prediction is realized, and the response speed of the high-optimal task is improved; optimizing the resource utilization rate by adopting resource state modeling and prospective mapping; and reinforcement learning and a feedback closed loop are introduced, a sustainable optimization scheduling system is constructed, and the adaptability and stability of the system in a complex photoelectric task environment are enhanced.
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