Intelligent road network-oriented cloud edge collaborative computing resource elastic scheduling method and system
By deploying lightweight monitoring agents on roadside edge computing nodes, and combining task priorities and node load status, a hybrid scheduling strategy is generated, and the computing resource quotas of edge nodes are dynamically adjusted. This solves the problems of rigid resource scheduling and ambiguous task priorities in the vehicle-road-cloud integrated system, achieves efficient resource utilization and differentiated task protection, and improves the system's response speed and model iteration efficiency.
Patent Information
- Application Number
- CN202610450689.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-04-08
- Publication Date
- 2026-07-17
AI Technical Summary
The integrated vehicle-road-cloud system suffers from problems such as rigid cloud-edge computing resource scheduling, ambiguous task priorities, and uneven load on edge nodes, resulting in idle or overloaded computing resources, affecting system response speed and stability, and making it difficult to achieve efficient resource utilization and differentiated task assurance.
By deploying lightweight monitoring agents on roadside edge computing nodes, resource utilization and network latency data are collected in real time. Combined with task priority and node load status, a hybrid scheduling strategy is generated. The computing resource quotas of edge nodes are dynamically adjusted through the cloud resource scheduling center. By aggregating edge model parameters through collaborative learning, elastic scheduling of resources is achieved.
It improved system resource utilization, task response speed, and model iteration efficiency, enhanced the overall intelligence level of scheduling, and ensured efficient utilization of computing resources and differentiated task support.
Smart Images
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