Agent-based and parallel immune computing-based computing power network resource scheduling method and device
By using an agent-based and parallel immune computing approach, computing network resources are virtualized and clustered, and combined with multi-dimensional judgment conditions and auction mechanisms, the scheduling problem of existing computing network resource scheduling technologies in large-scale, heterogeneous, and highly dynamic scenarios is solved, achieving efficient and flexible resource scheduling and task adaptation.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- SHENZHEN Y& D ELECTRONICS CO LTD
- Filing Date
- 2026-06-17
- Publication Date
- 2026-07-17
AI Technical Summary
Existing computing power network resource scheduling technologies suffer from problems such as a single scheduling mode, fixed evaluation indicators, insufficient flexibility in dynamic adaptation, low efficiency in large-scale node optimization, weak heterogeneous resource collaboration capabilities, and limitations in intelligent scheduling technology in large-scale, heterogeneous, and highly dynamic scenarios, making it difficult to meet the requirements of high real-time performance and global optimization.
A method based on intelligent agents and parallel immune computing is adopted to virtualize and cluster the heterogeneous physical resources in the computing network, generate a standardized virtual resource model, filter the resource set by combining multi-dimensional judgment conditions, schedule it through auction mechanism and multi-group parallel immune algorithm, and monitor and update resource information in real time to form a closed loop optimization.
It has achieved multi-objective collaborative scheduling capability in highly dynamic scenarios, improved the optimization efficiency of large-scale heterogeneous resources, ensured the precise coordination of tasks and resources, improved the flexibility and speed of scheduling, and guaranteed the service quality of high-value tasks.
Smart Images
Figure CN122412166A_ABST