天地一体化信息网络2025，Vol.6Issue(1)：78-85,8.DOI:10.11959/j.issn.2096-8930.2025009
双引擎下的量子电子算力网络资源调度优化方法
Method of Optimize Scheduling Under Double Engines about Quantum/Electron Computing Power Networks Resource
摘要
Abstract
This paper presented an optimization method for resource scheduling in quantum/electron computing power networks under a dual-engine paradigm.To address the challenges associated with heterogeneous computing resources,guiding mechanisms and au-thentication technologies were introduced,included dual-engine labels under the"hybrid control"condition and dual-engine identifica-tion guidance under the'hybrid computing power'condition.Additionally,it proposed a dual-ngine scheduling mechanism based on"hy-brid metrics"under uncertain conditions,and a global optimal solution algorithm for heterogeneous computing power based on the com-prehensive integration model using relative entropy.The research on quantum/electron heterogeneous computing power networks,based on a dual-engine global optimization metric scheduling mechanism and algorithm for quantum/electron computing network re-sources,demonstrates both foresight and scientific rigor.A software system compatible with the design and development of allocation device prototype systems was implemented,which realized the transformation of a physical system into a processor at the software level,and completed the global optimization scheduling of the target task in the hybrid computing network.This method formulated a theory and innovates a new technical of engineering path for resource scheduling in quantum/electron computing power networks.关键词
混合算力网络/网络资源/算力调度/全局最优解Key words
hybrid computing power network/network resource/computing power scheduling/global optimum solution分类
信息技术与安全科学引用本文复制引用
程启月,陆军..双引擎下的量子电子算力网络资源调度优化方法[J].天地一体化信息网络,2025,6(1):78-85,8.基金项目
中国工程院行业院重大项目(No.2022-HYZD-01) （No.2022-HYZD-01）
科技创新载体计划项目(No.SZS2022416)Major Project of Industry Institute of China Academy of Engineering(No.2022-HYZD-01),Science and Technology Innovation Carrier Plan Project(No.SZS2022416) （No.SZS2022416）
