电子学报2025，Vol.53Issue(6)：1847-1864,18.DOI:10.12263/DZXB.20241050
云边端异构算力网络计算任务分割与路径优化方法研究
Task Segmentation and Path Optimization in Heterogeneous Cloud-Edge-End Computing Power Network
摘要
Abstract
Collaborative optimization of transmission,computation,and storage resources in"cloud-edge-end"com-puting power networks is a critical and highly challenging task.Effectively integrating high-performance cloud resources,low-latency edge resources,widely distributed node resources,and low-cost user resources to achieve intelligent resource distribution,association,trading,and allocation are essential for the optimal configuration and efficient utilization of net-work-wide resources.This paper constructs a detailed mathematical model for the"cloud-edge-end"heterogeneous comput-ing power networks with a focus on the integration of transmission and computation.Addressing multiple dimensions such as computing power demand,resource distribution,trading,and allocation,the joint optimization problem of minimizing de-lay and cost in scheduling heterogeneous computing and transmission resources is transformed into a mixed-integer nonlin-ear programming problem.Subsequently,an innovative serial sub-task path allocation mechanism is proposed,combined with the optimal route and assignment maximization(ORAM),to achieve efficient collaborative optimization of task com-putation and transmission paths.This mechanism divides computing tasks into multiple sub-tasks,perceives and manages the dependencies between serial sub-tasks,and utilizes the ORAM algorithm to select optimal computation paths that satisfy dependency relationships in real-time.It directs the transmission of computation results to target nodes with the fewest hops,thereby forming an end-to-end efficient resource scheduling channel.This approach not only reduces transmission de-lay and resource costs but also effectively transforms the traditional"transmit-then-compute"model into a"transmit-com-pute collaborative"model.Experimental results demonstrate that the proposed algorithm outperforms various benchmark al-gorithms in terms of delay,cost,and path optimization under different computational demands,sensing ranges,and node quantities.关键词
算力网络/任务调度/算力任务/传输路径/算力架构Key words
computing power network/task scheduling/computing task/transmission path/computing power architecture分类
信息技术与安全科学引用本文复制引用
马博,余应洁,吴莎尘,倪畅,陆琴,陈超,李传煌..云边端异构算力网络计算任务分割与路径优化方法研究[J].电子学报,2025,53(6):1847-1864,18.基金项目
国家自然科学基金(No.62401506,No.62301488,No.62302446) （No.62401506,No.62301488,No.62302446）
浙江省科技创新重点项目(No.2023R5211) （No.2023R5211）
浙江省自然科学基金(No.LZ23F010003,No.LQ23F010009) （No.LZ23F010003,No.LQ23F010009）
浙江省属高校基本业务费专项资金资助项目(No.QRK23009) National Science Foundation of China(No.62401506,No.62301488,No.62302446) （No.QRK23009）
Zhejiang Provincial Science and Technology Innovation Key Project(No.2023R5211) （No.2023R5211）
Natural Science Foundation of Zhejiang Province(No.LZ23F010003,No.LQ23F010009) （No.LZ23F010003,No.LQ23F010009）
Fundamental Research Funds for the Provincial Universities of Zhejiang(No.QRK23009) （No.QRK23009）
