算力网络中成本最小化的跨地域流量调度算法

张旭; 顾梦瑶; 宁萌; 冯川; 巩小雪; 郭磊

doi:10.11959/j.issn.1000-0801.DXKX260166

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算力网络中成本最小化的跨地域流量调度算法

更新时间：2026-05-11

- 算力网络中成本最小化的跨地域流量调度算法
- Cost-Minimized Cross-Regional Traffic Scheduling Algorithm in Computing Power Networks
- 电信科学 2026年
- 作者机构：
  
  1.重庆邮电大学通信与信息工程学院，中国重庆，400065
  2.重庆邮电大学智能通信与网络安全研究院，中国重庆，400065
  3.重庆邮电大学大数据智能计算重点实验室，中国重庆，400065
  4.东北大学计算机科学与工程学院，中国沈阳，110819
- 作者简介：
  
  冯川，fengc@cqupt.edu.cn
- 基金信息：
  
  国家自然科学基金资助项目(62571078;62331017;62501097);重庆市自然科学基金资助项目(CSTB2025NSCQ-GPX1283);重庆市教育委员会科学技术研究基金资助项目(KJQN202400621)
- DOI：10.11959/j.issn.1000-0801.DXKX260166
  中图分类号： TP913
- 收稿：2026-03-11，
  
  修回：2026-04-05，
  
  录用：2026-05-11，
- 稿件说明：
移动端阅览
张旭, 顾梦瑶, 宁萌, 等. 算力网络中成本最小化的跨地域流量调度算法[J/OL]. 电信科学, 2026.

ZHANG Xu, GU Mengyao, NING Meng, et al. Cost-Minimized Cross-Regional Traffic Scheduling Algorithm in Computing Power Networks[J/OL]. Telecommunications Science, 2026.
张旭, 顾梦瑶, 宁萌, 等. 算力网络中成本最小化的跨地域流量调度算法[J/OL]. 电信科学, 2026. DOI： 10.11959/j.issn.1000-0801.DXKX260166.

ZHANG Xu, GU Mengyao, NING Meng, et al. Cost-Minimized Cross-Regional Traffic Scheduling Algorithm in Computing Power Networks[J/OL]. Telecommunications Science, 2026. DOI： 10.11959/j.issn.1000-0801.DXKX260166.

摘要

针对各地域算力资源供需不平衡及电价差异显著所导致的资源调度成本较高、资源利用率较低的问题，将业务计算与网络传输过程中的能耗总成本建模为混合整数线性规划问题，并提出一种基于成本最小化的跨地域流量调度算法（Cost-Minimized Cross-Regional Traffic Scheduling Algorithm，CM-CRTSA）。该算法通过构建带超级源点和超级汇点的业务—数据中心二部衍生流图，利用最小费用最大流方法实现业务请求与数据中心之间的最优匹配；在路径选择阶段，综合考虑能耗成本与链路频谱资源状态，对候选路径进行优先级排序；在频谱分配阶段，引入频谱连续度指标以优选可用频谱块。仿真结果表明，该算法能够有效降低跨地域流量调度的总成本与业务阻塞率，并在高负载条件下保持良好的资源调度稳定性，为算力网络环境下的跨地域算网协同调度提供了一种高效解决方案。

Abstract

To address the high resource scheduling cost and low resource utilization caused by the imbalance of computing resource supply and demand across regions and significant electricity price differences

the total energy consumption cost involved in task computation and network transmission is formulated as a mixed-integer linear programming (MILP) problem. Based on this model

a Cost-minimized Cross-Regional Traffic Scheduling Algorithm (CM-CRTSA) was proposed. In this algorithm

a bipartite derivative flow graph with super source and sink nodes was constructed to achieve optimal matching between service requests and data centers using the minimum-cost maximum-flow method. During path selection

both energy cost and spectrum status were considered to rank candidate paths. In the spectrum allocation stage

a contiguity metric was introduced to prioritize available spectrum blocks. Simulation results demonstrated that CM-CRTSA effectively reduced the total scheduling cost and request blocking ratio

and maintained stable resource scheduling performance under high load

providing an efficient solution for cross-regional computing-network coordinated scheduling in computing optical networks.

关键词

Keywords

references

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