Cost-Minimized Cross-Regional Traffic Scheduling Algorithm in Computing Power Networks

ZHANG Xu; GU Mengyao; NING Meng; FENG Chuan; GONG Xiaoxue; GUO Lei

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

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Cost-Minimized Cross-Regional Traffic Scheduling Algorithm in Computing Power Networks

更新时间：2026-05-11

- Cost-Minimized Cross-Regional Traffic Scheduling Algorithm in Computing Power Networks
- Telecommunications Science (2026)
- 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：
- 基金信息：
  
  The National Natural Science Foundation of China(62571078;62331017;62501097);Natural Science Foundation of Chongqing(CSTB2025NSCQ-GPX1283);Chongqing Municipal Education Commission(KJQN202400621)
- DOI：10.11959/j.issn.1000-0801.DXKX260166
  CLC： TP913
- Received：11 March 2026，
  
  Revised：2026-04-05，
  
  Accepted：11 May 2026，
- 稿件说明：
移动端阅览
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：

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.

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Keywords

references

Ren P , Qiao X , Huang Y , et al . Edge AR X5: An edge-assisted multi-user collaborative framework for mobile web augmented reality in 5G and beyond [J ] . IEEE Transactions on Cloud Computing , 2020 , 10 ( 4 ): 2521 - 2537 .

Yang Z , Cui Y , Wang X , et al . Towards maximal service profit in geo-distributed clouds [C ] // 2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS) , July 7-10, 2019 , Dallas, TX, USA . Los Alamitos : IEEE Computer Society , 2019 : 442 - 452 .

Luo L , Zhao G , Xu H , et al . Achieving cost optimization for tenant task placement in geo-distributed clouds [J ] . IEEE/ACM Transactions on Networking , 2023 , 32 ( 2 ): 1391 - 1406 .

Li H , Gao Y , Zhu L , et al . Cost-aware scheduling for streaming applications in geographically distributed heterogeneous cloud [J ] . Future Generation Computer Systems , 2026 , 175 : 1 - 12 .

Zhou S , Zhou M , Wu Z , et al . Energy-aware coordinated operation strategy of geographically distributed data centers [J ] . International Journal of Electrical Power & Energy Systems , 2024 , 159 : 1591 - 1604 .

Cao Y , Cao F , Wang Y , et al . Managing data center cluster as non-wire alternative: A case in balancing market [J ] . Applied Energy , 2024 , 360 : 1 - 15 .

Khatiri A , Mirjalily G , Luo Z Q . Balanced resource allocation for VNF service chain provisioning in inter-datacenter elastic optical networks [J ] . Computer Networks , 2022 , 203 : 1 - 12 .

Batham D , Thakare V V . An improved cost function-based class of service provisioning scheme for elastic optical networks [J ] . Computer Networks , 2024 , 243 : 1 - 14 .

Jaber M B S , Shaaban O Y . Deep reinforcement learning for dynamic routing, modulation, and spectrum assignment in elastic optical networks [J ] . Journal of Communications , 2025 , 20 ( 4 ): 446 - 456 .

Carvalho R , Pinheiro D , Dinarte H , et al . Hybrid Routing and Spectrum Allocation in Elastic Optical Networks by Machine Learning and Topological Metrics [J ] . Optics , 2025 , 6 ( 4 ): 57 .

Hogade N , Pasricha S , Siegel H J . Energy and Network Aware Workload Management for Geographically Distributed Data Centers [J ] . IEEE Trans. Sustain. Computing., 2022 , 7 ( 2 ): 400 - 413 .

Xie T , Li C , Hao N , et al . Multi-objective optimization of data deployment and scheduling based on the minimum cost in geo-distributed cloud [J ] . Computer Communications , 2022 , 185 ( 1 ): 142 - 158 .

Adnan A H , Al-Muqarm A M A , Abosinnee A S . Network-Aware Optimization for Efficient Data Placement in Geo-Distributed Cloud Systems: AH Adhab et al [J ] . Journal of Grid Computing , 2025 , 23 ( 4 ): 30 .

Xue L , Wang J , Li H , et al . Online energy conservation scheduling for geo-distributed data centers with hybrid data-driven and knowledge-driven approach [J ] . Energy , 2025 , 322 : 1 - 14 .

Wang S , Zhang H , Wu T , et al . Electricity cost minimization for multi-workflow allocation in geo-distributed data centers [J ] . IEEE Transactions on Services Computing , 2025 , 18 ( 3 ): 1397 - 1411 .

Guillen-Perez A , Naug A , Gundecha V , et al . DCcluster-opt: Benchmarking dynamic multi-objective optimization for geo-distributed data center workloads [EB/OL ] . ( 2025-11-01 )[ 2026-03-31 ] . https://arxiv.org/abs/2511.00117 https://arxiv.org/abs/2511.00117 .

Ali A , Özkasap Ö . Spatial and thermal aware methods for efficient workload management in distributed data centers [J ] . Future Generation Computer Systems , 2024 , 153 : 360 - 374 .

H. Xu and B. Li . Cost efficient datacenter selection for cloud services [C ] // 2012 1st IEEE International Conference on Communications in China (ICCC) , August 15-17, 2012 , Beijing, China . Piscataway : IEEE , 2012 : 51 - 56 .

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