Research on intelligent integrated collaborative scheduling of computing network brain and edge computing

An Ying; Yan Yaqi; Wang Dong; Wang Tao; Liu Shenyi

doi:10.11959/j.issn.1000-0801.DXKX250463

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Research on intelligent integrated collaborative scheduling of computing network brain and edge computing

Engineering and Application | 更新时间：2026-06-17

- Research on intelligent integrated collaborative scheduling of computing network brain and edge computing
- Telecommunications Science Vol. 42, Issue 5, Pages: 198-211(2026)
- 作者机构：
  
  1.中国铁塔股份有限公司，北京 100080
  2.中国移动集团设计院有限公司，北京 100080
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.DXKX250463
  CLC： TP393.0
- Received：21 July 2025，
  
  Revised：2025-11-27，
  
  Accepted：27 November 2025，
  
  Published：20 May 2026
- 稿件说明：
移动端阅览
安颖,闫亚旗,王东等.算网大脑与边缘计算的智能化协同调度研究[J].电信科学,2026,42(05):198-211.

An Ying,Yan Yaqi,Wang Dong,et al.Research on intelligent integrated collaborative scheduling of computing network brain and edge computing[J].Telecommunications Science,2026,42(05):198-211.
安颖,闫亚旗,王东等.算网大脑与边缘计算的智能化协同调度研究[J].电信科学,2026,42(05):198-211. DOI： 10.11959/j.issn.1000-0801.DXKX250463.

An Ying,Yan Yaqi,Wang Dong,et al.Research on intelligent integrated collaborative scheduling of computing network brain and edge computing[J].Telecommunications Science,2026,42(05):198-211. DOI： 10.11959/j.issn.1000-0801.DXKX250463.

摘要

在数字时代信息科技不断发展的进程中，以算力网络及边缘计算为核心的计算范式，已于诸多领域得到了应用与认可。通过整合异构异地的计算资源，算网大脑可实现高效的资源调度及任务分配。对算网大脑与边缘计算之间的协同方式展开了探索，剖析当前及新兴的技术手段，提出了独创性的算法体系，其具备主客观多要素指标、动态阈值及赋权、双尺度决策与三级资源调度五大特征。通过该算法的落地执行，可有效减少业务总时延，提升资源利用率，加强对业务可靠性的保障。

Abstract

Amid the ongoing advancement of information technology in the digital era

computing paradigms centered on computing power network and edge computing have been widely applied and recognized across numerous fields. By integrating heterogeneous and distributed computing resources

the computing network brain enables efficient resource scheduling and task allocation. The collaborative mechanisms between the computing network brain and edge computing were explored

both current and emerging technical approaches were examined

and an innovative algorithmic system was proposed. This system was characterized by five key features: multi-dimensional subjective and objective metrics

dynamic threshold adjustment and weighting

dual-scale decision-making

and intelligent hierarchical scheduling strategies. The implementation of this algorithm effectively reduces overall service latency

enhances resource utilization

and improves operational reliability.

关键词

Keywords

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