高性能网络数字孪生仿真引擎研究

石鸿伟; 倪中阳; 陆干沂; 黄韬

doi:10.11959/j.issn.2096-3750.2026.00505

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高性能网络数字孪生仿真引擎研究

理论与技术 | 更新时间：2026-04-16

- 高性能网络数字孪生仿真引擎研究
- Research on high-performance network digital twin simulation engine
- 物联网学报 2026年10卷第1期页码：161-171
- 作者机构：
  
  1.东南大学网络空间安全学院，江苏南京 211189
  2.紫金山实验室，江苏南京 211111
  3.北京邮电大学网络与交换技术全国重点实验室，北京 100876
- 作者简介：
  
  [ "石鸿伟（1982‒ ），男，东南大学网络空间安全学院博士生、紫金山实验室高级工程师，主要研究方向为未来网络体系架构、软件定义网络、网络智能控制。" ]
  [ "倪中阳（1987‒ ），男，博士，紫金山实验室研究员，主要研究方向为网络管控、数字孪生。" ]
  [ "陆干沂（1991‒ ），男，博士，紫金山实验室研究员，主要研究方向为网络编排、数字孪生。" ]
  [ "黄韬（1980‒ ），男，博士，北京邮电大学网络与交换技术全国重点实验室教授、博士生导师，主要研究方向为路由与交换、软件定义网络、内容分发网络、确定性网络、算力网络。" ]
- 基金信息：
  
  国家重点研发计划项目(2022YFB2702303)
- DOI：10.11959/j.issn.2096-3750.2026.00505
  中图分类号： TP393
- 收稿：2025-05-23，
  
  修回：2025-06-18，
  
  录用：2025-07-18，
  
  纸质出版：2026-03-30
- 稿件说明：
移动端阅览
石鸿伟,倪中阳,陆干沂等.高性能网络数字孪生仿真引擎研究[J].物联网学报,2026,10(01):161-171.

Shi Hongwei,Ni Zhongyang,Lu Ganyi,et al.Research on high-performance network digital twin simulation engine[J].Chinese Journal on Internet of Things,2026,10(01):161-171.
石鸿伟,倪中阳,陆干沂等.高性能网络数字孪生仿真引擎研究[J].物联网学报,2026,10(01):161-171. DOI： 10.11959/j.issn.2096-3750.2026.00505.

Shi Hongwei,Ni Zhongyang,Lu Ganyi,et al.Research on high-performance network digital twin simulation engine[J].Chinese Journal on Internet of Things,2026,10(01):161-171. DOI： 10.11959/j.issn.2096-3750.2026.00505.

摘要

网络数字孪生技术在提升IP承载网仿真测试的运维效率与决策精度方面具有重要作用，然而，当前仍面临仿真精度不高与仿真性能不足等问题。基于PNetLab仿真平台，提出了一种高性能网络数字孪生仿真引擎——ePNetLab（extended PNetLab）。首先，对原有平台进行性能优化与功能扩展，改进接口响应机制，设计跨节点通信方案，提升拓扑构建效率并增强集群化组网能力。其次，设计并实现基于社区划分算法的拓扑动态构建方法，有效地降低了大规模仿真场景的构建时间与资源开销。最后，通过实验评估验证了所提方案的可行性与高效性。实验结果表明，ePNetLab在拓扑构建效率方面相较于原生PNetLab在最优条件下提升了82.9%；同时，所引入的社区划分算法在仿真效率、资源利用率与业务性能等方面较其他算法有较大提升。

Abstract

Network digital twin technology plays a significant role in improving the maintenance efficiency and decision-making accuracy of IP bearer network simulation and testing. However

it still faces challenges

such as low simulation accuracy and insufficient simulation performance. A high-performance network digital twin simulation engine

extended PNetLab (ePNetLab)

based on the PNetLab simulation platform was proposed. Firstly

the original platform was optimized in terms of performance and functionality. The interface response mechanism was improved

a cross-node communication scheme was designed

and the efficiency of topology construction was enhanced

along with the ability to form clustered networks. Secondly

a topology dynamic construction method based on community detection algorithms was designed and implemented

effectively reducing the construction time and resource overhead in the large-scale simulation scenarios. Finally

experimental evaluations were conducted to verify the feasibility and efficiency of the proposed solution. The experimental results show that ePNetLab improves the topology construction efficiency by 82.9% compared with the native PNetLab under the optimal conditions. Meanwhile

the community partitioning algorithm introduced greatly improves simulation efficiency

resource utilization

and business performance compared with the other algorithms.

关键词

Keywords

references

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