Service function chain orchestration mechanism on embedded DPU

Xing Ruopeng; Guo Shaoyong; Qiu Xuesong; Hao Jiakai; Li Yuting

doi:10.11959/j.issn.1000-436x.2026079

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Service function chain orchestration mechanism on embedded DPU

Papers | 更新时间：2026-05-07

- Service function chain orchestration mechanism on embedded DPU
- Journal on Communications Vol. 47, Issue 4, Pages: 13-28(2026)
- 作者机构：
  
  1.北京邮电大学网络与交换技术国家重点实验室，北京 100876
  2.国网北京市电力公司，北京 100031
- 作者简介：
- 基金信息：
  
  The National Key Research and Development Program of China(2024YFB3108204)
- DOI：10.11959/j.issn.1000-436x.2026079
  CLC： TP309
- Received：30 December 2025，
  
  Revised：2026-03-18，
  
  Accepted：19 March 2026，
  
  Published：20 April 2026
- 稿件说明：
移动端阅览
邢若鹏,郭少勇,邱雪松等.内嵌式数据处理单元的服务功能链编排机制[J].通信学报,2026,47(04):13-28.

Xing Ruopeng,Guo Shaoyong,Qiu Xuesong,et al.Service function chain orchestration mechanism on embedded DPU[J].Journal on Communications,2026,47(04):13-28.
邢若鹏,郭少勇,邱雪松等.内嵌式数据处理单元的服务功能链编排机制[J].通信学报,2026,47(04):13-28. DOI： 10.11959/j.issn.1000-436x.2026079.

Xing Ruopeng,Guo Shaoyong,Qiu Xuesong,et al.Service function chain orchestration mechanism on embedded DPU[J].Journal on Communications,2026,47(04):13-28. DOI： 10.11959/j.issn.1000-436x.2026079.

摘要

针对云-边-端场景下大规模、多元化业务应用对高灵活性和高性能网络服务的需求，提出一种内嵌式数据处理单元的服务功能链编排机制。首先，提出了一种内嵌式数据处理单元的服务功能链架构，以解决传统服务功能链无法兼顾灵活性和性能的问题。其次，针对该架构下服务功能需求异构资源的特点，提出综合考虑资源占用率、硬件加速器利用率、端到端时延和部署响应时间的服务功能链部署问题。为解决该问题，设计了一种基于遗传粒子群优化算法的服务功能链部署方法，同时提出子链划分方法和相似请求合并方法，分别优化方法的计算时间和部署方法的平均响应时间。仿真结果表明，相较于对比方法，所提方法可以得出更优的服务功能链部署策略，且具备较快的决策速度。

Abstract

In response to the demand for high flexibility and high-performance network services for large-scale and diversified business applications in cloud-edge-end scenarios

a service function chain orchestration mechanism on embedded data processing units was proposed. Firstly

an architecture of service function chain on embedded data processing units was proposed to address the issue of traditional service function chains being unable to balance high flexibility and high-speed processing. Secondly

in response to the heterogeneous resources requirement of service functions under this architecture

a service function chain deployment problem was formulated by comprehensively incorporating resource occupancy

hardware accelerator utilization

end-to-end latency

and deployment response time. To solve this problem

a service function chain deployment method based on the genetic particle swarm optimization algorithm was developed

and the process of dividing sub chains and merging similar requests was designed to improve the speed of the proposed method. Simulation results show that

compared with other methods

the proposed method provides better service function chain deployment decisions and has a faster decision-making speed.

关键词

Keywords

references

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