Key Technologies for Collaborative Inference in Edge Intelligence Computing

ZHANG Zhihan; ZHANG Tiankui; DANG Meimei; CHENG Weiqiang

doi:10.11959/j.issn.1000-0801.DXKX260099

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Key Technologies for Collaborative Inference in Edge Intelligence Computing

更新时间：2026-05-19

- Key Technologies for Collaborative Inference in Edge Intelligence Computing
- Telecommunications Science (2026)
- 作者机构：
  
  1.北京邮电大学信息与通信工程学院，北京 100876
  2.中国信息通信研究院技术与标准研究所，北京 100191
  3.中国移动通信有限公司研究院，北京 100053
- 作者简介：
- 基金信息：
  
  The National Natural Science Foundation of China(62371068);Education and Research Foundation of PCL - Technological Innovation Foundation of China Mobile(SQ2510300009)
- DOI：10.11959/j.issn.1000-0801.DXKX260099
  CLC： TP393
- Received：10 February 2026，
  
  Revised：2026-04-27，
  
  Accepted：18 May 2026，
- 稿件说明：
移动端阅览
ZHANG Zhihan, ZHANG Tiankui, DANG Meimei, et al. Key Technologies for Collaborative Inference in Edge Intelligence Computing[J/OL]. Telecommunications Science, 2026.
DOI：

ZHANG Zhihan, ZHANG Tiankui, DANG Meimei, et al. Key Technologies for Collaborative Inference in Edge Intelligence Computing[J/OL]. Telecommunications Science, 2026. DOI： 10.11959/j.issn.1000-0801.DXKX260099.

摘要

本文剖析了边缘智能计算技术在边缘计算网络中的实现逻辑，并围绕边缘协同推理任务的推理时延与推理质量需求，分别从判别式与生成式人工智能模型的特性出发，系统分析了边缘协同推理关键技术的实现方法。在此基础上，提出了一种面向生成式人工智能模型的边端协同推理系统设计实例，验证了其在推理时延与推理质量方面的优势，为边缘智能计算在边缘计算网络中高效部署与应用实现提供了可行的技术方案。

Abstract

This paper provided an in-depth analysis of the implementation logic of edge collaborative intelligent computing technologies in edge computing networks. Focusing on the latency and inference quality requirements of edge collaborative inference tasks

it systematically analyzed the characteristics of discriminative and generative artificial intelligence models

respectively

and summarized the core implementation approaches of key technologies for edge collaborative inference. On this basis

a device–edge collaborative inference system design tailored for generative artificial intelligence models was proposed

and its advantages in terms of inference latency and inference quality were validated. The proposed approach provided a technical reference for the efficient deployment and practical implementation of edge collaborative intelligent computing technologies.

关键词

Keywords

references

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