联邦边缘智能网络碳排放评估及优化

张鹏; 肖泳; 胡记伟; 廖亮; 吕建新; 白泽刚

doi:10.11959/j.issn.2096-3750.2024.00375

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联邦边缘智能网络碳排放评估及优化

理论与技术 | 更新时间：2024-06-05

- 联邦边缘智能网络碳排放评估及优化
- Evaluation and optimization of carbon emission for federal edge intelligence network
- 物联网学报 2024年8卷第1期页码：98-110
- 作者机构：
  
  1. 华中科技大学，湖北武汉 430074
  2. 烽火通信科技股份有限公司，湖北武汉 430074
  3. 鹏城实验室，广东深圳 518055
  4. 琶洲实验室（黄埔），广东广州 510555
  5. 武汉烽火技术服务有限公司，湖北武汉 430074
- 作者简介：
  
  [ "张鹏（1978‒ ），男，华中科技大学博士生、烽火通信科技股份有限公司高级工程师，主要研究方向为网络人工智能" ]
  [ "肖泳（1980‒ ），男，华中科技大学教授、IMT-2030 （6G）推进组网络智能方向副组长、5G联创行业应用开发实验室副主任，主要研究方向为网络人工智能、边缘计算、通信网络博弈理论等" ]
  [ "胡记伟（1985‒ ），男，武汉烽火技术服务有限公司项目总监、高级工程师，主要研究方向为智能网络运维、数字化转型" ]
  [ "廖亮（1976‒ ），男，烽火通信科技股份有限公司科技管理部副总经理、高级工程师，主要研究方向为数据通信、网络人工智能" ]
  [ "吕建新（1966‒ ），男，烽火通信科技股份有限公司技术委员会副主任、教授级高级工程师，主要研究方向为光纤通信技术与网络" ]
  [ "白泽刚（1975‒ ），男，烽火通信科技股份有限公司教授级高级工程师，主要研究方向为网络管理与控制系统、智能网络运维" ]
- 基金信息：
  
  国家自然科学基金项目;The National Natural Science Foundation of China(62071193);湖北省科技创新及人才服务专项;Hubei Province Science and Technology Innovation Talents and Service Program(2021EHB015);武汉市人工智能专项;The Key AI Program of Wuhan(2022010702040062);鹏城实验室重大攻关项目;Major project of Peng Cheng Laboratory(PCL2023AS1-2)
- DOI：10.11959/j.issn.2096-3750.2024.00375
  中图分类号： TG391
- 纸质出版日期：2024-03-30，
  
  网络出版日期：2024-03，
- 稿件说明：
移动端阅览
张鹏, 肖泳, 胡记伟, 等. 联邦边缘智能网络碳排放评估及优化[J]. 物联网学报, 2024,8(1):98-110.

PENG ZHANG, YONG XIAO, JIWEI HU, et al. Evaluation and optimization of carbon emission for federal edge intelligence network. [J]. Chinese journal on internet of things, 2024, 8(1): 98-110.
张鹏, 肖泳, 胡记伟, 等. 联邦边缘智能网络碳排放评估及优化[J]. 物联网学报, 2024,8(1):98-110. DOI： 10.11959/j.issn.2096-3750.2024.00375.

PENG ZHANG, YONG XIAO, JIWEI HU, et al. Evaluation and optimization of carbon emission for federal edge intelligence network. [J]. Chinese journal on internet of things, 2024, 8(1): 98-110. DOI： 10.11959/j.issn.2096-3750.2024.00375.

摘要

近年来，通信技术的持续演进导致通信网络的能耗显著增加。随着人工智能（AI

artificial intelligence）技术与算法在通信网络中的广泛应用和深度部署，未来6G智能通信网络架构和技术演进将对通信网络的节能减排带来更为严峻的挑战。基于边缘计算和分布式联邦学习的联邦边缘智能（FEI

federated edge intelligence）网络已被普遍认为是实现6G网络内生智能的关键路径之一。然而，如何评估和优化联邦边缘智能网络的综合碳排放量仍然是一大难题。为解决该问题，首先，提出了一种联邦边缘智能网络碳排放评估框架和方法。其次，基于该评估框架和方法提出3种联邦边缘智能网络碳排放优化方案，包括动态能量交易（DET

dynamic energy trading）、动态任务分配（DTA

dynamic task allocation）和动态能量交易与任务分配（DETA

dynamic energy trading and task allocation）。最后，通过自行搭建的真实硬件平台，并利用真实世界的碳强度数据集进行联邦边缘智能网络生命周期碳排放仿真。实验结果表明，3种优化方案均能在不同场景和约束条件下显著减少联邦边缘智能网络的碳排放，为下一代智能通信网络的可持续发展和实现绿色低碳6G网络提供了依据。

Abstract

In recent years

the continuous evolution of communication technology has led to a significant increase in energy consumption.With the widespread application and deep deployment of artificial intelligence (AI) technology and algorithms in telecommunication networks

the network architecture and technological evolution of network intelligent will pose even more severe challenges to the energy efficiency and emission reduction of future 6G.Federated edge intelligence (FEI)

based on edge computing and distributed federated machine learning

has been widely acknowledged as one of the key pathway for implementing network native intelligence.However

evaluating and optimizing the comprehensive carbon emissions of federated edge intelligence networks remains a significant challenge.To address this issue

a framework and a method for assessing the carbon emissions of federated edge intelligence networks were proposed.Subsequently

three carbon emission optimization schemes for FEI networks were presented

including dynamic energy trading (DET)

dynamic task allocation (DTA)

and dynamic energy trading and task allocation (DETA).Finally

by utilizing a simulation network built on real hardware and employing real-world carbon intensity datasets

FEI networks lifecycle carbon emission experiments were conducted.The experimental results demonstrate that all three optimization schemes significantly reduce the carbon emissions of FEI networks under different scenarios and constraints.This provides a basis for the sustainable development of next-generation intelligent communication networks and the realization of low-carbon 6G networks.

关键词

6G碳排放联邦边缘智能网络碳排放评估框架和方法动态能量交易与任务分配

Keywords

6Gcarbon emissionfederated edge intelligence networkcarbon emission assessment framework and methoddynamic energy trading and task allocation

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