面向边缘端工业微服务部署的多目标白鲨优化算法

李孝斌; 苟堃耀; 尹超

doi:10.7652/xjtuxb202508001

您当前的位置：

首页 >

文章列表页 >

面向边缘端工业微服务部署的多目标白鲨优化算法

专题　工业互联网与制造服务 | 更新时间：2025-07-30

- 面向边缘端工业微服务部署的多目标白鲨优化算法
- Multi-Objective White Shark Optimizer for Edge-Side Industrial Microservice Deployment
- 西安交通大学学报 2025年59卷第8期页码：1-10
- 作者机构：
  
  重庆大学绿色智能制造研究所， 400044，重庆
- 作者简介：
  
  李孝斌（1987—），男，副教授，博士生导师。
- 基金信息：
  
  国家重点研发计划资助项目(2022YFB3305703);国家自然科学基金资助项目(52075060);重庆市科技创新重大研发项目(CSTB2024TIAD-STX0029)
- DOI：10.7652/xjtuxb202508001
  中图分类号： TP277
- 收稿：2025-01-06，
  
  网络首发：2025-04-15，
  
  纸质出版：2025-08-10
- 稿件说明：
移动端阅览
李孝斌, 苟堃耀, 尹超. 面向边缘端工业微服务部署的多目标白鲨优化算法[J]. 西安交通大学学报, 2025,59(8):1-10.

LI Xiaobin, GOU Kunyao, YIN Chao. Multi-Objective White Shark Optimizer for Edge-Side Industrial Microservice Deployment[J]. Journal of Xi’an Jiaotong University, 2025, 59(8): 1-10.
李孝斌, 苟堃耀, 尹超. 面向边缘端工业微服务部署的多目标白鲨优化算法[J]. 西安交通大学学报, 2025,59(8):1-10. DOI： 10.7652/xjtuxb202508001.

LI Xiaobin, GOU Kunyao, YIN Chao. Multi-Objective White Shark Optimizer for Edge-Side Industrial Microservice Deployment[J]. Journal of Xi’an Jiaotong University, 2025, 59(8): 1-10. DOI： 10.7652/xjtuxb202508001.

摘要

针对在有限资源的边缘节点上部署工业微服务时难以兼顾节点的资源利用和负载均衡状况的问题，提出了一种改进型多目标白鲨优化算法。考虑工业微服务部署时边缘节点资源利用和负载状况的协同优化问题，建立了一个以边缘节点计算资源余量、服务通信能耗、负载均衡状况和存储资源余量为指标的多目标优化模型；针对该模型的求解，从初始种群质量、收敛速度、跳出局部最优能力以及优质解的保留4个方面，分别引入了混沌映射初始化、自适应权重因子、差分进化算子以及精英保留策略对多目标白鲨优化算法进行改进。模型求解实验结果表明，相较于原始多目标白鲨优化算法，改进型多目标白鲨优化算法在上述4个指标上分别优化了13.8%、37.1%、63.9%、47.4%，相较于二代遗传算法则分别优化了63.2%、53.2%、39.1%、63.6%，且所提算法收敛速度更快。

Abstract

To address the challenge of balancing resource utilization and load balancing in edge nodes with limited resources during industrial microservice deployment

an improved multi-objective white shark optimizer (IMOWSO) is proposed. Considering the co-optimization of resource utilization and load conditions in edge nodes during industrial microservice deployment

a multi-objective optimization model is established with four key metrics: computational resource margin of edge nodes

service communication energy consumption

load balancing status

and storage resource margin. To solve this model

the improved algorithm enhances the original multi-objective white shark optimizer (MOWSO) in four aspects: initial population quality

convergence speed

ability to escape local optima

and preservation of high-quality solutions. Specifically

chaotic mapping initialization

adaptive weight factors

differential evolution operators

and an elite retention strategy are introduced. Experimental results demonstrate that compared to the original MOWSO

the proposed IMOWSO achieves optimizations of 13.8%

37.1%

63.9%

and 47.4% in the four metrics

respectively. Furthermore

when compared to the second-generation genetic algorithm

the improvements reach 63.2%

53.2%

39.1%

and 63.6%

respectively

while also exhibiting faster convergence speed.

关键词

Keywords

references

杨鹏 . 工业互联网平台微服务参考框架标准解读 [J ] . 信息技术与标准化 , 2023 ( 10 ): 14 - 18 .

YANG Peng . Interpretation of industrial internet platforms mircoservices reference framework [J ] . Information Technology & Standardization , 2023 ( 10 ): 14 - 18 .

国家市场监督管理总局 , 国家标准化管理委员会 . 工业互联网平台　微服务参考框架：GB/T 42568—2023 [S ] . 北京 : 中国标准出版社 , 2023 .

BIGHETI J A , FERNANDES M M , GODOY E P . Control as a service: a microservice approach to industry 4.0 [C ] // 2019 Ⅱ Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0 & IoT) . Piscataway, NJ, USA : IEEE , 2019 : 438 - 443 .

STEIBER A , ALÄNGE S , GHOSH S , et al . Digital transformation of industrial firms: an innovation diffusion perspective [J ] . European Journal of Innovation Management , 2021 , 24 ( 3 ): 799 - 819 .

KULAWIAK K E . Manufacturing the platform economy. An exploratory case study of MindSphere, the industrial digital platform from Siemens [D ] . Oslo, Norway : University of Oslo , 2021 .

JUNG S , FERBER S , CRAMER I , et al . Bosch IoT suite: exploiting the potential of smart connected products [M ] // GASSMANN O , FERRANDINA F . Connected Business: Create Value in a Networked Economy . Cham : Springer International Publishing , 2021 : 267 - 282 .

KOREN Y , HU S J , WEBER T W . Impact of manufacturing system configuration on performance [J ] . CIRP Annals , 1998 , 47 ( 1 ): 369 - 372 .

BLINOWSKI G , OJDOWSKA A , PRZYBYŁEK A . Monolithic vs. Microservice architecture: a performance and scalability evaluation [J ] . IEEE Access , 2022 , 10 : 20357 - 20374 .

ZHANG He , LI Shanshan , JIA Zijia , et al . Microservice architecture in reality: an industrial inquiry [C ] // 2019 IEEE International Conference on Software Architecture (ICSA) . Piscataway, NJ, USA : IEEE , 2019 : 51 - 60 .

李亚杰 , 李昭楠 . 面向微服务的制造执行系统关键技术研究 [J ] . 制造技术与机床 , 2023 ( 9 ): 95 - 101 .

LI Yajie , LI Zhaonan . Research on key technologies of microservice based manufacturing execution system [J ] . Manufacturing Technology & Machine Tool , 2023 ( 9 ): 95 - 101 .

FILIP I D , POP F , SERBANESCU C , et al . Microservices scheduling model over heterogeneous cloud-edge environments as support for IoT applications [J ] . IEEE Internet of Things Journal , 2018 , 5 ( 4 ): 2672 - 2681 .

MA Wubin , WANG Rui , GU Yuanlin , et al . Multi-objective microservice deployment optimization via a knowledge-driven evolutionary algorithm [J ] . Complex & Intelligent Systems , 2021 , 7 ( 3 ): 1153 - 1171 .

FAN Guisheng , CHEN Liang , YU Huiqun , et al . Multi-objective optimization of container-based microservice scheduling in edge computing [J ] . Computer Science and Information Systems , 2021 , 18 ( 1 ): 23 - 42 .

LÜ Wenkai , WANG Quan , YANG Pengfei , et al . Microservice deployment in edge computing based on deep Q learning [J ] . IEEE Transactions on Parallel and Distributed Systems , 2022 , 33 ( 11 ): 2968 - 2978 .

CHEN Lulu , XU Yangchuan , LU Zhihui , et al . IoT microservice deployment in edge-cloud hybrid environment using reinforcement learning [J ] . IEEE Internet of Things Journal , 2021 , 8 ( 16 ): 12610 - 12622 .

孙梦宇 , 林睿 . 基于日志可观测的云：边协同微服务部署优化 [J ] . 电信科学 , 2023 , 39 ( 12 ): 122 - 132 .

SUN Mengyu , LIN Rui . Cloud-edge collaboration service deployment optimization based on log observability [J ] . Telecommunications Science , 2023 , 39 ( 12 ): 122 - 132 .

BRAIK M , HAMMOURI A , ATWAN J , et al . White shark optimizer: a novel bio-inspired meta-heuristic algorithm for global optimization problems [J ] . Knowledge-Based Systems , 2022 , 243 : 108457 .

CAPONETTO R , FORTUNA L , FAZZINO S , et al . Chaotic sequences to improve the performance of evolutionary algorithms [J ] . IEEE Transactions on Evolutionary Computation , 2003 , 7 ( 3 ): 289 - 304 .

WU Guocheng , BALEANU D . Discrete fractional logistic map and its chaos [J ] . Nonlinear Dynamics , 2014 , 75 ( 1 ): 283 - 287 .

YOUSRI D , ABDELATY A M , SAID L A , et al . Chaotic flower pollination and grey wolf algorithms for parameter extraction of bio-impedance models [J ] . Applied Soft Computing , 2019 , 75 : 750 - 774 .

YOU Zhiyu , CHEN Weirong , HE Guojun , et al . Adaptive weight particle swarm optimization algorithm with constriction factor [C ] // 2010 International Conference of Information Science and Management Engineering . Piscataway, NJ, USA : IEEE , 2010 : 245 - 248 .

MA Haiping , ZHANG Yajing , SUN Shengyi , et al . A comprehensive survey on NSGA-Ⅱ for multi-objective optimization and applications [J ] . Artificial Intelligence Review , 2023 , 56 ( 12 ): 15217 - 15270 .

CHIN V J , SALAM Z , ISHAQUE K . An accurate and fast computational algorithm for the two-diode model of PV module based on a hybrid method [J ] . IEEE Transactions on Industrial Electronics , 2017 , 64 ( 8 ): 6212 - 6222 .

DEB K , PRATAP A , AGARWAL S , et al . A fast and elitist multiobjective genetic algorithm: NSGA-Ⅱ [J ] . IEEE Transactions on Evolutionary Computation , 2002 , 6 ( 2 ): 182 - 197 .

ZHU Jianyong , LU Bin , YU Xiaoqiang , et al . An approach to workload generation for cloud benchmarking: a view from Alibaba trace [C ] // 2023 IEEE 15th International Symposium on Autonomous Decentralized System (ISADS) . Piscataway, NJ, USA : IEEE , 2023 : 1 - 8 .

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

采用改进多目标粒子群算法的海岛综合能源系统优化调度

带锥形孔的矩阵冷却通道流动换热多目标优化

大型可展开网状天线展开过程仿真建模与竖向索预拉力优化调控

采用改进多目标粒子群算法的海岛综合能源系统优化调度

网络生存适应性的多目标评估