Service relationship network modeling and service composition optimization algorithm based on hypergraph

JIANG Lingyun; YANG Xuewei

doi:10.11959/j.issn.2096-3750.2025.00393

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Service relationship network modeling and service composition optimization algorithm based on hypergraph

Theory and Technology | 更新时间：2026-01-04

- Service relationship network modeling and service composition optimization algorithm based on hypergraph
- Chinese Journal on Internet of Things Vol. 9, Issue 4, Pages: 159-171(2025)
- 作者机构：
  
  南京邮电大学通信与信息工程学院，江苏南京 210003
- 作者简介：
- 基金信息：
  
  The Jiangsu Provincial Key Research and Development Program(BE2020084-4)
- DOI：10.11959/j.issn.2096-3750.2025.00393
  CLC：
- Received：30 January 2024，
  
  Revised：2024-04-15，
  
  Published：10 December 2025
- 稿件说明：
移动端阅览
江凌云,杨雪薇.基于超图的服务关系网络建模及服务组合优化算法[J].物联网学报,2025,09(04):159-171.

JIANG Lingyun,YANG Xuewei.Service relationship network modeling and service composition optimization algorithm based on hypergraph[J].Chinese Journal on Internet of Things,2025,09(04):159-171.
江凌云,杨雪薇.基于超图的服务关系网络建模及服务组合优化算法[J].物联网学报,2025,09(04):159-171. DOI： 10.11959/j.issn.2096-3750.2025.00393.

JIANG Lingyun,YANG Xuewei.Service relationship network modeling and service composition optimization algorithm based on hypergraph[J].Chinese Journal on Internet of Things,2025,09(04):159-171. DOI： 10.11959/j.issn.2096-3750.2025.00393.

摘要

随着移动网络、云服务等技术的快速发展，物联网环境下的服务数量逐渐增多，类型逐渐多样，服务间的相关性更加复杂。这种相关性会影响服务的服务质量（QoS

quality of service）性能，因此在服务组合过程中，考虑服务间的相关性是非常必要的。针对此问题，使用意图和上下文对服务进行建模，通过构建超图对服务关系网络进行描述，利用超边来表示聚类的服务集和服务间的相关性。在此基础上，采用了第三代非支配排序遗传算法（non-dominated sorting genetic algorithm Ⅲ

NSGA-Ⅲ），考虑超边表示的服务间相关性对QoS性能的影响，完成服务组合。实验证明，超图模型可以很好地描述服务及服务间的相关性，并提高多目标优化算法求解得到的服务组合方案的QoS性能。

Abstract

With the rapid development of mobile network

cloud services and other technologies

the number of services in the Internet of Things environment is gradually increasing

the types are gradually diverse

and the correlation between the services is more complex. This correlation will affect the quality of service(QoS) performance of services

so it is necessary to consider the correlation between services in the process of service composition. In order to solve this problem

services were modeled by the intention and the context. The service relationship network was described by constructing the hypergraph. The set of clustered services and the correlation between the services are represented by hyperedges. On this basis

the NSGA-Ⅲ multi-objective optimization algorithm is used to complete the service composition

which covers the influence of the correlation between the services represented by hyperedges on QoS performance. The experiment proves that the hypergraph model can describe the service and the correlation between the services well

and improve the QoS quality of the service combination solution solved by the multi-objective optimization algorithm.

关键词

Keywords

references

TAHERKORDI A , ELIASSEN F . Scalable modeling of cloud-based IoT services for smart cities [C ] // Proceedings of the 2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops) . Piscataway : IEEE Press , 2016 : 1 - 6 .

王久超 , 赵卓峰 . 基于实体-数据的物联网服务建模 [J ] . 计算机系统应用 , 2023 , 32 ( 6 ): 70 - 79 .

WANG J C , ZHAO Z F . Entity-data-based modeling for Internet of Things services [J ] . Computer Systems and Applications , 2023 , 32 ( 6 ): 70 - 79 .

JIN H , YAO X F , CHEN Y . Correlation-aware QoS modeling and manufacturing cloud service composition [J ] . Journal of Intelligent Manufacturing , 2017 , 28 ( 8 ): 1947 - 1960 .

HÄSTBACKA D , HALME J , BARNA L , et al . Dynamic edge and cloud service integration for industrial IoT and production monitoring applications of industrial cyber-physical systems [J ] . IEEE Transactions on Industrial Informatics , 2022 , 18 ( 1 ): 498 - 508 .

张晶 , 徐鼎 , 刘旭 , 等 . 物联网与智能制造 [M ] . 北京 : 化学工业出版社 , 2019

ZHANH J , XU D , LIU X , et al . Internet of things and intelligent manufacturing [M ] . Beijing : Chemical Industry Press , 2019 .

齐明皓 . IoT服务组合建模及工具 [D ] . 北京 : 北方工业大学 , 2023 .

QI M H . IoT service combination modeling methods and tools [D ] . Beijing : North China University of Technology , 2023 .

BAEK J , LEE C . Hypergraph based multi-agents representation learning for similarity analysis [C ] // Proceedings of the 2021 21st International Conference on Control, Automation and Systems (ICCAS) . Piscataway : IEEE Press , 2021 : 1686 - 1689 .

WU L , HE M G , HAN Y Y . Hypergraph clustering-based cloud manufacturing service management method [C ] // Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design (CSCWD) . Piscataway : IEEE Press , 2014 : 220 - 225 .

NAGHAVIPOUR H , SOON T K , IDRISMohd Yamani Idna Bin , et al . Hybrid metaheuristics for QoS-aware service composition: a systematic mapping study [J ] . IEEE Access , 2021 , 10 : 12678 - 12701 .

MIN X Y , XU X F , LIU Z Z , et al . An approach to resource and QoS-aware services optimal composition in the big service and Internet of Things [J ] . IEEE Access , 2018 , 6 : 39895 - 39906 .

PERERA C , ZASLAVSKY A , LIU C H , et al . Sensor search techniques for sensing as a service architecture for the Internet of Things [J ] . IEEE Sensors Journal , 2014 , 14 ( 2 ): 406 - 420 .

刘星宇 , 江凌云 . 基于意图的物联网服务描述与发现 [J ] . 计算机应用研究 , 2022 , 39 ( 9 ): 2731 - 2737, 2756 .

LIU X Y , JIANG L Y . Intent-based IoT service description and discovery [J ] . Application Research of Computers , 2022 , 39 ( 9 ): 2731 - 2737, 2756 .

BASU S , CASATI F , DANIEL F . Toward web service dependency discovery for SOA management [C ] // Proceedings of the 2008 IEEE International Conference on Services Computing . Piscataway : IEEE Press , 2008 : 422 - 429 .

ROMANO D , PINZGER M , BOUWERS E . Extracting dynamic dependencies between web services using vector clocks [C ] // Proceedings of the 2011 IEEE International Conference on Service-Oriented Computing and Applications (SOCA) . Piscataway : IEEE Press , 2011 : 1 - 8 .

KANG G S , LIU J X , TANG M D , et al . Web service selection algorithm based on principal component analysis [J ] . Journal of Electronics (China) , 2013 , 30 ( 2 ): 204 - 212 .

DENG S G , WU H Y , HU D N , et al . Service selection for composition with QoS correlations [J ] . IEEE Transactions on Services Computing , 2016 , 9 ( 2 ): 291 - 303 .

MISHRA S K , HARATY R A , DEBNATH N C , et al . A hypergraph coloring based modelling of service oriented system [C ] // Proceedings of the 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) . Piscataway : IEEE Press , 2019 : 1349 - 1350 .

WU L , YANG Z , LIU S J , et al . An approach to web service organization based on hypergraph clustering [C ] // Proceedings of the 2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design (CSCWD) . Piscataway : IEEE Press , 2018 : 87 - 91 .

ZHANG L Y , GUO J F , LI Y , et al . Construction and embedding representation of relational aggregation hypergraphs in cyber-physical systems [J ] . IEEE Systems Journal , 2023 , 17 ( 4 ): 5216 - 5227 .

HAYTAMY S , OMARA F . Enhanced QoS-based service composition approach in multi-cloud environment [C ] // Proceedings of the 2020 International Conference on Innovative Trends in Communication and Computer Engineering (ITCE) . Piscataway : IEEE Press , 2020 : 33 - 38 .

KASHYAP N , KUMARI A C , CHHIKARA R . Multi-objective Optimization using NSGA II for service composition in IoT [J ] . Procedia Computer Science , 2020 , 167 : 1928 - 1933 .

范国栋 , 祝铭 , 李静 , 等 . 基于FAHP与规划图融合的Web服务组合方法 [J ] . 计算机科学 , 2020 , 47 ( 1 ): 270 - 275 .

FAN G D , ZHU M , LI J , et al . Web service composition by combining FAHP and graphplan [J ] . Computer Science , 2020 , 47 ( 1 ): 270 - 275 .

HUO Y , QIU P , ZHAI J Y , et al . Multi-objective service composition model based on cost-effective optimization [J ] . Applied Intelligence , 2018 , 48 ( 3 ): 651 - 669 .

LIU X Y , JIANG L Y . Service composition in Internet of vehicle environment using multi-objective Harris hawk optimization algorithm [C ] // Proceedings of the 2022 IEEE 8th International Conference on Computer and Communications (ICCC) . Piscataway : IEEE Press , 2022 : 852 - 861 .

栾宁 , 熊轲 , 张煜 , 等 . 6G: 典型应用、关键技术与面临挑战 [J ] . 物联网学报 , 2022 , 6 ( 1 ): 29 - 43 .

LUAN N , XIONG K , ZHANG Y , et al . 6G: typical applications, key technologies and challenges [J ] . Chinese Journal on Internet of Things , 2022 , 6 ( 1 ): 29 - 43 .

AVRAMIDIS I I , TAKIS-DEFTERAIOS G . Flexicurity: some thoughts about a different smart grid of the future [J ] . IEEE Transactions on Smart Grid , 2023 , 14 ( 2 ): 1333 - 1336 . .

R A B , KADAM A S , KULKARNI A , et al . IoT based smart water meter for water management [C ] // Proceedings of the 2023 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE) . Piscataway : IEEE Press , 2023 : 674 - 678 .

NEIAT A G , BOUGUETTAYA A , BAHUTAIR M . A deep reinforcement learning approach for composing moving IoT services [J ] . IEEE Transactions on Services Computing , 2022 , 15 ( 5 ): 2538 - 2550 .

LI D W , YE D Y , GAO N , et al . Service selection with QoS correlations in distributed service-based systems [J ] . IEEE Access , 2019 , 7 : 88718 - 88732 .

YANG D J , HE D . Web service clustering method based on word vector and biterm topic model [C ] // Proceedings of the 2021 IEEE 6th International Conference on Cloud Computing and Big Data Analytics (ICCCBDA) . Piscataway : IEEE Press , 2021 : 299 - 304 .

蒋伟进 , 周文颖 , 李恩 , 等 . 基于区块链技术的云制造服务架构及共识算法研究 [J ] . 物联网学报 , 2023 , 7 ( 1 ): 159 - 173 .

JIANG W J , ZHOU W Y , LI E , et al . Research on cloud manufacturing service architecture and consensus algorithm based on blockchain technology [J ] . Chinese Journal on Internet of Things , 2023 , 7 ( 1 ): 159 - 173 .

SINGH M , BARANWAL G . Quality of service (QoS) in Internet of Things [C ] // Proceedings of the 2018 3rd International Conference on Internet of Things: Smart Innovation and Usages (IoT-SIU) . Piscataway : IEEE Press , 2018 : 1 - 6 .

徐雪敏 , 张秀国 , 肖媛元 , 等 . 基于优化的灰狼算法的大规模Web服务组合 [J ] . 计算机应用 , 2022 , 42 ( 10 ): 3162 - 3169 .

XU X M , ZHANG X G , XIAO Y Y , et al . Large-scale Web service composition based on optimized grey wolf optimizer [J ] . Journal of Computer Applications , 2022 , 42 ( 10 ): 3162 - 3169 .

GUO K , LI J J , NIU M Q . Multi-agent interests service composition optimization in cloud manufacturing environment [J ] . IEEE Access , 2023 , 11 : 53760 - 53771 .

BI X X , YU D , LIU J S , et al . A preference-based multi-objective algorithm for optimal service composition selection in cloud manufacturing [J ] . International Journal of Computer Integrated Manufacturing , 2020 , 33 ( 8 ): 751 - 768 .

DEB K , JAIN H . An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints [J ] . IEEE Transactions on Evolutionary Computation , 2014 , 18 ( 4 ): 577 - 601 .

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