Abstract
A web application contains diverse functions where a distinct collection of candidate web services exists on the web to perform each function. Each web service in a collection performs the same function but with a different quality of service (QoS). When a web service with a specific QoS is selected from each collection for each application function, a composition of web services is created. Therefore, many compositions can be made for a web application so that their near-optimal selection is a matter of concern. Two issues exist with the selection: (1) how to compute the composition’s QoS and (2) how to select the compositions based on their QoSs, which is an NP-hard problem. This paper aims to address resolving these issues. To show the effectiveness of our proposed method, we applied it to four web-based service-oriented applications with a dataset of 2507 web services in collections. Then, regarding a few performance indicators, we evaluated the solutions obtained using our method against those obtained using six related studies. Moreover, we exploited statistical tests to show the generality of the results in terms of the QoSs. The performance indicator of the coverage ratio showed our solutions dominate 79% of related studies’ solutions on average.














Similar content being viewed by others
Data availability
The data are available from the site links stated in the paper text.
References
Xu J et al (2023) Business-process-driven service composition in a hybrid cloud environment. Inform Syst Front. https://doi.org/10.1007/s10796-023-10436-z
Gabrel V et al (2018) QoS-aware automatic syntactic service composition problem: complexity and resolution. Futur Gener Comput Syst 80:311–321
Dahan F (2023) Neighborhood search based improved bat algorithm for web service composition. Comput Syst Sci Eng 45(2):1343
Ramírez A et al (2017) Evolutionary composition of QoS-aware web services: a many-objective perspective. Expert Syst Appl 72:357–370
Mirjalili S et al (2016) Multi-objective grey wolf optimizer: a novel algorithm for multi-criterion optimization. Expert Syst Appl 47:106–119
Yin L, Sun Z (2022) Distributed multi-objective grey wolf optimizer for distributed multi-objective economic dispatch of multi-area interconnected power systems. Appl Soft Comput 117:108345
Makhadmeh SN et al (2022) Recent advances in multi-objective grey wolf optimizer, its versions and applications. Neural Comput Appl 34(22):19723–19749
Alkhraisat H et al (2023) Size optimization of truss structures using improved grey wolf optimizer. IEEE Access 11:13383–13397
Hu J et al (2023) Microservice combination optimisation based on improved gray wolf algorithm. Connect Sci 35(1):2175791
Li JZ et al. Application of SPEA2 algorithm in Web services selection. In 2010 IEEE Youth Conference on Information, Computing and Telecommunications. 2010. IEEE.
Kashyap N, Kumari AC, Chhikara R (2020) Multi-objective optimization using NSGA II for service composition in IoT. Procedia Comput Sci 167:1928–1933
Yang Y et al (2020) An enhanced multi-objective grey wolf optimizer for service composition in cloud manufacturing. Appl Soft Comput 87:106003
Wang R, Lu J (2022) QoS-aware service discovery and selection management for cloud-edge computing using a hybrid meta-heuristic algorithm in IoT. Wireless Pers Commun 126(3):2269–2282
Jin H et al (2022) Eagle strategy using uniform mutation and modified whale optimization algorithm for QoS-aware cloud service composition. Appl Soft Comput 114:108053
Dahan F (2022) An improved whale optimization algorithm for web service composition. Axioms 11(12):725
Dahan F, Alwabel A (2023) Artificial bee colony with cuckoo search for solving service composition. Intel Automation Soft Comput 35(3):3385
Azouz Y, Boughaci D (2022) Multi-objective memetic approach for the optimal web services composition. Expert Syst 40:e13084
Sangaiah AK et al (2020) A novel quality-of-service-aware web services composition using biogeography-based optimization algorithm. Soft Comput 24:8125–8137
Wang C et al (2021) Memetic EDA-based approaches to QoS-aware fully automated semantic web service composition. IEEE Trans Evol Comput 26(3):570–584
Jalal S, Yadav DK (2021) A multiobjective discrete grey wolf optimization approach for transactional and QoS-driven web services composition. Appl Artif Intell 35(15):1646–1684
Li J et al (2022) A novel and efficient salp swarm algorithm for large-scale QoS-aware service composition selection. Computing 104(9):2031–2051
Liang H et al (2021) Parallel optimization of QoS-aware big service processes with discovery of skyline services. Futur Gener Comput Syst 125:496–514
Cherifi A et al (2023) A parallel approach for user-centered QoS-aware services composition in the internet of things. Eng Appl Artif Intell 123:106277
Dahan F et al (2021) An enhanced ant colony optimization based algorithm to solve QoS-aware web service composition. Ieee Access 9:34098–34111
García-Domínguez A et al (2023) Computing performance requirements for web service compositions. Comput Standards Interfaces 83:103664
Zheng H et al (2013) QoS analysis for web service compositions with complex structures. IEEE Trans Serv Comput 6(3):373–386
Yang Y et al (2019) An improved grey wolf optimizer algorithm for energy-aware service composition in cloud manufacturing. Int J Adv Manuf Technol 105:3079–3091
Asghari P, Rahmani AM, Javadi HHS (2022) Privacy-aware cloud service composition based on QoS optimization in Internet of Things. J Ambient Intell Humaniz Comput 13(11):5295–5320
Li C et al (2021) Memetic Harris Hawks optimization: developments and perspectives on project scheduling and QoS-aware web service composition. Expert Syst Appl 171:114529
Gao Y et al (2022) Bi-objective service composition and optimal selection for cloud manufacturing with QoS and robustness criteria. Appl Soft Comput 128:109530
Ait Hacène Ouhadda S et al (2024) A discrete adaptive lion optimization algorithm for QoS-driven IoT service composition with global constraints. J Netw Syst Manag 32(2):34
Nezafat Tabalvandani MA, Hosseini Shirvani M, Motameni H (2024) Reliability-aware web service composition with cost minimization perspective: a multi-objective particle swarm optimization model in multi-cloud scenarios. Soft Comput 28(6):5173–5196
Kouicem A, Khanouche ME, Tari A (2022) Novel bat algorithm for QoS-aware services composition in large scale internet of things. Clust Comput 25(5):3683–3697
Mohapatra SS et al (2022) QoS-aware cloud service recommendation using metaheuristic approach. Electronics 11(21):3469
Sadouki SC, Tari A (2019) Multi-objective and discrete elephants herding optimization algorithm for QoS aware web service composition. RAIRO-Operations Res 53(2):445–459
Dahan F (2024) An innovative approach for QoS-aware web service composition using whale optimization algorithm. Sci Rep 14(1):22622
Bouzary H, Frank Chen F (2019) A hybrid grey wolf optimizer algorithm with evolutionary operators for optimal QoS-aware service composition and optimal selection in cloud manufacturing. Int J Adv Manuf Technol 101:2771–2784
Al-Masri E (2019) Quality of Web Service (QWS) Dataset. Available from: https://zenodo.org/records/3557008.
Hogg RV, Tanis EA, Zimmerman DL (2021) Probability and statistical inference, 10 edition. Pearson
Yousefi M, Babamir SM (2024) A hybrid energy-aware algorithm for virtual machine placement in cloud computing. Computing 106(5):1297–1320
Acknowledgements
We thank University of Kashan for supporting this research.
Funding
This research was fully supported and funded by University of Kashan.
Author information
Authors and Affiliations
Contributions
Nargess Zahiri obtained real case studies and achieved the results by applying the proposed method to the study. In addition, she provided the related studies. Babamir proposed the suggested method and supervised the research.
Corresponding author
Ethics declarations
Conflict of interests
Zahri is a PhD candidate in software engineering at University of Kashan focusing on web service composition as her thesis subject. Babamir is a professor of software engineering at University of Kashan with research fields of cloud computing and distributed systems. The authors declare that have no competing interests.
Ethical approval
The authors declare that they used no ethical matters.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Zahiri, N., Babamir, S.M. Quality-aware web service composition using a hybrid summarization. J Supercomput 81, 633 (2025). https://doi.org/10.1007/s11227-025-06937-0
Accepted:
Published:
DOI: https://doi.org/10.1007/s11227-025-06937-0