{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T18:31:17Z","timestamp":1775068277118,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T00:00:00Z","timestamp":1656374400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Marie Sk\u0142odowska Curie Actions (MSCA) Innovative Training Network (ITN)","award":["No. 861219"],"award-info":[{"award-number":["No. 861219"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The rapid development of Cloud Computing (CC) has led to the release of many services in the cloud environment. Service composition awareness of Quality of Service (QoS) is a significant challenge in CC. A single service in the cloud environment cannot respond to the complex requests and diverse requirements of the real world. In some cases, one service cannot fulfill the user\u2019s needs, so it is necessary to combine different services to meet these requirements. Many available services provide an enormous QoS and selecting or composing those combined services is called an Np-hard optimization problem. One of the significant challenges in CC is integrating existing services to meet the intricate necessities of different types of users. Due to NP-hard complexity of service composition, many metaheuristic algorithms have been used so far. This article presents the Artificial Bee Colony and Genetic Algorithm (ABCGA) as a metaheuristic algorithm to achieve the desired goals. If the fitness function of the services selected by the Genetic Algorithm (GA) is suitable, a set of services is further introduced for the Artificial Bee Colony (ABC) algorithm to choose the appropriate service from, according to each user\u2019s needs. The proposed solution is evaluated through experiments using Cloud SIM simulation, and the numerical results prove the efficiency of the proposed method with respect to reliability, availability, and cost.<\/jats:p>","DOI":"10.3390\/s22134873","type":"journal-article","created":{"date-parts":[[2022,6,29]],"date-time":"2022-06-29T01:48:38Z","timestamp":1656467318000},"page":"4873","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["A Hybrid Service Selection and Composition for Cloud Computing Using the Adaptive Penalty Function in Genetic and Artificial Bee Colony Algorithm"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7208-3576","authenticated-orcid":false,"given":"Seyed Salar","family":"Sefati","sequence":"first","affiliation":[{"name":"Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, 060042 Bucure\u0219ti, Romania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7028-3921","authenticated-orcid":false,"given":"Simona","family":"Halunga","sequence":"additional","affiliation":[{"name":"Faculty of Electronics, Telecommunications and Information Technology, University Politehnica of Bucharest, 060042 Bucure\u0219ti, Romania"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Bella, H.K., and Vasundra, S. (2022, January 20\u201322). A study of Security Threats and Attacks in Cloud Computing. Proceedings of the 2022 4th International Conference on Smart Systems and Inventive Technology (ICSSIT), Tirunelveli, India.","DOI":"10.1109\/ICSSIT53264.2022.9716317"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"101487","DOI":"10.1016\/j.techsoc.2020.101487","article-title":"Customer satisfaction with bank services: The role of cloud services, security, e-learning and service quality","volume":"64","author":"Li","year":"2021","journal-title":"Technol. Soc."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1865","DOI":"10.1002\/spe.2598","article-title":"A moth-flame optimization algorithm for web service composition in cloud computing: Simulation and verification","volume":"48","author":"Rahmanian","year":"2018","journal-title":"Softw. Pract. Exp."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1007\/s11227-021-03810-8","article-title":"Load balancing in cloud computing environment using the Grey wolf optimization algorithm based on the reliability: Performance evaluation","volume":"78","author":"Sefati","year":"2022","journal-title":"J. Supercomput."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Cho, S., Hwang, S., Shin, W., Kim, N., and In, H.P. (2021). Design of military service framework for enabling migration to military SaaS cloud environment. Electronics, 10.","DOI":"10.3390\/electronics10050572"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"3079","DOI":"10.1007\/s00170-019-04449-9","article-title":"An improved grey wolf optimizer algorithm for energy-aware service composition in cloud manufacturing","volume":"105","author":"Yang","year":"2019","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"424","DOI":"10.1016\/j.jnca.2013.10.004","article-title":"Resource management for Infrastructure as a Service (IaaS) in cloud computing: A survey","volume":"41","author":"Manvi","year":"2014","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_8","first-page":"119","article-title":"An optimisation model for cloud-based supply chain network design: Case study in the banking industry","volume":"27","author":"Hajipour","year":"2021","journal-title":"Int. J. Commun. Netw. Distrib. Syst."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1388","DOI":"10.1108\/K-02-2021-0129","article-title":"Toward the efficient service selection approaches in cloud computing","volume":"51","author":"Rahimi","year":"2021","journal-title":"Kybernetes"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1007\/s10586-020-03108-z","article-title":"Service-oriented replication strategies for improving quality-of-service in cloud computing: A survey","volume":"24","author":"Slimani","year":"2021","journal-title":"Clust. Comput."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ye, Z., Zhou, X., and Bouguettaya, A. (2011). Genetic algorithm based QoS-aware service compositions in cloud computing. International Conference on Database Systems for Advanced Applications, Springer.","DOI":"10.1007\/978-3-642-20152-3_24"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Buyya, R., Ranjan, R., and Calheiros, R.N. (2010). Intercloud: Utility-oriented federation of cloud computing environments for scaling of application services. International Conference on Algorithms and Architectures for Parallel Processing, Springer.","DOI":"10.1007\/978-3-642-13119-6_2"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1016\/j.compind.2014.01.017","article-title":"The challenge of networked enterprises for cloud computing interoperability","volume":"65","author":"Rauschecker","year":"2014","journal-title":"Comput. Ind."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"15620","DOI":"10.1109\/JIOT.2021.3074499","article-title":"A qos-aware service composition mechanism in the internet of things using a hidden-markov-model-based optimization algorithm","volume":"8","author":"Sefati","year":"2021","journal-title":"IEEE Internet Things J."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Zheng, Z., Zhu, J., and Lyu, M.R. (2013, January 6\u20139). Service-generated big data and big data-as-a-service: An overview. Proceedings of the 2013 IEEE International Congress on Big Data, Santa Clara, CA, USA.","DOI":"10.1109\/BigData.Congress.2013.60"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1109\/TSE.2004.11","article-title":"QoS-aware middleware for web services composition","volume":"30","author":"Zeng","year":"2004","journal-title":"IEEE Trans. Softw. Eng."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Bauer, E., and Adams, R. (2012). Reliability and Availability of Cloud Computing, John Wiley & Sons.","DOI":"10.1002\/9781118393994"},{"key":"ref_18","first-page":"285","article-title":"Cloud computing risk assessment: A systematic literature review","volume":"276","author":"Latif","year":"2014","journal-title":"Future Inf. Technol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1145\/2330667.2330685","article-title":"Success factors for deploying cloud computing","volume":"55","author":"Garrison","year":"2012","journal-title":"Commun. ACM"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Amin, Z., Singh, H., and Sethi, N. (2015). Review on fault tolerance techniques in cloud computing. Int. J. Comput. Appl., 116.","DOI":"10.5120\/20435-2768"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"e4768","DOI":"10.1002\/dac.4768","article-title":"Cluster-based data transmission scheme in wireless sensor networks using black hole and ant colony algorithms","volume":"34","author":"Sefati","year":"2021","journal-title":"Int. J. Commun. Syst."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1109\/TSC.2011.7","article-title":"Optimization of resource provisioning cost in cloud computing","volume":"5","author":"Chaisiri","year":"2011","journal-title":"IEEE Trans. Serv. Comput."},{"key":"ref_23","first-page":"1710","article-title":"Single-based and Population-based Metaheuristics for Solving NP-hard Problems","volume":"62","author":"Almufti","year":"2021","journal-title":"Iraqi J. Sci."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"e5240","DOI":"10.1002\/cpe.5240","article-title":"Deterministic and non-deterministic query optimization techniques in the cloud computing","volume":"31","author":"Azhir","year":"2019","journal-title":"Concurr. Comput. Pract. Exp."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"102090","DOI":"10.1016\/j.simpat.2020.102090","article-title":"Simulation and modeling of an improved multi-verse optimization algorithm for QoS-aware web service composition with service level agreements in the cloud environments","volume":"103","author":"Yaghoubi","year":"2020","journal-title":"Simul. Model. Pract. Theory"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Song, Y., Wang, Y., and Jin, D. (2020). A Bayesian approach based on bayes minimum risk decision for reliability assessment of Web service composition. Future Internet, 12.","DOI":"10.3390\/fi12120221"},{"key":"ref_27","first-page":"18","article-title":"HMM-based fault diagnosis for Web service composition","volume":"31","author":"Jia","year":"2020","journal-title":"J. Comput."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"867","DOI":"10.1007\/s10586-020-03166-3","article-title":"CCS-OSSR: A framework based on hybrid MCDM for optimal service selection and ranking of cloud computing services","volume":"24","author":"Kumar","year":"2021","journal-title":"Clust. Comput."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1007\/s00607-021-00955-5","article-title":"Nature inspired meta heuristic algorithms for optimization problems","volume":"104","year":"2022","journal-title":"Computing"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"4676","DOI":"10.1080\/00207543.2017.1402137","article-title":"Correlation-aware manufacturing service composition model using an extended flower pollination algorithm","volume":"56","author":"Zhang","year":"2018","journal-title":"Int. J. Prod. Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2251","DOI":"10.1007\/s10586-016-0647-9","article-title":"Nature-inspired multimedia service composition in a media cloud-based healthcare environment","volume":"19","author":"Alamri","year":"2016","journal-title":"Clust. Comput."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.future.2018.11.022","article-title":"Optimal fitness aware cloud service composition using an adaptive genotypes evolution based genetic algorithm","volume":"94","author":"Jatoth","year":"2019","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1016\/j.jmsy.2020.12.019","article-title":"A multi-attribute personalized recommendation method for manufacturing service composition with combining collaborative filtering and genetic algorithm","volume":"58","author":"Liu","year":"2021","journal-title":"J. Manuf. Syst."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1080\/0951192X.2013.874595","article-title":"A state-of-the-art survey of cloud manufacturing","volume":"28","author":"He","year":"2015","journal-title":"Int. J. Comput. Integr. Manuf."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.elerap.2014.10.002","article-title":"A method for discovering clusters of e-commerce interest patterns using click-stream data","volume":"14","author":"Su","year":"2015","journal-title":"Electron. Commer. Res. Appl."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"17493","DOI":"10.1109\/ACCESS.2019.2895824","article-title":"Semantic-enhanced and context-aware hybrid collaborative filtering for event recommendation in event-based social networks","volume":"7","author":"Xu","year":"2019","journal-title":"IEEE Access"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1402","DOI":"10.1109\/TIFS.2015.2413386","article-title":"T-broker: A trust-aware service brokering scheme for multiple cloud collaborative services","volume":"10","author":"Li","year":"2015","journal-title":"IEEE Trans. Inf. Forensics Secur."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Kuang, L., Yu, L., Huang, L., Wang, Y., Ma, P., Li, C., and Zhu, Y. (2018). A personalized QoS prediction approach for CPS service recommendation based on reputation and location-aware collaborative filtering. Sensors, 18.","DOI":"10.3390\/s18051556"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.knosys.2016.09.033","article-title":"TAP: A personalized trust-aware QoS prediction approach for web service recommendation","volume":"115","author":"Su","year":"2017","journal-title":"Knowl. Based Syst."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1109\/TSC.2015.2475743","article-title":"Data-driven and feedback-enhanced trust computing pattern for large-scale multi-cloud collaborative services","volume":"11","author":"Li","year":"2015","journal-title":"IEEE Trans. Serv. Comput."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"4:1","DOI":"10.1147\/JRD.2009.5429058","article-title":"The reservoir model and architecture for open federated cloud computing","volume":"53","author":"Rochwerger","year":"2009","journal-title":"IBM J. Res. Dev."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Da Cunha Rodrigues, G., Calheiros, R.N., Guimaraes, V.T., Santos, G.L.d., De Carvalho, M.B., Granville, L.Z., Tarouco, L.M.R., and Buyya, R. (2016, January 4\u20138). Monitoring of cloud computing environments: Concepts, solutions, trends, and future directions. Proceedings of the 31st Annual ACM Symposium on Applied Computing, Pisa, Italy.","DOI":"10.1145\/2851613.2851619"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Furht, B., and Escalante, A. (2010). Handbook of Cloud Computing, Springer.","DOI":"10.1007\/978-1-4419-6524-0"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"1102","DOI":"10.1049\/iet-com.2019.0855","article-title":"Performance-based service-level agreement in cloud computing to optimise penalties and revenue","volume":"14","author":"Badshah","year":"2020","journal-title":"IET Commun."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.jnca.2018.07.013","article-title":"Service composition approaches in IoT: A systematic review","volume":"120","author":"Asghari","year":"2018","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"e1867","DOI":"10.2196\/jmir.1867","article-title":"Opportunities and challenges of cloud computing to improve health care services","volume":"13","author":"Kuo","year":"2011","journal-title":"J. Med. Internet Res."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1007\/s10207-013-0208-7","article-title":"Security issues in cloud environments: A survey","volume":"13","author":"Fernandes","year":"2014","journal-title":"Int. J. Inf. Secur."},{"key":"ref_48","unstructured":"Yu, T., and Lin, K.-J. (April, January 29). A broker-based framework for qos-aware web service composition. Proceedings of the 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service, Hong Kong, China."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1387","DOI":"10.1007\/s11227-016-1814-8","article-title":"QoS-aware service composition in cloud computing using data mining techniques and genetic algorithm","volume":"73","author":"Karimi","year":"2017","journal-title":"J. Supercomput."},{"key":"ref_50","first-page":"727","article-title":"Migrating to a service-oriented architecture","volume":"16","author":"Channabasavaiah","year":"2003","journal-title":"IBM Dev."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"e4259","DOI":"10.1002\/dac.4259","article-title":"A cloud service composition method using a trust-based clustering algorithm and honeybee mating optimization algorithm","volume":"33","author":"Zanbouri","year":"2020","journal-title":"Int. J. Commun. Syst."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Ma, H., Wang, A., and Zhang, M. (2015). A hybrid approach using genetic programming and greedy search for QoS-aware web service composition. Transactions on Large-Scale Data-and Knowledge-Centered Systems XVIII, Springer.","DOI":"10.1007\/978-3-662-46485-4_7"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/13\/4873\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T23:39:36Z","timestamp":1760139576000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/13\/4873"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,6,28]]},"references-count":52,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2022,7]]}},"alternative-id":["s22134873"],"URL":"https:\/\/doi.org\/10.3390\/s22134873","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,6,28]]}}}