CSA-WSC: cuckoo search algorithm for web service composition in cloud environments
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In recent years, service-based applications are deemed to be one of the new solutions to build an enterprise application system. In order to answer the most demanding needs or adaptations to the needs of changed services quickly, service composition is currently used to exploit the multi-service capabilities in the Information Technology organizations. While web services, which have been independently developed, may not always be compatible with each other, the selection of optimal services and composition of these services are seen as a challenging issue. In this paper, we present cuckoo search algorithm for web service composition problem which is called ‘CSA-WSC’ that provides web service composition to improve the quality of service (QoS) in the distributed cloud environment. The experimental results indicate that the CSA-WSC compared to genetic search skyline network (GS-S-Net) and genetic particle swarm optimization algorithm (GAPSO-WSC) reduces the costs by 7% and responding time by 6%, as two major reasons for the reduction of improvement of the quality of service. It also increases provider availability up to 7.25% and the reliability to 5.5%, as the two important QoS criteria for improving the quality of service.
KeywordsCloud computing Web service composition Quality of service Cuckoo search algorithm
Compliance with ethical standards
Conflict of interest
We have no conflict of interest to declare.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.
Human and animal participants
This article does not contain any studies with human participants or animals performed by any of the authors.
Informed consent was obtained from all individual participants included in the study.
- Buyya R, Broberg J, Goscinski AM (2010) Cloud computing: principles and paradigms, vol 87. Wiley, HobokenGoogle Scholar
- Ghobaei-Arani M, Shamsi M (2015) An extended approach for efficient data storage in cloud computing environment. Int J Comput Netw Inf Secur 7(8):30Google Scholar
- Liu B, Zhang Z (2016) QoS-aware service composition for cloud manufacturing based on the optimal construction of synergistic elementary service groups. Int J Adv Manuf Technol 88(9–12):2757–2771Google Scholar
- Portchelvi V, Venkatesan VP, Shanmugasundaram G (2012) Achieving web services composition-a survey. Softw Eng 2(5):195–202Google Scholar
- Seghir F, Khababa A (2016) A hybrid approach using genetic and fruit fly optimization algorithms for QoS-aware cloud service composition. J Intell Manuf. doi: 10.1007/s10845-016-1215-0
- Wang H, Wang W, Sun H, Cui Z, Rahnamayan S, Zeng S (2016b) A new cuckoo search algorithm with hybrid strategies for flow shop scheduling problems. Soft Comput 18(1):116–121Google Scholar
- Zhou J, Yao X (2016) A hybrid artificial bee colony algorithm for optimal selection of QoS-based cloud manufacturing service composition. Int J Adv Manuf Technol 88(9–12):3371–3387Google Scholar