Cloud Service Selection System Approach based on QoS Model: A Systematic Review

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Techniques involved in service composition
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Published: Mar 10, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i2.6104
Keywords:
Cloud service, Clustering, Fuzzy, Deep Learning, QoS models

Main Article Content

V N V L S Swathi
Research Scholar in CSE, Department of Computer Science and Engineering, SRM Institute of Technology and Sciences, Kattankulathur, Chennai, India
G Senthil Kumar
Department of Computational Intelligence, SRM Institute of Technology and Sciences, Kattankulathur, Chennai , India
A. Vani Vathsala
Department of Computer Science and Engineering, CVR College of Engineering, Hyderabad, India

Abstract

The Internet of Things (IoT) has received a lot of interest from researchers recently. IoT is seen as a component of the Internet of Things, which will include billions of intelligent, talkative "things" in the coming decades. IoT is a diverse, multi-layer, wide-area network composed of a number of network links. The detection of services and on-demand supply are difficult in such networks, which are comprised of a variety of resource-limited devices. The growth of service computing-related fields will be aided by the development of new IoT services. Therefore, Cloud service composition provides significant services by integrating the single services. Because of the fast spread of cloud services and their different Quality of Service (QoS), identifying necessary tasks and putting together a service model that includes specific performance assurances has become a major technological problem that has caused widespread concern. Various strategies are used in the composition of services i.e., Clustering, Fuzzy, Deep Learning, Particle Swarm Optimization, Cuckoo Search Algorithm and so on. Researchers have made significant efforts in this field, and computational intelligence approaches are thought to be useful in tackling such challenges. Even though, no systematic research on this topic has been done with specific attention to computational intelligence. Therefore, this publication provides a thorough overview of QoS-aware web service composition, with QoS models and approaches to finding future aspects.

Article Details

How to Cite
Swathi, V. N. V. L. S. ., Kumar, G. S. ., & Vathsala, A. V. . (2023). Cloud Service Selection System Approach based on QoS Model: A Systematic Review. International Journal on Recent and Innovation Trends in Computing and Communication, 11(2), 05–13. https://doi.org/10.17762/ijritcc.v11i2.6104
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Vol. 11 No. 2 (2023): February (2023) Issue
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Articles

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