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A cloud service composition method using a fuzzy-based particle swarm optimization algorithm

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Abstract

In today's dynamic business landscape, organizations heavily rely on cloud computing to leverage the power of virtualization and resource sharing. Service composition plays a vital role in cloud computing, combining multiple cloud services to fulfill complex user requests. Service composition in cloud computing presents several challenges. These include service heterogeneity, dynamic service availability, QoS (Quality of Service) constraints, and scalability issues. Traditional approaches often struggle to handle these challenges efficiently, leading to suboptimal resource utilization and poor service performance. This work presents a fuzzy-based strategy for composing cloud services to overcome these obstacles. The fact that service composition is NP-hard has prompted the use of a range of metaheuristic algorithms in numerous papers. Therefore, Particle Swarm Optimization (PSO) has been applied in this paper to solve the problem. Implementing a fuzzy-based PSO for service composition requires defining the fuzzy membership functions and rules based on the specific service domain. Once the fuzzy logic components are established, they can be integrated into the PSO algorithm. The simulation results have shown the high efficiency of the proposed method in decreasing the latency, cost, and response time.

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Notes

  1. Multiple Cloud Environment.

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Authors and Affiliations

  1. Department of Mathematics, Payame Noor University, Tehran, Iran

    Habibeh Nazif

  2. Communication Technology Engineering Department, Tartous University, Tartus, Syria

    Mohammad Nassr

  3. Dpartment of Mathematics and Natural Sciences, Gulf University for Science and Technology, Mishref Campus, Mubarak Al-Abdullah, Kuwait

    Mohammad Nassr

  4. Biomedical Engineering Department, College of Engineering and Technologies, Al-Mustaqbal University, 51001, Hillah, Babil, Iraq

    Hamza Mohammed Ridha Al-Khafaji

  5. Department of Computer Engineering, Faculty of Engineering and Natural Sciences, Kadir Has University, Istanbul, Turkey

    Nima Jafari Navimipour

  6. Future Technology Research Center, National Yunlin University of Science and Technology, Douliou, Yunlin, 64002, Taiwan

    Nima Jafari Navimipour

  7. Department of Computer Engineering, Nisantasi University, Istanbul, Turkey

    Mehmet Unal

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  1. Habibeh Nazif
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  2. Mohammad Nassr
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Correspondence to Nima Jafari Navimipour.

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Nazif, H., Nassr, M., Al-Khafaji, H.M.R. et al. A cloud service composition method using a fuzzy-based particle swarm optimization algorithm. Multimed Tools Appl (2023). https://doi.org/10.1007/s11042-023-17719-2

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  • DOI: https://doi.org/10.1007/s11042-023-17719-2

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