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A hybrid approach using genetic and fruit fly optimization algorithms for QoS-aware cloud service composition

Author

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  • Fateh Seghir

    (University of Ferhat Abbas-Setif 1)

  • Abdellah Khababa

    (University of Ferhat Abbas-Setif 1)

Abstract

This paper addresses the QoS-aware cloud service composition problem, which is known as a NP-hard problem, and proposes a hybrid genetic algorithm (HGA) to solve it. The proposed algorithm combines two phases to perform the evolutionary process search, including genetic algorithm phase and fruit fly optimization phase. In genetic algorithm phase, a novel roulette wheel selection operator is proposed to enhance the efficiency and the exploration search. To reduce the computation time and to maintain a balance between the exploration and exploitation abilities of the proposed HGA, the fruit fly optimization phase is incorporated as a local search strategy. In order to speed-up the convergence of the proposed algorithm, the initial population of HGA is created on the basis of a heuristic local selection method, and the elitism strategy is applied in each generation to prevent the loss of the best solutions during the evolutionary process. The parameter settings of our HGA were tuned and calibrated using the taguchi method of design of experiment, and we suggested the optimal values of these parameters. The experimental results show that the proposed algorithm outperforms the simple genetic algorithm, simple fruit fly optimization algorithm, and another recently proposed algorithm (DGABC) in terms of optimality, computation time, convergence speed and feasibility rate.

Suggested Citation

  • Fateh Seghir & Abdellah Khababa, 2018. "A hybrid approach using genetic and fruit fly optimization algorithms for QoS-aware cloud service composition," Journal of Intelligent Manufacturing, Springer, vol. 29(8), pages 1773-1792, December.
  • Handle: RePEc:spr:joinma:v:29:y:2018:i:8:d:10.1007_s10845-016-1215-0
    DOI: 10.1007/s10845-016-1215-0
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    Cited by:

    1. Venushini Rajendran & R Kanesaraj Ramasamy, 2024. "Real-Time Evaluation of the Improved Eagle Strategy Model in the Internet of Things," Future Internet, MDPI, vol. 16(11), pages 1-30, November.
    2. Hongbin Wang & Yang Ding & Hanchuan Xu, 2024. "Particle swarm optimization service composition algorithm based on prior knowledge," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 35-53, January.
    3. Venushini Rajendran & R Kanesaraj Ramasamy & Wan-Noorshahida Mohd-Isa, 2022. "Improved Eagle Strategy Algorithm for Dynamic Web Service Composition in the IoT: A Conceptual Approach," Future Internet, MDPI, vol. 14(2), pages 1-14, February.

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