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Application of Fuzzy Logic for Horizontal Scaling in Kubernetes Environments within the Context of Edge Computing

Author

Listed:
  • Sérgio N. Silva

    (InovAI Lab, nPITI/IMD, Federal University of Rio Grande do Norte (UFRN), Natal 59078-970, RN, Brazil
    Leading Advanced Technologies Center of Excellence (LANCE), nPITI/IMD, Federal University of Rio Grande do Norte (UFRN), Natal 59078-970, RN, Brazil
    These authors contributed equally to this work.)

  • Mateus A. S. de S. Goldbarg

    (InovAI Lab, nPITI/IMD, Federal University of Rio Grande do Norte (UFRN), Natal 59078-970, RN, Brazil
    Leading Advanced Technologies Center of Excellence (LANCE), nPITI/IMD, Federal University of Rio Grande do Norte (UFRN), Natal 59078-970, RN, Brazil)

  • Lucileide M. D. da Silva

    (InovAI Lab, nPITI/IMD, Federal University of Rio Grande do Norte (UFRN), Natal 59078-970, RN, Brazil
    Leading Advanced Technologies Center of Excellence (LANCE), nPITI/IMD, Federal University of Rio Grande do Norte (UFRN), Natal 59078-970, RN, Brazil
    Federal Institute of Education, Science and Technology of Rio Grande do Norte, Paraiso, Santa Cruz 59200-000, RN, Brazil)

  • Marcelo A. C. Fernandes

    (InovAI Lab, nPITI/IMD, Federal University of Rio Grande do Norte (UFRN), Natal 59078-970, RN, Brazil
    Leading Advanced Technologies Center of Excellence (LANCE), nPITI/IMD, Federal University of Rio Grande do Norte (UFRN), Natal 59078-970, RN, Brazil
    Department of Computer and Automation Engineering, Federal University of Rio Grande do Norte, Natal 59078-970, RN, Brazil
    These authors contributed equally to this work.)

Abstract

This paper presents a fuzzy logic-based approach for replica scaling in a Kubernetes environment, focusing on integrating Edge Computing. The proposed FHS (Fuzzy-based Horizontal Scaling) system was compared to the standard Kubernetes scaling mechanism, HPA (Horizontal Pod Autoscaler). The comparison considered resource consumption, the number of replicas used, and adherence to latency Service-Level Agreements (SLAs). The experiments were conducted in an environment simulating Edge Computing infrastructure, with virtual machines used to represent edge nodes and traffic generated via JMeter. The results demonstrate that FHS achieves a reduction in CPU consumption, uses fewer replicas under the same stress conditions, and exhibits more distributed SLA latency violation rates compared to HPA. These results indicate that FHS offers a more efficient and customizable solution for replica scaling in Kubernetes within Edge Computing environments, contributing to both operational efficiency and service quality.

Suggested Citation

  • Sérgio N. Silva & Mateus A. S. de S. Goldbarg & Lucileide M. D. da Silva & Marcelo A. C. Fernandes, 2024. "Application of Fuzzy Logic for Horizontal Scaling in Kubernetes Environments within the Context of Edge Computing," Future Internet, MDPI, vol. 16(9), pages 1-20, September.
    • Handle: RePEc:gam:jftint:v:16:y:2024:i:9:p:316-:d:1469257
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    References listed on IDEAS

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    1. Subrota Kumar Mondal & Xiaohai Wu & Hussain Mohammed Dipu Kabir & Hong-Ning Dai & Kan Ni & Honggang Yuan & Ting Wang, 2023. "Toward Optimal Load Prediction and Customizable Autoscaling Scheme for Kubernetes," Mathematics, MDPI, vol. 11(12), pages 1-30, June.
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