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Bio-inspired Fuzzy Model for Energy Efficient Cloud Computing Through Firefly Search Behaviour Methods

In: New Trends in Computational Vision and Bio-inspired Computing

Author

Listed:
  • Kaushik Sekaran

    (Vignan Institute of Technology and Science, Department of Computer Science and Engineering)

  • P. Venkata Krishna

    (Sri Padmavati Mahila Visvavidyalayam, Department of Computer Science and Engineering)

  • Yenugula Swapna

    (Vignan Institute of Technology and Science, Department of Computer Science and Engineering)

  • P. Lavanya Kumari

    (Vignan Institute of Technology and Science, Department of Computer Science and Engineering)

  • M. P. Divya

    (Vignan Institute of Technology and Science, Department of Computer Science and Engineering)

Abstract

Cloud computing mainly deals with the cloud services and cloud storage for its cloud users as well as to deliver all the data effectively from multiple cloud data centres. The cloud server plays an important role in cloud load balancing. As the number of cloud servers are increased day by day and we are continuously searching for optimal data and more reliable services over the cloud. We propose a new Bio-inspired fuzzy models in meta-heuristic algorithm named Firefly search algorithm that optimizes the load balancing of tasks among multiple virtual machines (VMs) in the cloud server thereby improving the energy efficiency in cloud servers. The proposed algorithm shows marked improvement in terms of throughput, response time, etc., when compared with existing cloud based load balancing algorithms.

Suggested Citation

  • Kaushik Sekaran & P. Venkata Krishna & Yenugula Swapna & P. Lavanya Kumari & M. P. Divya, 2020. "Bio-inspired Fuzzy Model for Energy Efficient Cloud Computing Through Firefly Search Behaviour Methods," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 1043-1049, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-41862-5_106
    DOI: 10.1007/978-3-030-41862-5_106
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