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Load balancing in cloud computing environment using the Grey wolf optimization algorithm based on the reliability: performance evaluation

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Abstract

The introduction of cloud computing has brought about significant developments in information technology. Users can benefit from the multitude of cloud technology services only by connecting to the internet. In cloud computing, load balancing is the fundamental issue that has challenged experts in this research area. Load balancing helps increase user satisfaction and enhance systems’ productivity through efficient and fair work assignments between computing resources. Besides, maintaining a load balancing among resources would be difficult because the resources are usually distributed in a heterogeneous way. Many load-balancing methods try to solve this problem by the metaheuristics algorithm, and each of them attempted to enhance the operation and efficiency of systems. In this paper, Grey wolf optimization (GWO) algorithm has been used based on the resource reliability capability to maintain proper load balancing. In this method, first, the GWO algorithm tries to find the unemployed or busy nodes and, after discovering this node, try to calculate each node’s threshold and fitness function. The results of simulation in CloudSim showed that the costs and response time in the proposed method are less than the other methods, and the obtained solutions are ideal.

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Authors and Affiliations

  1. Department of Computer Engineering, Tabriz branch, Islamic Azad University, Tabriz, Iran

    SeyedSalar Sefati

  2. Department of Management and Production Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Turin, Italy

    Maryamsadat Mousavinasab

  3. Department of Computer Engineering, Institute of Higher Education Roshdiyeh, Tabriz, Iran

    Roya Zareh Farkhady

Authors
  1. SeyedSalar Sefati
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  2. Maryamsadat Mousavinasab
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  3. Roya Zareh Farkhady
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Correspondence to SeyedSalar Sefati.

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Sefati, S., Mousavinasab, M. & Zareh Farkhady, R. Load balancing in cloud computing environment using the Grey wolf optimization algorithm based on the reliability: performance evaluation. J Supercomput 78, 18–42 (2022). https://doi.org/10.1007/s11227-021-03810-8

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  • DOI: https://doi.org/10.1007/s11227-021-03810-8

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