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Diverse Contemporary Algorithms to Resolve Load Balancing Issues in Cloud Computing—A Comparative Study

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Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing

Part of the book series: Algorithms for Intelligent Systems ((AIS))

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Abstract

In the past couple of years, cloud technology has experienced a massive growth as it offers a wide range of benefits like very less capital expenditure, increased flexibility, scalability, etc. This massive growth has made effective resource utilization in cloud environment, an important area of concern to ensure user satisfaction. Various load balancing approaches have been proposed in the past in order to overcome this concern. The present work presents a review of different load balancing techniques in cloud environment. It also presents a clear comparative study of six contemporary algorithms, viz. Round Robin, throttled, ant colony, honey bee, ESCEL and PSO based on salient cloud load balancing metrics and also highlights the pros and cons of each algorithm.

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Author information

Authors and Affiliations

  1. Institute of Engineering & Management, Kolkata, India

    Lopa Mandal & Jayjeet Dhar

Authors
  1. Lopa Mandal
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  2. Jayjeet Dhar
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Corresponding author

Correspondence to Lopa Mandal .

Editor information

Editors and Affiliations

  1. Department of Information Technology, Institute of Engineering and Management, Kolkata, West Bengal, India

    Lopa Mandal

  2. Department of Mechanical Engineering, Faculty of Engineering, University of Porto, Porto, Portugal

    Joao Manuel R. S. Tavares

  3. Department of Automation and Applied Informatics, Department of International Relations, Programs and Projects, Intelligent Systems Research Centre, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina E. Balas

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Mandal, L., Dhar, J. (2022). Diverse Contemporary Algorithms to Resolve Load Balancing Issues in Cloud Computing—A Comparative Study. In: Mandal, L., Tavares, J.M.R.S., Balas, V.E. (eds) Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-1657-1_35

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