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A Performance Comparison of Load Balancing in Cloud Computing Techniques

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Data Science and Big Data Analytics (IDBA 2023)

Part of the book series: Data-Intensive Research ((DIR))

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Abstract

Cloud computing is a new era in large-scale computing in which information is processed from large data centers. One of the most difficult aspects of this is balancing the load across all of the nodes. It is also necessary for proper asset use and equitable labor allocation. Appropriate allocation and exploitation of computer resources in sharing mode can result in high end-user experience as well as optimal resource consumption. To accomplish the desired aim, massive data-centric systems and networks must be balanced. The load rebalancing problem is seen as an efficiency problem, and a solid regulating set of rules for load can allow for a variety of compensations such as scalability enabling, barrier avoidance, minimizing resource usage, and so on. Several studies have offered numerous solutions to load balancing problems in the cloud environment. This work seeks to investigate and analyze a range of weight balancing methods within the context of cloud computing.

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Author information

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, College of Engineering and Technology, Wollega University, Nekemte, Ethiopia

    Rituraj Jain & Terefe Bayisa

  2. CHRIST (Deemed to be University), Delhi NCR, India

    Kamal Upreti

  3. Department of Computer Science and Engineering, ADGITM, New Delhi, Delhi, India

    Sheela Hundekari

  4. Department of MCA, MIT ADT University, Loni Kalbhor, Pune, India

    Jyoti Parashar

  5. Ajyal Al Marefaah International School, Jizan, Kingdom of Saudi Arabia

    Mujtaba Ali Khan

Authors
  1. Rituraj Jain
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  2. Kamal Upreti
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  3. Sheela Hundekari
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  4. Jyoti Parashar
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  5. Terefe Bayisa
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  6. Mujtaba Ali Khan
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Corresponding author

Correspondence to Kamal Upreti .

Editor information

Editors and Affiliations

  1. Symbiosis University of Applied Sciences Indore, Indore, Madhya Pradesh, India

    Durgesh Mishra

  2. Middlesex University, London, UK

    Xin She Yang

  3. Stanford University, Stanford, CA, USA

    Aynur Unal

  4. Computer Science Department, Namibia University of Science and Technology, Windhoek, Namibia

    Dharm Singh Jat

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Jain, R., Upreti, K., Hundekari, S., Parashar, J., Bayisa, T., Khan, M.A. (2024). A Performance Comparison of Load Balancing in Cloud Computing Techniques. In: Mishra, D., Yang, X.S., Unal, A., Jat, D.S. (eds) Data Science and Big Data Analytics. IDBA 2023. Data-Intensive Research. Springer, Singapore. https://doi.org/10.1007/978-981-99-9179-2_24

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