Taxonomy of Load Balancing Practices in the Cloud Computing Paradigm

Mukund Kulkarni, Prachi Deshpande, Sanjay Nalbalwar, Anil Nandgaonkar

Source Title: International Journal of Information Retrieval Research (IJIRR)12(3)

ISSN: 2155-6377|EISSN: 2155-6385|EISBN13: 9781683182108|DOI: 10.4018/IJIRR.300292

MLA

Kulkarni, Mukund, et al. "Taxonomy of Load Balancing Practices in the Cloud Computing Paradigm." IJIRR vol.12, no.3 2022: pp.1-15. http://doi.org/10.4018/IJIRR.300292

APA

Kulkarni, M., Deshpande, P., Nalbalwar, S., & Nandgaonkar, A. (2022). Taxonomy of Load Balancing Practices in the Cloud Computing Paradigm. International Journal of Information Retrieval Research (IJIRR), 12(3), 1-15. http://doi.org/10.4018/IJIRR.300292

Chicago

Kulkarni, Mukund, et al. "Taxonomy of Load Balancing Practices in the Cloud Computing Paradigm," International Journal of Information Retrieval Research (IJIRR) 12, no.3: 1-15. http://doi.org/10.4018/IJIRR.300292

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Abstract

Rapid growth in communication technology allows users location-independent access to IT infrastructure at pay-per-use via cloud computing. This has paved a new paradigm in information processing for the consumers. Due to Cloud's inherent characteristics, most service providers shift to the Cloud and its data centers. To retain Cloud's services' reliability, it's essential to carry out the minimum latency tasks and cost-effectively. Various techniques to improve performance and use of assets are focused on load control, task management, resource management, service quality, and workload management. Data load balancing helps data centers to avoid overload/underload of virtual machines, a difficulty in the world of cloud computing. This study reports a state-of-the-art analysis of current load balancing approaches', problems, and complexities to design more successful algorithms.