Load balancing is a research area that seeks to improve the quality of services provided to various clients in cloud computing environments. As cloud users increase around the world, cloud service providers are challenged to develop strategies for distributing tasks to machines for processing at cloud data centers. This work collected and undertook a thorough review of various load balancing techniques, uncovering the key limitations of existing strategies. The publications were chosen from peer-reviewed papers on Google Scholar. Cloud computing, cloud load balancing techniques, approaches to cloud load balancing, and big-data cloud computing systems were among the terms used in the search. Out of 201 studies, 39 met the criteria for inclusion. 5 of the research focused on cloud computing, 6 on cloud load balancing, 7 on resource scheduling in cloud, 16 on techniques for balancing cloud load, and 5 on big-data cloud computing environments. The study identified some research gaps and recommended a throughput-maximization based central-distributive load balancing architecture as a solution to maximize throughput, minimize response time and processing cost, and optimize load balancing architecture. Keywords— Centralized, cloud-computing, distributive, load-balancing.
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