A Comprehensive Review of Load Balancing Algorithms, Strategies, and Performance Evaluation

Abstract

Cloud computing has emerged in recent years as a fundamental paradigm for delivering scalable and flexible computing resources. Cloud environments rely on load balancing to allocate resources and distribute workloads efficiently among servers. This survey paper provides researchers with an overview of load-balancing methods, algorithms, and approaches. Literature and research studies are reviewed in order to identify load-balancing strategies' strengths, limitations, and applicability. The paper also examines load-balancing mechanisms in major cloud platforms, including Amazon Elastic Compute Cloud (EC2), Google APP Engine, and Microsoft Azure. An overview of existing studies is presented, along with the performance metrics and evaluation methodologies commonly used in cloud computing research. There is also a discussion of open challenges in load balancing and possible directions for future research. In addition to providing a valuable resource for researchers and practitioners seeking a deeper understanding of load balancing in cloud environments, this survey paper highlights the need for continual innovation in this field