Review of Techniques and Algorithms of Load Balancing in Cloud Computing

Abstract

Cloud computing has revolutionized the delivery of modern applications and services through its 
scalability, flexibility, and cost-effectiveness. Efficiently allocating jobs among servers or virtual 
machines is a significant challenge in fully harnessing the capabilities of cloud systems. This review does 
a comprehensive comparison and analysis of various cloud-based dynamic load balancing algorithms to 
identify the most effective one. A variety of load balancing algorithms, including Round Robin, ESCE, 
Min-Min, Max-Min, and Throttled, are covered in the discussion along with their effects on throughput, 
fault tolerance, scalability, and overhead. The literature review stresses the dynamic nature of the cloud 
computing landscape by highlighting important contributions from scholars. Additionally, the study 
identifies issues in cloud services, such as automated service provisioning, virtual machine migration, 
energy management, stored data management, and the growth of small data centers. Even though cloud 
computing has become widely used, these difficulties highlight the continued need for innovation in the 
industry. This review serves as an excellent resource for individuals engaged in the optimization, 
research, and development of cloud computing systems, providing insights into contemporary load 
balancing techniques.