Load Balancing Techniques in Cloud Computing: A Comparative Study
Abstract
Efficient load balancing is essential for maintaining performance and resource utilization in cloud computing environments. This paper presents a comparative analysis of static and dynamic load balancing algorithms used in distributed cloud systems. Parameters such as response time, throughput, scalability, and fault tolerance are evaluated using simulation models. The study highlights the advantages and limitations of popular techniques including Round Robin, Throttled Load Balancing, and Ant Colony Optimization. Results indicate that intelligent dynamic algorithms provide better performance in highly variable workloads. The paper also discusses future research opportunities in AI-driven load balancing.
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