Arohi Joshi
Independent Researcher
India
Abstract
Designing scalable load balancing techniques in cloud environments is critical to ensure high availability, fault tolerance, and efficient resource utilization in distributed systems. This manuscript presents a systematic study of load balancing algorithms and their scalability characteristics, drawing upon case studies from leading cloud providers and academic benchmarks as of 2018. The objectives include (1) classifying prominent load balancing strategies, (2) evaluating their performance under varying workload intensities, (3) analyzing architectural considerations that impact scalability, and (4) deriving best practices for engineering implementations. Through comparative analysis of round-robin, least-connection, weighted least-connection, and distributed hash table–based approaches, this work demonstrates how design choices influence throughput, latency, and resource elasticity in Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) models. The findings inform guidelines for cloud architects aiming to support dynamic scaling in multi-tenant environments.
Keywords
Load balancing, cloud scalability, distributed systems, elasticity, fault tolerance
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