Performance Evaluation of Intelligent Load Balancing Algorithms Using Cloud Analyst

Cloud computing has transformed the approach businesses usage their IT assets by providing flexible and scalable services. As the number of cloud users increases, efficient use of resources becomes very important. Load balancing helps in distributing incoming user requests among multiple servers so that performance is improved and system availability is maintained.

This paper discusses different load balancing techniques and studies their effect on performance, scalability, and cost. Cyclic Request Allocation Method, Capacity-Aware Request Control Strategy and Dynamic Balanced Execution Load Distribution Technique are simulated using the Cloud Analyst tool. These algorithms are tested under three Service Allocation and Routing Strategies that are Closest Data Center, Optimized Response Time, and Reconfigure Dynamically with Load Balancer. The evolution is focused on overall response latency and whole data transfer cost