Analysis of Optimization and Conventional Algorithms Using CloudSim in Cloud

Cloud computing is an innovative evolving technology provides supreme computing power to the users in cloud environment over the Internet. Requirements of end users are getting better service at low cost and Service Providers requirements are attain maximum gain with minimal overhead. Load Balancing in Virtual Machine plays a vital role to achieve better performance. Request for Virtual Machine and submission of tasks is purely dynamic, which is based on client demand for task execution. In traditional task scheduling method, the scheduling is not optimized. In this paper, two different Meta heuristic scheduling algorithms are implemented for better scheduling of tasks. Many optimization algorithms such as Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) are used to handle the load balance in dynamic environment. In this paper, different LB optimized techniques and conventional algorithm results are compared and analyze by its metrics results.