Authors : V. Venkatesa Kumar, S. Daniel Madan Raja and M. Newlin Rajkumar
Abstract: Cloud computing may be a phrase accustomed to describe a variety of competing ideas that involve an oversized range of computers connected through a period of time communication network such as the web, internet, etc. Such cloud computing allows users to utilize the computation, storage, data and services from around the world in commercialize manner. In a cloud environment, task scheduling algorithms play an important role where the aim is to schedule the tasks effectively so as to reduce the turnaround time and improve resource utilization. Many scheduling techniques have been developed by the researchers like GA (Genetic Algorithm), PSO (Particle Swarm Optimization), min-min, max-min, X-suffrage, etc. An optimized algorithm based on the fuzzy based optimization has proposed which makes a scheduling decision by evaluating the entire group of task in the job queue. The simulation results show that execution time and the response time of an application are independent of each other which are executed separately by different algorithms.
V. Venkatesa Kumar, S. Daniel Madan Raja and M. Newlin Rajkumar, 2016. An Enhanced Resource Optimization for Cloud Based Applications. Asian Journal of Information Technology, 15: 627-634.