@article{MAKHILLAJIT20161536024,
    title = {An Enhanced Resource Optimization for Cloud Based Applications},
    journal = {Asian Journal of Information Technology},
    volume = {15},
    number = {3},
    pages = {627-634},
    year = {2016},
    issn = {1682-3915},
    doi = {ajit.2016.627.634},
    url = {https://makhillpublications.co/view-article.php?issn=1682-3915&doi=ajit.2016.627.634},
    author = {V. Venkatesa,S. Daniel Madan and},
    keywords = {Cloud computing,scheduling algorithm,turnaround time,jfuzzy,resource},
    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.}
    }