The primary participants in the cloud technology context are
cloud users and service providers. This setting comprises data centers,
servers, agents, and virtual machines. The supplier's resources are rented to
the cloud customer for varying loads. Since cloud services are so ubiquitous,
most scientists use them to run their workflow applications. Scientific
applications are workflow challenges that are huge and complex and require
higher processing power. The cloud satisfies the workflow requirements of
massive availability and enhanced computational power. For the cloud computing
system to operate well, scheduling is one of the most recent research topics.
This study examines several task-scheduling methods currently in use that are
based on various criteria. This work will help the investigators to gain a
better understanding of task scheduling techniques. The result of the
investigation is tabulated with their performance parameter metrics like
response time, energy efficiency, fault tolerance, and efficient resource
usage.
Author(s) Details
C. K. Sripavithra
Department of Computer Science, Christ (Deemed to be
University), Central Campus, Bangalore, India and Department of Computer
Science, Maharani’s Science College for Women (Autonomous), Mysore, India.
V. B. Kirubanand
Department of Computer Science, Christ (Deemed to be
University), Central Campus, Bangalore, India.
Please see the link:- https://doi.org/10.9734/bpi/strufp/v11/1629
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