Task Scheduling In Cloud Computing Based Deadline constraint

Authors

  • Department of Computer Science, College of Education for Pure Science, University of ThiQar, Nassiriya, Iraq.
  • Department of Computer Science, College of Education for Pure Science, University of ThiQar, Nassiriya, Iraq.

DOI:

https://doi.org/10.32792/jeps.v12i1.148

Keywords:

Cloud Computing, task priority, scheduling algorithm, Virtual Machine, Genetic Algorithm (GA).

Abstract

One of the newest technologies is cloud computing most aspects in distributed systems that are
most appealing . On-demand services are available on a pay-as-you-go system basis. In cloud computing,
Major research subjects include work scheduling and genetic algorithms. Task scheduling refers to the
process of allocating tasks to resources (virtual computers), while genetic algorithm is the process of
creating a community between resources in order to find optimal solutions to issues using the theory of
natural selection. We present a genetic approach to job scheduling with deadline constraints in this paper.
Each time the virtual machine load plus completion time is tested smaller and equal to the capacity of the
virtual machine and smaller and equal to the task deadline, two loops are formed, one for tasks and one
for virtual machines The suggested algorithm is compared to various algorithms Existing in use,
including as" An Effective Load Balancing Algorithm Based on Deadline Constraint) ELBAD( "and"
Elastic Load Balancer (ELB)" and the experimental results show that the proposed algorithm is superior
to others in terms of reducing rejected tasks and maximizing accepted tasks.
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Published

2023-01-16