| Autor: |
khadim, zahraa, Arif, Khaldun Ibraheem |
| Předmět: |
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| Zdroj: |
Journal of College of Education for Pure Science; Mar2022, Vol. 12 Issue 1, p60-73, 14p |
| Abstrakt: |
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. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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