Job scheduling in cloud computing environment
| dc.contributor.author | Hamza, Sarra | |
| dc.date.accessioned | 2020-11-26T12:39:55Z | |
| dc.date.available | 2020-11-26T12:39:55Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | Cloud computing provides a pool of virtualized computing resources and adopts pay-per-use model. Task Scheduler is one of the most important cloud computing problems. And that cannot be scheduled using single criteria, but according too many of the criteria's and rules. These rules and criteria's to be agreed upon by the service provider and the user. In this report, I present a particle swarm optimization (PSO) based scheduling algorithm to minimize the completion execution time makespan. Experiment is conducted by varying computation of tasks, number of particles and makespan in fitness function. Then I modify the proposed PSO by adding a method for sorting the tasks by them length to execute them by shortest job first (SJF). The two proposed algorithm are implemented by using the CloudSim simulator. By comparing the two proposed algorithms (PSO and SJF-PSO) the result given by (SJF-PSO) algorithm is the lower Makespan. | en_US |
| dc.identifier.uri | https://repository.univ-msila.dz/handle/123456789/21306 | |
| dc.language.iso | en | en_US |
| dc.publisher | FACULTY : MATHEMATICS AND COMPUTER SCIENCE DEPARTMENT : COMPUTER SCIENCE - SCIENCE OPTION : IDO | en_US |
| dc.subject | Cloud Computing, scheduling algorithm, Particle Swarm Optimization (PSO), Shortest Job First (SJF), Makespan, CloudSim. | en_US |
| dc.title | Job scheduling in cloud computing environment | en_US |
| dc.type | Thesis | en_US |
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