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Frequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
Home Archives Volume 5 Issue 1 ijcatr05011004

IJCATR Volume 5 Issue 1

Proposing a New Job Scheduling Algorithm in Grid Environment Using a Combination of Ant Colony Optimization Algorithm (ACO) and Suffrage

Firoozeh Ghazipour Seyed Javad Mirabedini
10.7753/IJCATR0501.1004
keywords : jobs, scheduling, Grid environment, Ant Colony Optimization (ACO), Suffrage, makespan

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Scheduling jobs to resources in grid computing is complicated due to the distributed and heterogeneous nature of the resources. The purpose of job scheduling in grid environment is to achieve high system throughput and minimize the execution time of applications. The complexity of scheduling problem increases with the size of the grid and becomes highly difficult to solve effectively. To obtain a good and efficient method to solve scheduling problems in grid, a new area of research is implemented. In this paper, a job scheduling algorithm is proposed to assign jobs to available resources in grid environment. The proposed algorithm is based on Ant Colony Optimization (ACO) algorithm. This algorithm is combined with one of the best scheduling algorithm, Suffrage. This paper uses the result of Suffrage in proposed ACO algorithm. The main contribution of this work is to minimize the makespan of a given set of jobs. The experimental results show that the proposed algorithm can lead to significant performance in grid environment.
@artical{f512016ijcatr05011004,
Title = "Proposing a New Job Scheduling Algorithm in Grid Environment Using a Combination of Ant Colony Optimization Algorithm (ACO) and Suffrage",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "5",
Issue ="1",
Pages ="20 - 25",
Year = "2016",
Authors ="Firoozeh Ghazipour Seyed Javad Mirabedini"}
  • The paper proposes a new job scheduling algorithm using a combination of ACO and Suffrage.
  • The proposed algorithm schedules the jobs efficiently in grid environment.
  • The proposed algorithm uses utility formulas to assign jobs into available resources.
  • In the Simulation, a performance evaluation of the proposed algorithm is carried out.
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