UPM Institutional Repository

Task scheduling on computational grids using Gravitational Search Algorithm


Citation

Zarrabi, Amirreza and Samsudin, Khairulmizam (2014) Task scheduling on computational grids using Gravitational Search Algorithm. Cluster Computing, 17 (3). pp. 1001-1011. ISSN 1386-7857; ESSN: 1573-7543

Abstract

Grid computing uses distributed interconnected computers and resources collectively to achieve higher performance computing and resource sharing. Task scheduling is one of the core steps to efficiently exploit the capabilities of Grid environment. Recently, heuristic algorithms have been successfully applied to solve task scheduling on computational Grids. In this paper, Gravitational Search Algorithm (GSA), as one of the latest population-based metaheuristic algorithms, is used for task scheduling on computational Grids. The proposed method employs GSA to find the best solution with the minimum makespan and flowtime. We evaluate this approach with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) method. The results demonstrate that the benefit of the GSA is its speed of convergence and the capability to obtain feasible schedules.


Download File

Full text not available from this repository.

Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.1007/s10586-013-0338-8
Publisher: Springer
Keywords: Grid task scheduling; Gravitational Search Algorithm; Makespan; Flowtime
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 18 Jan 2016 02:04
Last Modified: 18 Jan 2016 02:04
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1007/s10586-013-0338-8
URI: http://psasir.upm.edu.my/id/eprint/35599
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item