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Cluster Computing
Erschienen in: Cluster Computing 3/2014

01.09.2014

Task scheduling on computational Grids using Gravitational Search Algorithm

verfasst von: Amirreza Zarrabi, Khairulmizam Samsudin

Erschienen in: Cluster Computing | Ausgabe 3/2014

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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.
Vorheriger Artikel Towards autonomic performance management of large scale data centers using interaction balance principle
Nächster Artikel Trust-driven and QoS demand clustering analysis based cloud workflow scheduling strategies

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Metadaten
Titel
Task scheduling on computational Grids using Gravitational Search Algorithm
verfasst von
Amirreza Zarrabi
Khairulmizam Samsudin
Publikationsdatum
01.09.2014
Verlag
Springer US
Erschienen in
Cluster Computing / Ausgabe 3/2014
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-013-0338-8

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