Hybrid enhanced ant colony algorithm and enhanced bee colony algorithm for grid scheduling

Authors:
P. Mathiyalagan;S. Suriya;S. N. Sivanandam
Affiliations:
Department of Computer Science and Engineering, PSG College of Technology, Peelamedu, Coimbatore – 641004, TamilNadu, India.;Department of Computer Science and Engineering, PSG College of Technology, Peelamedu, Coimbatore – 641004, TamilNadu, India.;Department of Computer Science and Engineering, PSG College of Technology, Peelamedu, Coimbatore – 641004, TamilNadu, India
Venue:
International Journal of Grid and Utility Computing
Year:
2011

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Abstract

Selecting the right processor for a task is a complex problem in computational grids. The goal of resource allocation of tasks is the successful scheduling of tasks that reduces execution time. Usually, heuristic approaches are used for solving complex optimisation problems. In this paper, hybridisation of modified pheromone updating rule of ant colony algorithm and modified fitness functions of bee colony algorithm are proposed. The proposed method was simulated by using MATLAB with TORSCHE toolbox. The experimental results show that newly proposed hybrid modified ant colony method and modified bee colony method provide optimal solutions and reduce execution time of a particular task.