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

Authors: P. Mathiyalagan, S. Suriya, S.N. Sivanandam

Addresses: 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

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.

Keywords: swarm intelligence; scheduling; heuristics; stigmeric communication; pheromones; ant colony optimisation; bee colony optimisation; grid scheduling; grid computing; resource allocation; simulation.

DOI: 10.1504/IJGUC.2011.039980

International Journal of Grid and Utility Computing, 2011 Vol.2 No.1, pp.45 - 58

Received: 09 Jul 2010
Accepted: 21 Oct 2010
Published online: 28 Mar 2015 *

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