Title :
Task Scheduling of Computational Grid Based on Particle Swarm Algorithm
Author :
Li, Hui ; Wang, Lifeng ; Liu, Jianhong
Author_Institution :
Coll. of Commun. & Electron. Eng., Qiqihar Univ., Qiqihar, China
Abstract :
The traditional scheduling theory can only get the approximate optimal solution of the problem, and most is to consider algorithms on a single task or independent multitask scheduling. It presents a particle swarm algorithm to solve the task scheduling problem of computational grid. It builds a task scheduling model of computational grid, changes the particle swarm algorithm in continuous space searching to an integer space searching, selects the appropriate inertia weight value, and enhances the searching capabilities of the algorithm. Through comparison with genetic algorithm, hybrid algorithm, and ant algorithm, the results show that the grid task scheduling algorithm has some advantages.
Keywords :
computational complexity; genetic algorithms; grid computing; particle swarm optimisation; scheduling; task analysis; ant algorithm; computational grid task scheduling; continuous space searching; genetic algorithm; inertial weight value; integer space searching; multitask scheduling; particle swarm algorithm; Assembly; Computational modeling; Costs; Educational institutions; Genetic algorithms; Grid computing; Particle swarm optimization; Processor scheduling; Resource management; Scheduling algorithm; computational grid; particle swarm; scheduling model; task scheduling;
Conference_Titel :
Computational Science and Optimization (CSO), 2010 Third International Joint Conference on
Conference_Location :
Huangshan, Anhui
Print_ISBN :
978-1-4244-6812-6
Electronic_ISBN :
978-1-4244-6813-3
DOI :
10.1109/CSO.2010.34