Title :
Hopfield Neural Network Approach for Task Scheduling in a Grid Environment
Author :
Wang, Chengfei ; Wang, Hangyu ; Sun, Fucun
Author_Institution :
Coll. of Electron. Eng., Naval Univ. of Eng., Wuhan
Abstract :
A Hopfield neural network-based approach for task scheduling in a Grid environment is proposed in this paper. All constraints and the optimization object of task scheduling problem in Grid are developed and included in the computational energy function of neural network. To avoid Hopfield neural network converge into local minimum volume, the simulated annealing algorithms are applied to the network. Thus the global minimum of the network as a feasible solution for Grid task scheduling is achieved. The theoretic analyses and simulation experiments have manifested the approach´s effectiveness.
Keywords :
Hopfield neural nets; grid computing; scheduling; Hopfield neural network; computational energy function; simulated annealing algorithms; task scheduling; Computational modeling; Computer science; Constraint optimization; Educational institutions; Grid computing; Hopfield neural networks; Neural networks; Processor scheduling; Scheduling algorithm; Simulated annealing;
Conference_Titel :
Computer Science and Software Engineering, 2008 International Conference on
Conference_Location :
Wuhan, Hubei
Print_ISBN :
978-0-7695-3336-0
DOI :
10.1109/CSSE.2008.557