Title :
Multiprocessor scheduling by mean field theory
Author :
Zhang, Zeeman Z. ; Ansari, Nirwan ; Hou, Edwin ; Yi, Pei-Ken
Author_Institution :
Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA
Abstract :
The authors develop an optimization scheme based on mean field theory (MFT) to solve the task scheduling problem. The algorithm combines characteristics of the simulated annealing (SA) algorithm and the Hopfield neural network. The temperature behavior of MFT for the task scheduling problem is shown to possess a critical temperature below which an optimal solution may be achieved. The algorithm has been applied to various task graphs, and promising results have been obtained
Keywords :
Hopfield neural nets; multiprocessing systems; scheduling; simulated annealing; Hopfield neural network; mean field theory; optimization scheme; simulated annealing; task scheduling; Computational modeling; Hopfield neural networks; Multiprocessing systems; Neural networks; Neurons; Processor scheduling; Simulated annealing; Tellurium; Temperature; Traveling salesman problems;
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
DOI :
10.1109/IJCNN.1992.227256
