DocumentCode
3251294
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
Volume
4
fYear
1992
fDate
7-11 Jun 1992
Firstpage
582
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location
Baltimore, MD
Print_ISBN
0-7803-0559-0
Type
conf
DOI
10.1109/IJCNN.1992.227256
Filename
227256
Link To Document