Title :
Grid task scheduling based on constraint satisfaction neural network
Author :
Dong, Yueli ; Guo, Quan
Author_Institution :
Dept. of Comput. Sci. & Technol., Dalian Neusoft Inst. of Inf., Dalian, China
Abstract :
Task scheduling is of great significance to shorten performing time and minimize the cost for computational Grid. A grid task schedule algorithm is presented in this paper, which is based on a constraint satisfaction neural network. The constraint satisfaction means to remove the violations for sequence and resource constraints during scheduling subtasks for grid environment. The data-transferring costs among subtasks are also considered in our task scheduling. The simulation in this paper has shown that the task schedule algorithm is efficient with respect to the quality of solutions and the solving speed.
Keywords :
constraint theory; electronic data interchange; grid computing; neural nets; resource allocation; scheduling; computational grid; constraint satisfaction neural network; data-transferring; grid environment; grid task schedule algorithm; grid task scheduling; resource constraints; scheduling subtasks; Computational efficiency; Computer networks; Computer science; Costs; Grid computing; Neural networks; Neurons; Processor scheduling; Scheduling algorithm; System recovery; constraint; grid; neural network; task scheduling;
Conference_Titel :
Advanced Computer Control (ICACC), 2010 2nd International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-5845-5
DOI :
10.1109/ICACC.2010.5487161