Research on Resource Scheduling Algorithm Integrating Task Weight and Multi-QoS Constraint

2011 ◽  
Vol 52-54 ◽  
pp. 1125-1130
Author(s):  
Jing Chen ◽  
Ming Xin Liu

To improve the utilization ratio of resources and the complete number of tasks, a kind of a new grid resource scheduling algorithm TWMQC (based on Task Weight and Multi-QoS Constraint) integrating multi-QoS constraint with task weight was proposed. The accomplished process of grid resource scheduling algorithm was transformed multi attribute constraints of resource and task, according to the parametric resource information and task information, classified different task weight sets based on the priority of tasks. Multi-QoS constraints of deadline of gridlets, bandwidth and CPU were defined, and the correlative algorithms were simulated by the GridSim toolkits. The simulation results show that algorithm TWMQC, which integrating multi-QoS constraint and tasks weight is superior in solving such kind of issues by comparing and analyzing the result data.

2011 ◽  
Vol 204-210 ◽  
pp. 1594-1598
Author(s):  
Sheng Jun Xue ◽  
Wei Qi

Traditional resource scheduling algorithm, in grid environment, exist some defects, for example it can not well meet the quality requirements and can not get the optimal solution. This article gives a new resource scheduling method based on improved genetic algorithm. It achieves grid resource scheduling by using real number encoding and activities point crossover. Experiments show that genetic algorithm can reduce executing time and task completion time, and further improve the scalability of resource scheduling model. This algorithm has stability and high efficiency in grid environment.


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