Grid Resource Scheduling Algorithm Based on Optimization Hierarchy

2019 ◽  
Author(s):  
Feng Liu ◽  
Wei-Wei Guo ◽  
Yu-Long Li
Keyword(s):  
Scheduling Algorithm ◽  
Resource Scheduling ◽  
Grid Resource ◽  
Grid Resource Scheduling

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
Keyword(s):  
Scheduling Algorithm ◽  
Resource Scheduling ◽  
Grid Resource ◽  
Resource Information ◽  
Grid Resource Scheduling ◽  
Utilization Ratio ◽  
Simulation Results ◽  
And Task

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.

Grid Resource Scheduling Strategy Based on Elite DNA Genetic Algorithm

2011 ◽  
Vol 204-210 ◽  
pp. 1594-1598
Author(s):  
Sheng Jun Xue ◽  
Wei Qi
Keyword(s):  
Genetic Algorithm ◽  
High Efficiency ◽  
Scheduling Algorithm ◽  
Resource Scheduling ◽  
Optimal Solution ◽  
Task Completion ◽  
Improved Genetic Algorithm ◽  
Grid Resource ◽  
Grid Environment ◽  
Grid Resource Scheduling

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.

Sign in / Sign up

Export Citation Format

Share Document