Multiobjective differential evolution for workflow execution on grids
Proceedings of the 5th international workshop on Middleware for grid computing: held at the ACM/IFIP/USENIX 8th International Middleware Conference
Spectral Clustering Scheduling Techniques for Tasks with Strict QoS Requirements
Euro-Par '08 Proceedings of the 14th international Euro-Par conference on Parallel Processing
International Journal of Knowledge-based and Intelligent Engineering Systems
New challenges of parallel job scheduling
JSSPP'07 Proceedings of the 13th international conference on Job scheduling strategies for parallel processing
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
Reference Point Based Multi-Objective Optimization to Workflow Grid Scheduling
International Journal of Applied Evolutionary Computation
Meta-schedulers for grid computing based on multi-objective swarm algorithms
Applied Soft Computing
Computational Optimization and Applications
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Resources scheduling plays an important role in Grid. This paper converts resources scheduling problem in Grid into a multiobjective optimization problem, and presents a resources scheduling approach based on multiobjective genetic algorithms. This approach deals with dependent relationships of jobs, and regards multi-dimensional Qos metrics, completion time and execution cost of jobs, as multiobjective. Based on Pareto Sorting and niched sharing method, our approach determines optimal solutions. Experimental results show that our approach gets less completion time of jobs and total execution cost of jobs than Min-Min algorithm and Max-Min algorithm.