%0 Journal Article
%T Grid Scheduling Strategy using GA (GSSGA)
%A Dr.D.I.George Amalarethinam
%A F.Kurus Malai Selvi
%J International Journal of Computer Technology and Applications
%D 2012
%I Technopark Publications
%X Efficient scheduling algorithm is required to usethe grid resources properly. List schedulingheuristic algorithms are to schedule theapplication programs and produces sub optimalsolutions. An evolutionary based schedulingalgorithm will produce an optimal solution. Theproposed algorithm, namely, ¡°Grid SchedulingStrategy using GA¡± (GSSGA) adopts the geneticalgorithm to solve the dependent task basedapplications. The new fitness function has beendeveloped in GSSGA and the conventionalgenetic operators like selection, crossover andmutation are used appropriately. Afterconducting numerous experiments, the proposedGSSGA outperforms the existing algorithms byminimizing the schedule length of the task graph
%K Grid Computing
%K Parallel Processing
%K GA
%K Task Scheduling
%K DAG
%K Fitness Function.
%U http://ijcta.com/documents/volumes/vol3issue5/ijcta2012030527.pdf