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Genetic algorithm for DAG scheduling in Grid environments

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3 Author(s)
Pop, F. ; Fac. of Autom. Control & Comput. Sci., Univ. Politeh. of Bucharest, Bucharest, Romania ; Dobre, C. ; Cristea, V.

Complex applications are describing using work-flows. Execution of these workflows in Grid environments require optimized assignment of tasks on available resources according with different constrains. This paper presents a decentralized scheduling algorithm based on genetic algorithms for the problem of DAG scheduling. The genetic algorithm presents a powerful method for optimization and could consider multiple criteria in optimization process. Also, we describe in this paper the integration platform for the proposed algorithm in Grid systems. We make a comparative evaluation with other existing DAG scheduling solution: Cluster ready Children First, Earliest Time First, Highest Level First with Estimated Times, Improved Critical Path with Descendant Prediction) and Hybrid Remapper. We carry out our experiments using a simulation tool with various scheduling scenarios and with heterogeneous input tasks and computation resources. We present several experimental results that offer a support for near-optimal algorithm selection.

Published in:

Intelligent Computer Communication and Processing, 2009. ICCP 2009. IEEE 5th International Conference on

Date of Conference:

27-29 Aug. 2009

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