Abstract
This paper focuses on the task migration enabling grid workflow application rescheduling problem, presents a reduced task graph model, and implements a performance oriented rescheduling algorithm based on immune genetic algorithm. The experiment shows that, compared with Adaptive Heterogeneous Earliest Finish Time static rescheduling algorithm and the classical dynamic Max-Min scheduling algorithm, the performance advantage of the proposed rescheduling algorithm is obvious, on the one hand because of the performance contribution of global optimization and task migration, and on the other hand because of the efficiency contribution of task graph reduction and immune genetic algorithm’s convergent speed. It also shows that task migration improves grid application’s adaptability of dynamics further.
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Hao, X., Dai, Y., Zhang, B., Chen, T. (2008). Task Migration Enabling Grid Workflow Application Rescheduling. In: Zhang, Y., Yu, G., Bertino, E., Xu, G. (eds) Progress in WWW Research and Development. APWeb 2008. Lecture Notes in Computer Science, vol 4976. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-78849-2_15
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DOI: https://doi.org/10.1007/978-3-540-78849-2_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-78848-5
Online ISBN: 978-3-540-78849-2
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