DAG Scheduling Using a Lookahead Variant of the Heterogeneous Earliest Finish Time Algorithm

Among the numerous DAG scheduling heuristics suitable for heterogeneous systems, the Heterogeneous Earliest Finish Time (HEFT) heuristic is known to give good results in short time. In this paper, we propose an improvement of HEFT, where the locally optimal decisions made by the heuristic do not rely on estimates of a single task only, but also look ahead in the schedule and take into account information about the impact of this decision to the children of the task being allocated. Preliminary simulation results indicate that the lookahead variation of HEFT can effectively reduce the makespan of the schedule in most cases without making the algorithm’s execution time prohibitively high.

[1]  Rizos Sakellariou,et al.  Scheduling Data-IntensiveWorkflows onto Storage-Constrained Distributed Resources , 2007, Seventh IEEE International Symposium on Cluster Computing and the Grid (CCGrid '07).

[2]  Ian J. Taylor,et al.  Workflows and e-Science: An overview of workflow system features and capabilities , 2009, Future Gener. Comput. Syst..

[3]  James Annis et al. Applying chimera virtual data concepts to cluster finding in the Sloan Sky Survey , 2002 .

[4]  Michael Pinedo,et al.  Scheduling: Theory, Algorithms, and Systems , 1994 .

[5]  Yong Zhao,et al.  A notation and system for expressing and executing cleanly typed workflows on messy scientific data , 2005, SGMD.

[6]  Kuo-Chi Lin,et al.  An incremental genetic algorithm approach to multiprocessor scheduling , 2004, IEEE Transactions on Parallel and Distributed Systems.

[7]  Rizos Sakellariou,et al.  An Experimental Investigation into the Rank Function of the Heterogeneous Earliest Finish Time Scheduling Algorithm , 2003, Euro-Par.

[8]  Salim Hariri,et al.  Performance-Effective and Low-Complexity Task Scheduling for Heterogeneous Computing , 2002, IEEE Trans. Parallel Distributed Syst..

[9]  Y.-K. Kwok,et al.  Static scheduling algorithms for allocating directed task graphs to multiprocessors , 1999, CSUR.

[10]  Dennis Gannon,et al.  Workflows for e-Science, Scientific Workflows for Grids , 2014 .

[11]  Emmanuel Jeannot,et al.  Comparative Evaluation Of The Robustness Of DAG Scheduling Heuristics , 2008, CoreGRID Integration Workshop.

[12]  Heon Young Yeom,et al.  k-Depth Look-Ahead Task Scheduling in Network of Heterogeneous Processors , 2002, ICOIN.

[13]  Rizos Sakellariou,et al.  A hybrid heuristic for DAG scheduling on heterogeneous systems , 2004, 18th International Parallel and Distributed Processing Symposium, 2004. Proceedings..

[14]  Edmundo Roberto Mauro Madeira,et al.  A performance-oriented adaptive scheduler for dependent tasks on grids , 2008 .

[15]  Rajkumar Buyya,et al.  Workflow scheduling algorithms for grid computing , 2008 .

[16]  Daniel S. Katz,et al.  Pegasus: A framework for mapping complex scientific workflows onto distributed systems , 2005, Sci. Program..