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Ant colony based constrained workflow scheduling for heterogeneous computing systems

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Abstract

The problem of constrained workflow scheduling on heterogeneous computing systems has been of major interest in the recent years. The user requirements are described by defining constraints on the workflow makespan and/or its execution cost. The uncertainty in the activity execution path and the dynamicity in the resource workload may cause some run-time changes of the makespan or cost. To prohibit run-time constraint violation, the system needs robust schedules. In this paper, probability of violation (POV) of constraints is proposed as a criterion for the schedule robustness. An ant colony system is then used to minimize an aggregation of violation of constraints and the POV. Simulation results on real world workflows show the effectiveness of the proposed method in finding feasible schedules. The results also indicate that the proposed method decreases the POV, as well as the expected penalty at run-time.

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Notes

  1. Note that larger workflows may require more computations. Therefore, the lower/upper bounds of makespan and cost becomes greater. Thus, according to (5), for a specific tightness coefficient, higher deadline and budget are assigned.

  2. Resource contention is the situation that several activities on the critical path be mapped to the same resource.

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Authors and Affiliations

  1. Faculty of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran

    Somayeh Kianpisheh & Nasrolah Moghadam Charkari

  2. School of Electrical and Computer Engineering, Faculty of Engineering, University of Tehran, Tehran, Iran

    Mehdi Kargahi

  3. School of Computer Science, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran

    Mehdi Kargahi

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  1. Somayeh Kianpisheh
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  2. Nasrolah Moghadam Charkari
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  3. Mehdi Kargahi
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Correspondence to Nasrolah Moghadam Charkari.

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Kianpisheh, S., Charkari, N.M. & Kargahi, M. Ant colony based constrained workflow scheduling for heterogeneous computing systems. Cluster Comput 19, 1053–1070 (2016). https://doi.org/10.1007/s10586-016-0575-8

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