A Preemptive Version of the Min-Min Heuristic for Dynamically Mapping Meta-Tasks on a Distributed Heterogeneous Environment

Mapping and scheduling of Meta-tasks in distributed heterogeneous computing systems are complex computational problems. They are known to be NP-Complete except under a few special situations. Solving the mapping problem is basically deciding on which task should be moved to where and when, to improve the overall performance. There is a wide variety of approaches to the problem of mapping and scheduling in HC systems that are either static or dynamic. In this paper, we propose a preemptive (migratory) of the Min- min heuristic for mapping a set of independent tasks to machines in a HC suite. The proposed algorithm works dynamically to assign tasks in a batch-mode fashion. In our approach, we revise the decision taken by the Min- min heuristic and adjust its allocation strategy in order to improve machine (processor) utilization and hence achieve better mapping performance by minimizing the makespan.