Parental Prioritization-Based Task Scheduling in Heterogeneous Systems
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Efficient task scheduling is important for achieving high performance in heterogeneous distributed computing systems. The main focus of this research is to build a task scheduling algorithm for a heterogeneous environment. We proposed an algorithm named parental prioritization earliest finish time. It has two phases, tasks prioritization phase and processor assigning phase. In the tasks prioritization phase, tasks will schedule in parental priority queue (PPQ) on the basis of downward rank and parental priority. Task prioritization is based on the directed acyclic graph. It can schedule the task of successor row before the current row if it has less communication cost. In the processor assigning phase, the processor will allocate to the scheduled tasks obtained from PPQ keeping the computation cost to a minimum. This proposed algorithm is compared with HEFT and CPOP algorithms through graphs generated from random task graph generator and a set of tasks. The experimental results show that our proposed scheduling algorithm performs significantly better than other algorithms in terms of both cost and makespan of schedules.
KeywordsHeterogeneous systems Task scheduling Cloud computing Directed acyclic graph Parental priority queue
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