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Delay-Aware Associate Tasks Scheduling in the Cloud Computing

机译:云计算中的延迟感知关联任务调度

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Cloud computing can provide the dynamic and elastic virtual resources for the users to execute the large-scale computing tasks. It has become the hot spot in the academic and industry fields. The tasks scheduling plays an important role in the Cloud computing. It should adopt the scheme to dispatch the computing tasks to the appropriate resources considering some QoS constraints, e.g., task execution time, task completion time, resource utilization, and cost. At present, the scheduling schemes should consider the associate tasks scheduling problem with some constraints in the real applications. In this paper, concerning the delay of the associated tasks scheduling in cloud computing, a structured-based hierarchical task models was discussed and the associated task scheduling algorithms based on delay-bound constraint (SAH-DB) was proposed. The scheduling scheme based on the tasks model can improve the task execution concurrency. The tasks in the parallel structure can be grouped into one task set belonging to the same task layer. Through the calculation of the total tasks execution time-bound in each task layer, the associated task was dispatched to the resources with the minimum execution time. Extensive experimental results demonstrated that the proposed SAH-DB algorithms can achieve better performance than CPM and TS-Sim algorithm in the terms of the total execution cost and resource utilization.
机译:云计算可以为用户提供动态弹性的虚拟资源,以供用户执行大规模的计算任务。它已成为学术和工业领域的热点。任务调度在云计算中起着重要作用。考虑到某些QoS约束,例如任务执行时间,任务完成时间,资源利用率和成本,应采用该方案将计算任务分派到适当的资源。目前,调度方案应在实际应用中考虑具有一定约束的联合任务调度问题。针对云计算中相关任务调度的时延问题,讨论了一种基于结构的分层任务模型,并提出了基于时延约束(SAH-DB)的相关任务调度算法。基于任务模型的调度方案可以提高任务执行的并发性。并行结构中的任务可以分组为一个属于同一任务层的任务集。通过计算每个任务层中的总任务执行时限,可以将关联任务分配到执行时间最短的资源。大量的实验结果表明,从总执行成本和资源利用方面来看,所提出的SAH-DB算法比CPM和TS-Sim算法具有更好的性能。

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