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Dynamic Task Scheduling Algorithm with Deadline Constraint in Heterogeneous Volunteer Computing Platforms

机译:异构志愿者计算平台中具有期限约束的动态任务调度算法

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Volunteer computing (VC) is a distributed computing paradigm, which provides unlimited computing resources in the form of donated idle resources for many large-scale scientific computing applications. Task scheduling is one of the most challenging problems in VC. Although, dynamic scheduling problem with deadline constraint has been extensively studied in prior studies in the heterogeneous system, such as cloud computing and clusters, these algorithms can’t be fully applied to VC. This is because volunteer nodes can get offline whenever they want without taking any responsibility, which is different from other distributed computing. For this situation, this paper proposes a dynamic task scheduling algorithm for heterogeneous VC with deadline constraint, called deadline preference dispatch scheduling (DPDS). The DPDS algorithm selects tasks with the nearest deadline each time and assigns them to volunteer nodes (VN), which solves the dynamic task scheduling problem with deadline constraint. To make full use of resources and maximize the number of completed tasks before the deadline constraint, on the basis of the DPDS algorithm, improved dispatch constraint scheduling (IDCS) is further proposed. To verify our algorithms, we conducted experiments, and the results show that the proposed algorithms can effectively solve the dynamic task assignment problem with deadline constraint in VC.
机译:志愿计算(VC)是一种分布式计算范例,它以捐赠的空闲资源的形式为许多大规模科学计算应用程序提供无限的计算资源。任务调度是VC中最具挑战性的问题之一。尽管在先前的研究中,诸如云计算和集群之类的异构系统已经广泛研究了具有期限约束的动态调度问题,但是这些算法无法完全应用于VC。这是因为志愿者节点可以随时根据需要脱机而无需承担任何责任,这与其他分布式计算不同。针对这种情况,本文提出了一种具有期限约束的异构VC动态任务调度算法,称为期限优先调度调度(DPDS)。 DPDS算法每次都会选择截止日期最近的任务,并将其分配给志愿者节点(VN),从而解决了具有截止日期约束的动态任务调度问题。为了充分利用资源并在截止期限约束之前最大化已完成任务的数量,在DPDS算法的基础上,进一步提出了改进的调度约束调度(IDCS)。为了验证我们的算法,我们进行了实验,结果表明所提出的算法可以有效地解决VC中具有期限约束的动态任务分配问题。

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