Resource demand aware scheduling for workflows in clouds
Resource demand aware scheduling for workflows in clouds
复制标题
云中工作流程的资源需求感知调度
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
B. Mans
中科院分区：
文献类型：
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作者：
K. Almi’ani;Young Choon Lee;B. Mans
在云中运行应用程序的一个主要挑战是确定在性能和成本方面租用的资源（虚拟机或VM）的正确数量。如果应用程序需要跨多个资源运行，则这样的挑战会变得更大。在本文中，我们解决了科学工作流程应用程序的调度问题。由优先级/数据依赖性决定的工作流结构以及云中资源的多样性都使得资源供应和任务调度非常复杂。为此，我们设计了资源需求感知调度（RDAS）算法，调度工作流的资源需求和优先级的基础上考虑工作流的结构。RDAS将工作流分区，并以“公平”的方式将可能不同容量/类型的资源分配给分区，使得它们的执行时间不会显著变化。RDAS将资源和应用程序的异构性（云计算中的一个主要阻碍因素）转化为优化科学工作流资源配置的机会。基于我们的实验结果，RDAS证明了它的能力，最大限度地减少整体工作流完成时间（makespan），从而最大限度地减少执行成本。特别是，RDAS优于现有的三种算法的22%，13%和33%，平均而言，在最大完工时间，成本和使用的资源数量，分别。
A major challenge of running applications in clouds is to determine the right number of resources (virtual machines or VMs) to rent in terms of both performance and cost. Such a challenge becomes greater if the application requires to run across multiple resources. In this paper, we address the problem of scheduling scientific workflow applications. The structure of workflows, dictated by precedence/data dependencies, and the diversity of resources in clouds both at large scale make the resource provisioning and task scheduling very complex. To this end, we design the Resource Demand Aware Scheduling (RDAS) algorithm that schedules workflows based on their resource demands and priorities considering workflow structure. RDAS partitions workflows and allocates resources of possibly different capacities/types to the partitions in a “fair” manner such that their execution times do not vary significantly. RDAS turns resource and application heterogeneity (a major hindering factor in clouds) into an opportunity for optimizing resource provisioning for scientific workflows. Based on our experimental results, RDAS demonstrates its capacity of minimizing the overall workflow completion time (makespan) and in turn minimizing costs of the execution. In particular, RDAS outperforms three existing algorithms by 22%, 13% and 33%, on average, in terms of makespan, cost and the number of resources used, respectively.