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首页> 外文期刊>Parallel and Distributed Systems, IEEE Transactions on >Resource and Instance Hour Minimization for Deadline Constrained DAG Applications Using Computer Clouds
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Resource and Instance Hour Minimization for Deadline Constrained DAG Applications Using Computer Clouds

机译：使用计算机云使截止日期受限的DAG应用程序的资源和实例小时最小化

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摘要

In this paper, we address the resource and virtual machine instance hour minimization problem for directed-acyclic-graph-based deadline constrained applications deployed on computer clouds. The allocated resources and instance hours on computer clouds must: (1) guarantee the satisfaction of a deadline constrained application’s end-to-end deadline; (2) ensure that the number of virtual machine (VM) instances allocated to the application is minimized; (3) under the allocated number of VM instances, determine application execution schedule that minimizes the application’s makespan; and (4) under the decided application execution schedule, determine a VM operation schedule, i.e., when a VM should be turned on or off, that minimizes total VM instance hours needed to execute the application. We first give lower and upper bounds for the number of VM instances needed to guarantee the satisfaction of a deadline constrained application’s end-to-end deadline. Based on the bounds, we develop a heuristic algorithm called minimal slack time and minimal distance (MSMD) algorithm that finds the minimum number of VM instances needed to guarantee the application’s deadline and schedules tasks on the allocated VM instances so that the application’s makespan is minimized. Once the application execution schedule and the number of VM instances needed are determined, the proposed VM instance hour minimization (IHM) algorithm is applied to further reduce the instance hours needed by VMs to complete the application’s execution. Our experimental results show that the MSMD algorithm can guarantee applications’ end-to-end deadlines with less resources than the HEFT , MOHEFT , DBUS , QoS-base and Auto-Scaling heuristic sched- ling algorithms in the literature. Furthermore, under allocated resources, the MSMD algorithm can, on average, reduce an application’s makespan by 3.4 percent of its deadline. In addition, with the IHM algorithm we can effectively reduce the application’s execution instance hours compared with when IHM is not applied.
机译：在本文中，我们针对部署在计算机云上的基于有向无环图的截止日期受限制的应用程序，解决了资源和虚拟机实例小时最小化的问题。在计算机云上分配的资源和实例时间必须：（1）确保满足期限受限的应用程序的端到端期限； （2）确保分配给应用程序的虚拟机（VM）实例的数量最少； （3）在分配的VM实例数量下，确定可最大程度缩短应用程序生成时间的应用程序执行计划； （4）根据确定的应用执行时间表，确定VM运行时间表，即何时开启或关闭VM，以最大程度地减少执行应用所需的VM实例总时数。首先，我们为需要满足期限限制的应用程序的端到端期限提供所需的VM实例数量的上限和下限。根据边界，我们开发了一种启发式算法，称为最小松弛时间和最小距离（MSMD）算法，该算法查找保证应用程序期限所需的最小VM实例数，并在分配的VM实例上调度任务，从而最大程度地减少应用程序的制造时间。一旦确定了应用程序的执行时间表和所需的VM实例数量，建议的VM实例小时最小化（IHM）算法将被应用，以进一步减少VM来完成应用程序执行所需的实例时间。我们的实验结果表明，与文献中的HEFT，MOHEFT，DBUS，基于QoS和Auto-Scaling启发式调度算法相比，MSMD算法可以以更少的资源保证应用程序的端到端期限。此外，在分配的资源下，MSMD算法平均可将应用程序的有效期缩短其截止日期的3.4％。此外，与未应用IHM相比，借助IHM算法，我们可以有效减少应用程序的执行实例时间。

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