通信关键任务复制的云工作流程调度与时间和预算问题

Mohammad Kamyar Arbab, Mahmoud Naghibzadeh, S. R. Kamel Tabbakh
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引用次数: 1

摘要

在许多应用程序中,科学工作流是并行识别和执行任务的合适模型,特别是在云中。云环境中资源配置和资源定价模型的不同,使得工作流的调度问题非常复杂。调度算法的主要目的之一是满足用户对服务质量的不同要求。任务间通信延迟是影响工作流优化调度的重要因素。如果不采取适当的措施,它还会大大增加工作流调度的成本。为了解决这个问题,我们提出了一种基于任务重复的列表调度算法,称为通信关键任务复制(CCTD)。我们首先定义工作流的通信关键任务(CCT)的概念。然后,通过提出一种基于排名的方法,我们确定了工作流中的通信关键任务以及重复的候选任务。它们的子任务映射到租用虚拟机的空闲时隙中的任务重复。这种思想在消除父子任务之间数据传输的成本和时间的同时,减少了任务的执行时间,并有效地利用了资源的租用时间间隔。根据所提出的调度算法,提出了一种新的启发式预算分配方法。该方法根据每个任务的工作量和重复程度,将总预算按比例分配给任务。采用四种著名的科学工作流对该算法进行了评估和验证。仿真结果表明,CCTD算法在尊重用户预算约束的前提下,缩短了工作流的总体完成时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Communication-Critical Task Duplication for Cloud Workflow Scheduling with Time and Budget Concerns
scientific workflows are suitable models in many applications for recognition and execution of tasks in parallel, especially in the Cloud. Different aspects of resource provisioning and the resource pricing model in the cloud environment cause the scheduling problem of workflow very complex. One of the main aims of the scheduling algorithms is to satisfy the users’ different quality of service requirements. Communication delay between tasks is an important affecting factor in optimal scheduling of workflows. It can also highly increase the cost of workflow scheduling if proper actions are not taken. To solve this problem, we propose a tasks duplication-based list scheduling algorithm called Communication-Critical Task Duplication (CCTD). We first define the concept of communication critical task (CCT) for a workflow. Then, by presenting a ranking-based approach, we identify communication critical tasks in a workflow as well as duplicating candidates. Task duplication in idle time slots of leased virtual machines which their children tasks are mapped to. This idea, while eliminating the cost and time of data transfer between parent-child tasks, reduces the time of execution of tasks and effectively uses leased time intervals of resources. According to the proposed scheduling algorithm, a new heuristic method has been proposed for the budget distribution. This method distribute overall budget to tasks in proportional to the workload and duplication rank of each task. The proposed algorithm was evaluated and verified using four well-known scientific workflows. The simulation results show that the CCTD algorithm, while respecting the user budget constraint, reduces the workflow overall completion time.
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