IaaS云中基于QoS的动态任务调度

Anbazhagi, L. Tamilselvan, Shakkeera
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引用次数: 9

摘要

云计算是一种并行和分布式系统,由一组相互连接和虚拟化的计算机组成,这些计算机在服务提供者和消费者之间作为一个或多个统一的计算资源进行动态配置和呈现。在云计算中,许多任务需要由可用的服务执行,以实现更好的性能、最短的总完成时间、最短的响应时间和资源利用率等。由于这些不同的意图,我们需要提出一种调度算法来执行任务在资源上的适当分配映射。在现有的云计算系统中,任务调度算法主要是基于优先级和总完成时间来设计的。任务调度算法首先根据用户的输入计算任务的优先级,然后按优先级对任务进行排序。其次,该算法计算不同资源上所有任务的最小完成时间,并相应地调度到一个资源上。现有系统的缺点是不能有效地利用闲置资源。本文提出了一种动态调度算法,通过监测资源上的任务时序信息,有效地利用资源的空闲时间。多维成本矩阵表基于执行时间、每个任务的CPU使用情况和当前资源的CPU使用情况,并使用最小-最大策略延长了截止时间值,以便在较早的时间段内完成任务。本文将截止时间、空闲时间和可靠性作为调度的QoS参数。
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QoS based dynamic task scheduling in IaaS cloud
Cloud Computing is a type of parallel and distributed system consisting of a collection of interconnected and virtualized computers that are dynamically provisioned and presented as one or more unified computing resources between the service provider and consumers. In cloud computing, many tasks are to be executed by the available services to achieve better performance, minimum total time for completion, shortest response time, utilization of resources etc. Because of these different intentions, we need to propose a scheduling algorithm to perform appropriate allocation map of tasks on resources. In existing system task scheduling algorithm have been designed based on priority and total completion time in cloud computing. The task scheduling algorithm first computes the priority of the tasks based on the inputs of the users and then sorts the tasks by priority. Second, this algorithm calculates the minimum completion time of all the tasks on different resources and schedules onto a resources accordingly. The drawbacks in existing system are, it does not effectively use the idle resources. In this paper we proposed a dynamic scheduling algorithm that efficiently uses the idle time of resources from monitoring the task timing information on resources. The multi-dimensional cost matrix table is developed based on execution time, CPU usage of each tasks and current CPU usage of resources and also we have extended the deadline time value using min-max policies to complete the tasks within a earlier time period. In this paper, we have considered deadline, idle time and reliability as QoS parameters for scheduling.
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