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Scheduling of Sporadic Tasks with Deadline Constrains in Cloud Environments

机译:在云环境中具有最后期限约束的零星任务调度

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The mobile interaction in Cloud systems became a fancy behavior. Data processing on demand or data transfers requests are usually sporadic tasks. In a public environment like a Cloud, events are processed according to specific conditions. Each event has one ore more tasks that will be scheduled and executed in Cloud. This paper addresses the problem of remote scheduling of a periodic and sporadic tasks with deadline constrains in Cloud Environments. Starting from classical addressed scheduling techniques and considering asynchronous mechanism to handle tasks, we analyze the possibility of decoupling event listening from task creation and scheduling, actions that can be put into a peer-peer relation over a network or to client-server in Cloud. We consider multiple independent tasks sources that follow with a specific distribution. We will prove in this paper that for a scheduler in a Cloud these independent sources could be considered as a single one. More, we will prove that the resource allocation process respects the same distribution. We created a simulation experiment in MONARC that highlights the capability of tasks migration in order to respect the deadlines.
机译:云系统中的移动交互成为一种幻想行为。按需数据处理或数据传输请求通常是零星的任务。在像Cloud这样的公共环境中,事件是根据特定条件进行处理的。每个事件都有一个或多个将在Cloud中安排和执行的任务。本文解决了在云环境中具有期限限制的周期性和零星任务的远程调度问题。从经典的寻址调度技术开始,并考虑异步机制来处理任务,我们分析了将事件侦听与任务创建和调度分离的可能性,这些行为可以通过网络或云中的客户端-服务器建立对等关系。我们考虑了多个独立的任务源,它们遵循特定的分布。我们将在本文中证明,对于Cloud中的调度程序,这些独立的资源可以视为一个资源。此外,我们将证明资源分配过程遵循相同的分配。我们在MONARC中创建了一个模拟实验,该实验强调了任务迁移的功能,以便遵守截止日期。

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