Scheduling of Sporadic Tasks with Deadline Constrains in Cloud Environments

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.