Soft Reliability Aware Scheduling of Real-time Applications on Cloud with MTTF constraints

Nowadays the cloud system receives requests from a wide horizon of users. In order to execute a large number of modern resource-intensive, latency-sensitive applications with deadline requests from the users, the cloud systems are equipped with powerful machines, and the machines run for a significant amount of time. This leads to an increase in the probability of failures of these machines. Hence, the reliability of the cloud system is to be duly considered while designing a scheduling strategy for executing resource-intensive, latency-sensitive applications on it. This paper proposes an efficient scheduling strategy for executing real-time applications (scientific applications) maintaining the reliability constraints of both the cloud system and applications and the deadline constraints of these applications. The proposed policy assigns recoveries for an optimal number of tasks of the application while scheduling them on the cloud considering the reliability constraints of both the cloud system and the application. The experimental evaluation proves that the proposed policy outperforms the state-of-the-art policy both for the synthetic task set and scientific workflows.