Resource Provision for Batch and Interactive Workloads in Data Centers

In this paper we describe a scheduling framework that allocates resources to both batch jobs and interactive jobs simultaneously in a private cloud with a static amount of resources. In the system, every job has an individual service level agreement (SLA), and violating the SLA incurs penalty. We propose a model to formally quantify the SLA violation penalty of both batch and interactive jobs. The analysis on the interactive jobs focuses on queuing analysis and response time. The analysis on batch jobs focuses on the non-preemptive job scheduling for multiple processing units. Based on this model we also propose algorithms to estimate the penalty for both batch jobs and interactive jobs, and algorithms that reduce the total SLA violation penalty. Our experiment results suggest that our system effectively reduces the total penalty by allocating the right amount of resources to heterogeneous jobs in a private cloud system.