A Queueing Model to Achieve Proper Elasticity for Cloud Cluster Jobs

Achieving proper elasticity for cloud jobs is a challenging research problem and far from being solved. In this paper, we focus on how to achieve proper elasticity for highly parallelized jobs which run on cloud clusters. In particular, we present an analytical model based on finite queueing systems that can be used to determine at any given instance of time and under current workload conditions the minimal number of cloud resources needed to satisfy the SLO response time. We give numerical examples to demonstrate the applicability and usefulness of our model. In addition, we verify the correctness of our analytical model using simulation.