Towards Performance Modeling of Speculative Execution for Cloud Applications

Abstract

Interesting approaches to counteract performance variability within cloud datacenters include sending multiple request clones, either immediately or after a specified waiting time. In this paper we present a performance model of cloud applications that utilize the latter concept, known as speculative execution. We study the popular Join-Shortest-Queue load-balancing strategy under the processor sharing queuing discipline. Utilizing the near-synchronized service property of this setting, we model speculative execution using a simplified synchronized service model. Our model is approximate, but accurate enough to be useful even for high utilization scenarios. Furthermore, the model is valid for any, possibly empirical, inter-arrival and service time distributions. We present preliminary simulation results, showing the promise of our proposed model.