Modeling cross-architecture co-tenancy performance interference

Document Type

Conference Proceeding

Publication Date



Department of Computer Science, Center for Data Sciences, Center for Scalable Architectures and Systems


Cloud computing has become a dominant computing paradigm to provide elastic, affordable computing resources to end users. Due to the increased computing power of modern machines powered by multi/many-core computing, data centers often co-locate multiple virtual machines (VMs) into one physical machine, resulting in co-tenancy, and resource sharing and competition. Applications or VMs co-locating in one physical machine can interfere with each other despite of the promise of performance isolation through virtualization. Modelling and predicting co-run interference therefore becomes critical for data center job scheduling and QoS (Quality of Service) assurance. Co-run interference can be categorized into two metrics, sensitivity and pressure, where the former denotes how an application's performance is affected by its co-run applications, and the latter measures how it impacts the performance of its co-run applications. This paper shows that sensitivity and pressure are both application-and architecture dependent. Further, we propose a regression model that predicts an application's sensitivity and pressure across architectures with high accuracy. This regression model enables a data center scheduler to guarantee the QoS of a VM/application when it is scheduled to co-locate with another VMs/applications.

Publisher's Statement

© 2015 IEEE. Publisher's version of record: https://doi.org/10.1109/CCGrid.2015.152

Publication Title

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing