R. Mancini, T. Cucinotta, L. Abeni.
"Performance Modeling in Predictable Cloud Computing,"
in Proceedings of the
10th International Conference on Cloud Computing and Services Science (CLOSER 2020),
May 7-9, 2020, Prague, Czech Republic.
This paper deals with the problem of performance stability of software running in shared vir-
tualized infrastructures. The focus is on the ability to build an abstract performance model of
containerized application components, where real-time scheduling at the CPU level, along with
traffic shaping at the networking level, are used to limit the temporal interferences among co-
located workloads, so as to obtain a predictable distributed computing platform. A model for a
simple client-server application running in containers is used as a case-study, where an extensive
experimental validation of the model is conducted over a testbed running a modified OpenStack
on top of a custom real-time CPU scheduler in the Linux kernel.
See paper on publisher website