Improving virtual host efficiency through resource and interference aware scheduling

Modern Infrastructure-as-a-Service Clouds operate in a competitive environment that caters to any user's requirements for computing resources. The sharing of the various types of resources by diverse applications poses a series of challenges in order to optimize resource utilization while avoiding performance degradation caused by application interference. In this paper, we present two scheduling methodologies enforcing consolidation techniques on multicore physical machines. Our resource-aware and interference-aware scheduling schemes aim at improving physical host efficiency while preserving the application performance by taking into account host oversubscription and the resulting workload interference. We validate our fully operational framework through a set of real-life workloads representing a wide class of modern cloud applications. The experimental results prove the efficiency of our system in optimizing resource utilization and thus energy consumption even in the presence of oversubscription. Both methodologies achieve significant reductions of the CPU time consumed, reaching up to 50%, while at the same time maintaining workload performance compared to widely used scheduling schemes under a variety of representative cloud platform scenarios.