Equinox: Adaptive network reservation in the Cloud

Most of today´s public cloud services provide dedicated compute and memory resources but they do not provide any dedicated network resources. The shared network can be a major cause of the well known “noisy neighbor” problem, which is a growing concern in public cloud services like Amazon EC2. Network reservations, therefore, are of prime importance for the Cloud. However, a tenant´s network demand would usually keep changing over time and thus, a static one-time reservation would either lead to poor performance or resource wastage (and higher cost). In this context, we present Equinox - a system that automatically reserves end-to-end bandwidth for a tenant based on the predicted demand and adapts this reservation with time. We leverage flow monitoring support in virtual switches to collect flow data that helps us predict demand at a future time. We use a combination of vswitch based rate-limiting and OpenFlow based flow rerouting to provision end-to-end bandwidth requirements. We have implemented Equinox in an OpenStack environment with OpenFlow based network control. Our experimental results, using traces based on Facebook´s production data centers, show that Equinox can provide up to 47% reduction in bandwidth cost as compared to a static reservation scheme while providing the same efficiency in terms of flow completion times.