The topic of network-aware job placement in datacenter environments has attracted lots of research attention recently. Since network bandwidth is sometimes a scarce resource in multi-tenant datacenters, several virtualization abstractions have been proposed to avoid oversubscription of datacenter networks, and provide predictable QoS performance for users. In my work, a simulation environment is built to study job placement and scheduling strategies in datacenter networks. In particular, I model
the Temporally-Interleaved Virtual Cluster (TIVC) algorithm, and study its sensitivity to different job characteristics and how the configured network capacity affects the system performance.
The simulation results indicate that careful management of a delay queue for pending jobs can help achieve high system utilization. Different workload models have a pronounced influence on the system performance. In addition, an anomaly is found under certain datacenter network configurations, wherein increasing the datacenter resources produces "worse" system performance. Further investigation provides an explanation for this counter-intuitive result.