Understanding data center network architectures in virtualized environments: A view from multi-tier applications

In recent years, data center network (DCN) architectures (e.g., DCell [11], FiConn [14], BCube [10], FatTree [1], and VL2 [8]) received a surge of interest from both the industry and academia. However, evaluation of these newly proposed DCN architectures is limited to MapReduce or scientific computing type of traffic patterns, and none of them provides an in-depth understanding of their performance in conventional transaction systems under realistic workloads. Moreover, it is also unclear how these architectures are affected in virtualized environments. In this paper, we fill this void by conducting an experimental evaluation of FiConn and FatTree, each respectively as a representative of hierarchical and flat architectures, in a clustered three-tier transaction system using a virtualized deployment. We evaluate these two architectures from the perspective of application performance and explicitly consider the impact of server virtualization. Our experiments are conducted in two major testing scenarios, service fragmentation and failure resilience, from which we observe several fundamental characteristics that are embedded in both classes of network topologies and cast a new light on the implication of virtualization in DCN architectures. Issues observed in this paper are generic and should be properly considered in any DCN design before the actual deployment, especially in mission-critical real-time transaction