Scaling-up versus scaling-out networking in data centers: a comparative robustness analysis

The information and communication technology nowadays more than ever depends on the Internet and cloud computing, so that the data centers (DCs) have been converted to a constitutive unit of the cloud computing. A DC is composed of two primary parts: servers and Data Center Networks (DCNs). Robustness and scalability are two major challenges of the DCNs that are expanded based on two strategies, scale-out, and scale-up. This paper is distinctive from the related studies in two aspects. The first one is to simultaneously focus on both the scalability and the robustness challenges of the DCNs. For this purpose, we will concentrate on the comparison of robustness in the scalable models of these networks. The second one is, despite the previous work that only evaluated the DCN robustness under topological changes, we evaluated the robustness and fault tolerance against three types of unexpected changes in topology, traffic, and COI (community of interest) in the present work. Hence, we have chosen the network criticality (NC) as a graph-theoretic metric for analyzing DCN robustness. Afterward, we compare some structural and spectral graph metrics with NC among some well-known DCNs, and their scale-out and scale-up. Our results are useful to select the appropriate scaling strategy with the goal of maximizing the robustness of existing DCNs and provide a guideline for designing the new robust and scalable DCN.