Achieving energy-proportionality in fat-tree DCNs

Fat-tree is a popular topology for data center networks (DCNs). Many recent papers propose new energy-efficient techniques that reduce the power consumption of fat-tree DCNs by dynamically powering off idle network switches and links. However, fat-tree DCNs adopting those techniques still consume a significant amount of energy even when lightly loaded. In this paper, we examine the approach of merging traffic in a fat-tree DCN in order to consolidate the traffic into fewer switches. We first derive an analytical model for the lower-bound of active switches required in a fat-tree DCN as a function of load, assuming traffic merging. Then we formulate a power optimization model and propose a scalable heuristic algorithm to find the minimum subset of network switches and links that satisfies a variety of traffic patterns and loads in actual DCNs. Simulation results show that our approach can substantially reduce the number of active switches and lower the energy consumption of a fat-tree DCN when the load is light. We show that our solution achieves near energy proportionality.