Dynamic Load Balancing in Hybrid Switching Data Center Networks with Converters

Abstract

Today's data centers rely on scale-out architectures like fat-tree, BCube, VL2, etc. to connect a large number of commodity servers. It's important to balance the traffic load across the available links. Since the traditional electrical network cannot perfectly respond to the traffic variations in data centers, a growing trend is to introduce converters with adjustable optical links instead of adding more wiring links. However, little is known today about how to fully exploit the potential of the flexibility from the converters: the joint optimization on adjusting the optical links inside the converters and the routing in the whole network remains algorithmically challenging. In this paper, we initiate the study of dynamic load balancing problem (DLBP) in hybrid switching data center networks with converters. We design a set of specific converters for Diamond, VL2, BCube topologies to introduce more flexibility. Based on it, the connections of the optical links inside the converter and the route for each flow needs to be jointly optimized to minimize the maximum link utilization in the whole network. We formulate DLBP as an optimization program and prove that it's not only NP-hard, but also ρ-inapproximation. Further, we design a greedy algorithm to solve it. Extensive experiments show that our algorithm can reduce the traffic congestion by 12% on average.