HERO: Hierarchical Energy Optimization for Data Center Networks

Abstract

The rapid escalating power consumption has become critically important to modern data centers. Existing works on reducing the power consumption of network elements formulate the power optimization problem for a general network topology and require a centralized controller. As the scale of data centers increases, the complexity of solving this optimization problem increases rapidly. Inspired from the hierarchical data center network (DCN) topologies and data center traffic patterns, we design a two-level, pod-level, and core-level power optimization model, namely, Hierarchical EneRgy Optimization (HERO), to reduce the power consumption of network elements by switching off network switches and links while still guaranteeing full connectivity and maximizing link utilization. Given a physical DCN topology and a traffic matrix, we illustrate that two-level power optimizations in HERO fall in the class of capacitated multicommodity minimum cost flow (CMCF) problem, which is NP-hard. Therefore, we design several heuristic algorithms based on different switch elimination criteria to solve the proposed HERO optimization problem. The power-saving performance of the proposed HERO model is evaluated by several experiments with different traffic patterns. Our simulations demonstrate that HERO can reduce power consumptions of network elements effectively with reduced complexity.