HERO: Hierarchical Energy Optimization for Data Center Networks

Yan Zhang, Nirwan Ansari

Research output: Contribution to journalArticlepeer-review

39 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)406-415
Number of pages10
JournalIEEE Systems Journal
Issue number2
StatePublished - Jun 1 2015

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering


  • Data center networks (DCNs)
  • energy efficiency
  • green data centers
  • power optimization


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