4.7 Article

Energy and Network Aware Workload Management for Sustainable Data Centers with Thermal Storage

Journal

Publisher

IEEE COMPUTER SOC
DOI: 10.1109/TPDS.2013.278

Keywords

Data center; energy management; thermal storage; load scheduling; Lyapunov optimization

Funding

  1. U.S. National Science Foundation [ECCS-1129061, ECCS-1129062, CNS-1239274, CNS-1343356]
  2. Eckis Professor endowment at the University of Florida
  3. Direct For Computer & Info Scie & Enginr
  4. Division Of Computer and Network Systems [1239274] Funding Source: National Science Foundation
  5. Directorate For Engineering [1723849] Funding Source: National Science Foundation
  6. Directorate For Engineering
  7. Div Of Electrical, Commun & Cyber Sys [1129061] Funding Source: National Science Foundation
  8. Div Of Electrical, Commun & Cyber Sys [1723849] Funding Source: National Science Foundation
  9. Div Of Electrical, Commun & Cyber Sys
  10. Directorate For Engineering [1129062] Funding Source: National Science Foundation

Ask authors/readers for more resources

Reducing the carbon footprint of data centers is becoming a primary goal of large IT companies. Unlike traditional energy sources, renewable energy sources are usually intermittent and unpredictable. How to better utilize the green energy from these renewable sources in data centers is a challenging problem. In this paper, we exploit the opportunities offered by geographical load balancing, opportunistic scheduling of delay-tolerant workloads, and thermal storage management in data centers to facilitate green energy integration and reduce the cost of brown energy usage. Moreover, bandwidth cost variations between users and data centers are considered. Specifically, this problem is first formulated as a stochastic program, and then, an online control algorithm based on the Lyapunov optimization technique, called Stochastic Cost Minimization Algorithm (SCMA), is proposed to solve it. The algorithm can enable an explicit trade-off between cost saving and workload delay. Numerical results based on real-world traces illustrate the effectiveness of SCMA in practice.

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