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Guaranteeing performance based on time-stability for energy-efficient data centers

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  • Soongeol Kwon
  • Natarajan Gautam

Abstract

We consider a system of multiple parallel single-server queues where servers are heterogeneous with resources of different capacities and can be powered on or off while running at different speeds when they are powered on. In addition, we assume that application requests are heterogeneous with different workload distributions and resource requirements and the arrival, rates of request are time-varying. Managing such a heterogeneous, transient, and non-stationary system is a tremendous challenge. We take an unconventional approach, in that we force the queue lengths in each powered-on server to be time-stable (i.e., stationary). It allows the operators to guarantee performance and effectively monitor the system. We formulate a mixed-integer program to minimize energy costs while satisfying time-stability. Simulation results show that our suggested approach can stabilize queue length distributions and provide probabilistic performance guarantees on waiting times.

Suggested Citation

  • Soongeol Kwon & Natarajan Gautam, 2016. "Guaranteeing performance based on time-stability for energy-efficient data centers," IISE Transactions, Taylor & Francis Journals, vol. 48(9), pages 812-825, September.
    • Handle: RePEc:taf:uiiexx:v:48:y:2016:i:9:p:812-825
    DOI: 10.1080/0740817X.2015.1126003
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    Cited by:

    1. Yongkyu Cho & Young Myoung Ko, 2020. "Stabilizing the virtual response time in single-server processor sharing queues with slowly time-varying arrival rates," Annals of Operations Research, Springer, vol. 293(1), pages 27-55, October.
    2. Kwon, Soongeol, 2020. "Ensuring renewable energy utilization with quality of service guarantee for energy-efficient data center operations," Applied Energy, Elsevier, vol. 276(C).
    3. Alexander Zeifman & Yacov Satin & Ivan Kovalev & Rostislav Razumchik & Victor Korolev, 2020. "Facilitating Numerical Solutions of Inhomogeneous Continuous Time Markov Chains Using Ergodicity Bounds Obtained with Logarithmic Norm Method," Mathematics, MDPI, vol. 9(1), pages 1-20, December.

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