Minimizing electricity cost: optimization of distributed internet data centers in a multi-electricity-market environment

  • Authors:

  • Lei Rao;Xue Liu;Le Xie;Wenyu Liu

  • Affiliations:

  • Department of EI, WNLO, Huazhong University of Science and Technology, Wuhan, China and School of Computer Science, McGill University, Montreal, Canada;School of Computer Science, McGill University, Montreal, Canada;Department of ECE, Texas A&M University, College Station;Department of EI, WNLO, Huazhong University of Science and Technology, Wuhan, China

  • Venue:
  • INFOCOM'10 Proceedings of the 29th conference on Information communications
  • Year:
  • 2010

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Abstract

The study of Cyber-Physical System (CPS) has been an active area of research. Internet Data Center (IDC) is an important emerging Cyber-Physical System. As the demand on Internet services drastically increases in recent years, the power used by IDCs has been skyrocketing. While most existing research focuses on reducing power consumptions of IDCs, the power management problem for minimizing the total electricity cost has been overlooked. This is an important problem faced by service providers, especially in the current multi-electricity market, where the price of electricity may exhibit time and location diversities. Further, for these service providers, guaranteeing quality of service (i.e. service level objectives-SLO) such as service delay guarantees to the end users is of paramount importance. This paper studies the problem of minimizing the total electricity cost under multiple electricity markets environment while guaranteeing quality of service geared to the location diversity and time diversity of electricity price. We model the problem as a constrained mixed-integer programming and propose an efficient solution method. Extensive evaluations based on reallife electricity price data for multiple IDC locations illustrate the efficiency and efficacy of our approach.