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Infrastructure aware heterogeneous-workloads scheduling for data center energy cost minimization

Haghshenas, K ; Sharif University of Technology | 2022

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  1. Type of Document: Article
  2. DOI: 10.1109/TCC.2020.2977040
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2022
  4. Abstract:
  5. A huge amount of energy consumption, the cost of this usage and environmental effects have become serious issues for commercial cloud providers. Solar energy is a promising clean energy source, to provide some portion of the Internet data center's (IDC's) energy usage which can reduce environmental effects and total energy costs. Moreover, due to the high energy consumption of the cooling system, considering cooling power in job scheduling can provide efficient solutions to reduce total energy consumption. In this article, we investigate the problem of minimizing the energy cost of an IDC and propose an algorithm which schedules heterogeneous IDC workloads, by considering available renewable energy, cooling subsystem, and electricity rate structure. We evaluate the effectiveness and feasibility of our algorithm using real and synthetic workload traces. The simulation results illustrate how our proposed solution reduces the data center's energy cost by up to 46 percent compared to previous solutions. Moreover, results show that our solution is capable of reducing energy cost of data centers under different weather conditions, and rate structures. © 2013 IEEE
  6. Keywords:
  7. Energy cost ; Free cooling ; Internet data center (IDC) ; Renewable energy ; Uninterruptible power supply ; Computer aided software engineering ; Cooling ; Cost reduction ; Energy utilization ; Green computing ; Meteorology ; Scheduling ; Solar energy ; Solar power generation ; Clean energy sources ; Electricity rate structure ; Heterogeneous workloads ; High energy consumption ; Internet data centers ; Renewable energies ; Synthetic workloads ; Total energy consumption ; Data reduction
  8. Source: IEEE Transactions on Cloud Computing ; Volume 10, Issue 2 , 2022 , Pages 972-983 ; 21687161 (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/9017981