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Energy-Aware Service Job Scheduling in Data Center with Distributed UPS and Renewable Energy

Ranjbar, Behnaz | 2014

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 46580 (19)
  4. University: Sharif University of Technology
  5. Department: Computer Engineering
  6. Advisor(s): Goudarzi, Maziar
  7. Abstract:
  8. Recently, The Earth has become warm rapidly over the past few years. This global warming is not only caused by natural phenomena, and further increased by humans and the amount of greenhouse gases in the atmosphere. Around 40 to 50 percent of energy consumption is related to information technology and communications. However, the rapid growth of electricity consumption in data centers, in addition to increased costs, data center challenges faced serious environmental pollution and more greenhouse gases. Use of renewable energy and reducing electricity costs in data centers are the important subjects for researchers around the world. Many researchers provide solutions to reduce environmental pollution in data centers and increase profits by reducing costs, especially electricity costs. One of the solutions to this problem is the smart and efficient use of renewable energies. A data center during the day performs a lot of Jobs including service and batch. Service jobs require to do in specified time and should not be delayed but batch jobs can be delayed. In this work we proposed service job scheduler with fixed policy for batch jobs for data center powered by solar energy and brown energy to reduce energy cost. We use UPS battery for energy storage for more cost optimization. We implement Simulated Annealing and Best Fit for scheduling jobs but they are not appropriate for on-line scheduler. Finally an optimization method based on mathematical equation is proposed. One of the goals of our scheduler is to maximize the service level agreement. The experimental results show that our method is very faster than SA and more appropriate for on-line scheduling and also has less energy cost
  9. Keywords:
  10. Batch Job ; Data Center ; Renewable Energy Resources ; Uninterruptible Power Supplies ; Energy Aware ; Online Jobs ; Service Jobs

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