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Bin-Packing scheduling of delay tolerant tasks for zero-carbon data centers
  • +4
  • Yunfeng Peng,
  • Wenjie Si,
  • Yuhang Zou,
  • Yunhao Zhang,
  • Xueying Zhai,
  • Xiuping Guo,
  • Wei Zhang
Yunfeng Peng
University of Science and Technology Beijing

Corresponding Author:pengyf@ustb.edu.cn

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Wenjie Si
University of Science and Technology Beijing
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Yuhang Zou
University of Science and Technology Beijing
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Yunhao Zhang
University of Science and Technology Beijing
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Xueying Zhai
University of Science and Technology Beijing
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Xiuping Guo
Beijing University of Posts and Telecommunications School of Economics and Management
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Wei Zhang
Qilu University of Technology
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Abstract

Currently, the electricity to run cloud computers is usually generated from fossil fuels (e.g., petroleum, natural gas), which will cause carbon pollution. Therefore, data centers, as places to accommodate cloud computers, are now facing a serious problem of high carbon pollution. In this letter, an operational method is proposed to achieve zero-carbon data centers by carefully matching delay tolerant tasks to computing resources (e.g., CPU) when zero-carbon electricity (wind and solar energy) is available. We designed a unified measurement called CPU×Time, by which the complex matching problem involving tasks, computing resources, and zero-carbon electricity is simplified into a bin-packing scheduling. Simulations show that the proposed bin-packing scheduling method can achieve high resource utilization without carbon pollution.