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Self-similarity: Behind workload reshaping and prediction

机译:自我相似性:工作量重塑和预测的背后

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摘要

Energy efficiency has become one of the most important challenges in designing future computing systems. Workload reshaping and prediction have a significant impact on the energy conservation of computer components. In this paper, by using three HTTP traffic traces, we perform various evaluations to explore the possible reasons and indications which impact the workload reshaping and prediction. The experimental results indicate that the principles of reshaping workload to improve prediction quality are constructing or improving the self-similarity of the reshaped workloads.
机译:能源效率已成为设计未来计算系统的最重要挑战之一。工作量重塑和预测对计算机组件的节能有重要影响。在本文中,通过使用三个HTTP流量跟踪,我们进行了各种评估,以探索可能影响工作量重塑和预测的原因和指示。实验结果表明,重塑工作量以提高预测质量的原理正在构建或改善重塑工作量的自相似性。

著录项

  • 来源
    《Future generation computer systems》 |2012年第2期|p.350-357|共8页
  • 作者单位

    Department of Computer Science, Jinan University, 510632 Guangzhou, Guangdong Province, PR China;

    Department of Computer Science, Jinan University, 510632 Guangzhou, Guangdong Province, PR China;

    Department of Computer Science, Jinan University, 510632 Guangzhou, Guangdong Province, PR China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    workload shaper; time series; prediction; self-similarity;

    机译:工作量整形器;时间序列;预测;自相似;
  • 入库时间 2022-08-18 02:17:05

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