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Energy Conservation Using Dynamic Voltage Frequency Scaling for Computational Cloud.

A Paulin Florence1, V Shanthi2, C B Sunil Simon3

  • 1Sathyabama University, Chennai 600 119, India; St. Joseph's Institute of Technology, Chennai 600 119, India.

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Summary
This summary is machine-generated.

This study introduces a cloud computing method to analyze computational requests and optimize power usage. By calculating time complexity and adjusting CPU frequency with Dynamic Voltage and Frequency Scaling (DVFS), energy savings of up to 55% are achieved.

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Area of Science:

  • Computer Science
  • Cloud Computing
  • Energy Efficiency

Background:

  • Cloud computing enables resource sharing on a pay-as-you-go basis, offering services like SaaS, IaaS, and PaaS.
  • Efficiently serving computational requests with optimal power utilization is crucial in Infrastructure as a Service (IaaS).
  • Existing methods for power reduction in cloud environments include various algorithms and Dynamic Voltage and Frequency Scaling (DVFS).

Purpose of the Study:

  • To devise a methodology for analyzing cloud computational requests to improve power efficiency.
  • To optimize resource allocation and energy consumption within cloud infrastructure.

Main Methods:

  • Analyzing cloud request behavior to identify associated algorithms.
  • Calculating time complexity using asymptotic notations.
  • Employing a best-fit strategy for host allocation and job assignment.
  • Measuring required clock frequency based on calculated time complexity.
  • Utilizing Dynamic Voltage and Frequency Scaling (DVFS) to adjust CPU frequency for power saving.

Main Results:

  • Successful identification of algorithm types for cloud requests.
  • Accurate calculation of time complexity for incoming jobs.
  • Efficient host selection and job allocation using the best-fit strategy.
  • Demonstrated energy savings of up to 55% of total power consumption through CPU frequency scaling.

Conclusions:

  • The proposed methodology effectively analyzes cloud requests and optimizes power consumption.
  • Dynamic Voltage and Frequency Scaling (DVFS), guided by time complexity analysis, significantly enhances energy efficiency in cloud computing.
  • This approach offers a practical solution for reducing the environmental impact and operational costs of cloud data centers.