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Server Consolidation Based on Culture Multiple-Ant-Colony Algorithm in Cloud Computing.

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This summary is machine-generated.

This study introduces a novel algorithm for dynamic server consolidation in data centers. The culture multiple-ant-colony algorithm effectively reduces energy consumption and virtual machine migrations.

Keywords:
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Area of Science:

  • Computer Science
  • Artificial Intelligence
  • Energy Efficiency

Background:

  • High energy consumption in data centers is a critical global issue.
  • Dynamic server consolidation, including virtual machine migration, offers a promising solution for energy savings.
  • Current challenges lie in optimizing virtual machine placement for reduced energy usage.

Purpose of the Study:

  • To propose a novel server consolidation algorithm for dynamic virtual machine migration.
  • To reduce the energy consumption of cloud data centers through optimized resource allocation.
  • To minimize the number of virtual machine migrations while achieving energy efficiency.

Main Methods:

  • Development of a server consolidation algorithm based on the culture multiple-ant-colony algorithm (CMACA).
  • Implementation of dynamic virtual machine migration strategies.
  • Utilizing a specific target function to find an approximate optimal solution for consolidation.

Main Results:

  • The proposed CMACA algorithm significantly reduces data center energy consumption.
  • The algorithm also leads to a decrease in the total number of virtual machine migrations.
  • Simulation results validate the effectiveness of the CMACA approach.

Conclusions:

  • The CMACA algorithm presents an effective method for dynamic server consolidation.
  • This approach contributes to more energy-efficient cloud data center operations.
  • The study demonstrates a dual benefit of reduced energy use and fewer migrations.