Earticle

초록

영어

Virtual Machine Placement (VMP) is regarded as an important criterion to improve resource utilization and reduce energy consumption for cloud data centers. The existing VMP schemes simply set the VM resource requirements fixed values and ignore their fluctuation characteristics. Assuming normal distribution resource requirements, we firstly present a model for data centers based on a more accurate energy consumption model for single machine. Then, an effective genetic algorithm is adopted to solve this model. In the algorithm, some important issues, such as the number of population, fitness function and calculating method of energy consumption are discussed. In the end, we validate our method by experiments.

목차

Abstract
 1. Introduction
 2. Energy Consumption Optimization Model for Data Center
  2.1. Energy Model of PM
  2.2 Energy Optimization Model for Data Center
 3. Genetic-Based Algorithm
  3.1 Genome Encoding
  3.2 Genetic Operators
  3.3 Fitness Function
 4. Experiments and Analysis
  4.1 Parameter Values and Experimental Environment
  4.2 Benefits from Probability Distribution
  4.3 Effectiveness of GA
 5. Conclusion
 References

키워드

저자

• Ye Heng-zhou [ College of Electrical Engineering, Guangxi University, Nanning, China / College Of Information Science and Engineering , Guilin University Of Technology, Guilin, China ]
• Li Tao-shen [ School of Information and Engineering, Guangxi University, Nanning ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605