Dynamic Allocation of Virtual Resources Based on Genetic Algorithm in the Cloud

  • Li DengEmail author
  • Li Yao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9464)


Cloud computing provides dynamic resource allocation using virtualization technology to greatly improve resource efficiency. However, current resource reallocation solution seldom considers the stability of VM placement pattern. Varied workloads of applications would lead to frequent resource reconfiguration requirements due to repeated occurrence of hot nodes. In this paper, a multi-objective genetic algorithm (MOGA) is presented to significantly improve the stability of VM placement pattern with less migration overhead. The group encoding scheme is employed in MOGA to express the mapping of physical nodes and virtual machines (VMs). Fitness function is designed based on the stability and migration overhead of group. Our simulation results demonstrate that, our MOGA is much more efficient than other algorithms for resource reallocation with good stability.


Cloud computing Resource allocation Genetic algorithm 



This research was funded by Natural Science Foundation of Hubei Province (No. 2014CFB817), China.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.College of Computer Science and TechnologyWuhan University of Science and TechnologyWuhanChina
  2. 2.Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial SystemWuhanChina

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