Acta Metallurgica Sinica(English letters) ›› 2014, Vol. 21 ›› Issue (3): 62-70.doi: 10.1016/S1005-8885(14)60302-2

• Networks • Previous Articles     Next Articles

Virtual machine placement optimizing to improve network performance in cloud data centers

董健康 王洪波 李阳阳 程时端   

  1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2013-10-21 Revised:2014-04-08 Online:2014-06-30 Published:2014-06-30
  • Contact: Jiankang Dong
  • Supported by:

    This work was supported by the National Natural Science Foundation of China (61002011); the National High Technology Research and Development Program of China (863 Program) (2013AA013303); the Fundamental Research Funds for the Central Universities (2013RC1104); the Natural Science Foundation of Gansu Province, China (1308RJZA306); the Open Fund of the State Key Laboratory of Software Development Environment (SKLSDE- 2009KF-2-08).


With the wide application of virtualization technology in cloud data centers, how to effectively place virtual machine (VM) is becoming a major issue for cloud providers. The existing virtual machine placement (VMP) solutions are mainly to optimize server resources. However, they pay little consideration on network resources optimization, and they do not concern the impact of the network topology and the current network traffic. A multi-resource constraints VMP scheme is proposed. Firstly, the authors attempt to reduce the total communication traffic in the data center network, which is abstracted as a quadratic assignment problem; and then aim at optimizing network maximum link utilization (MLU). On the condition of slight variation of the total traffic, minimizing MLU can balance network traffic distribution and reduce network congestion hotspots, a classic combinatorial optimization problem as well as NP-hard problem. Ant colony optimization and 2-opt local search are combined to solve the problem. Simulation shows that MLU is decreased by 20%, and the number of hot links is decreased by 37%.

Key words:

cloud computing, data center network, virtual machine placement, traffic engineering, network performance