Chinese Journal of Network and Information Security ›› 2018, Vol. 4 ›› Issue (8): 47-55.doi: 10.11959/j.issn.2096-109x.2018066

• Papers • Previous Articles     Next Articles

5G network slicing function migration mechanism based on particle swarm optimization algorithm

Qiang CHEN1,2(),Caixia LIU1,2,Lingshu LI1,2   

  1. 1 National Digital Switching System Engineering and Technological R&D Center,Zhengzhou 450002,China
    2 National Engineering Laboratory for Mobile Network Security,Beijing 100876,China
  • Revised:2018-07-06 Online:2018-08-01 Published:2018-10-12
  • Supported by:
    The National High Technology Research and Development Program of China (863 Program)(2014AA01A701);The National Natural Science Foundation of China(61521003);Ministry of Science and Technology Support Plan(2014BAH30B01)


In multi-application scenarios of 5G,data traffic often increases dramatically.Virtual machine resources in network slicing may not meet the normal needs of users.In view of this,a network slicing function migration mechanism aiming at load balancing was proposed.The mechanism simulates the virtual machine into particles based on particle swarm optimization algorithm.In the process of migration,all particles were divided into several subgroups,and particle swarm optimization algorithm was applied within and among groups.According to the historical optimal solution and the current global optimal solution,the particle location was updated,and the best target particles were determined by selecting the smaller particle size of the particle in real time.The mechanism not only improves the convergence speed,but also improves the accuracy of the algorithm.Compared with other migration methods,the results show that the proposed migration mechanism has the advantages of high accuracy and fast convergence.And it can also improve the efficiency of resource utilization,reduce the energy consumption of data center,and has better adaptability.

Key words: function migration, particle swarm optimization algorithm, network slicing, 5G

CLC Number: 

No Suggested Reading articles found!