网络与信息安全学报 (Aug 2018)
5G network slicing function migration mechanism based on particle swarm optimization algorithm
Abstract
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.
