Approach for minimising network effect of VNF migration. Issue 20 (29th October 2018)

• Record Type: Journal Article
• Authors: Zhou, Xinhao; Yi, Bo; Wang, Xingwei; Huang, Min
• Is Part Of: IET communications. Volume 12:Issue 20(2018)
• Page Start: 2574
• Page End: 2581
• Publication Date: 2018-10-29
• Subjects: software defined networking -- virtual machines -- resource allocation -- virtualisation -- telecommunication network topology; software defined network environment -- network function virtualisation -- virtual machine migration -- virtual network function migration -- migration time -- migration cost -- network topology -- VNF migration -- migration effect -- network load -- network effect minimization -- network load balancing -- VNF; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2018.5188
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : In the software defined network (SDN) environment, network function virtualisation enables the virtual machine migration. Owing to the fact that transferring large amount of data will impede competing workflows, virtual network function (VNF) migration has brought a new perspective. Many optimised algorithms focusing on limiting migration time and migration cost have been proposed. In this study, the authors address the problem from a different perspective. They view the network topology from a global perspective and focus on the network effect of the whole network caused by VNF migration in the context of SDN. They introduce a parameter delay to formulate the network effect and an effect model is proposed to evaluate the migration effect of the network. In addition, a heuristic algorithm is proposed to minimise network effect while balancing network load and improving the service considering the migration cost and resources limit at the same time. The practicability and efficiency of the proposed model and algorithm are validated by simulation evaluation. By comparing their proposed algorithm with traditional benchmarks and closely related benchmarks, the experimental results show that their proposed algorithm largely reduces the network effect, while at the same time limiting the run time.