Virtual network function deployment strategy based on improved genetic simulated annealing algorithm in MEC

In order to effectively improve the end-to-end service delay of the flow in multi-clusters coexisting mobile edge computing (MEC) network,a virtual network function deployment strategy based on improved genetic simulated annealing algorithm was proposed.The delay of mobile service flow was mathemati...

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Bibliographic Details
Main Authors: Zhuo CHEN, Gang FENG, Yijing LIU, Yang ZHOU
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2020-04-01
Series:Tongxin xuebao
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Online Access:http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020074/
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Summary:In order to effectively improve the end-to-end service delay of the flow in multi-clusters coexisting mobile edge computing (MEC) network,a virtual network function deployment strategy based on improved genetic simulated annealing algorithm was proposed.The delay of mobile service flow was mathematically modeled through the open Jackson queuing network.After proving the NP attribute of this problem,a solution combining genetic algorithm and simulated annealing algorithm was proposed.In this strategy,the advance mapping mechanism avoids the possibility of network congestion,and the occurrence of local optima was avoided through using the methods of individual judgment and corrective genetic.Extensive simulation was set up to evaluate the effectiveness of the proposed strategy under different parameter settings,such as different volume of requests,different scale of service nodes,different number of MEC clusters,and logical link relationships between virtual network functions.Results show that this strategy can provide lower end-to-end services delay and better service experience for latency-sensitive mobile application.
ISSN:1000-436X