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CLC number: TP393

On-line Access: 2016-07-05

Received: 2015-11-10

Revision Accepted: 2016-02-16

Crosschecked: 2016-06-09

Cited: 5

Clicked: 8618

Citations:  Bibtex RefMan EndNote GB/T7714


Gang Xiong


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Frontiers of Information Technology & Electronic Engineering  2016 Vol.17 No.7 P.661-671


A virtual service placement approach based on improved quantum genetic algorithm

Author(s):  Gang Xiong, Yu-xiang Hu, Le Tian, Ju-long Lan, Jun-fei Li, Qiao Zhou

Affiliation(s):  National Digital Switching System Engineering & Technological Research Center, Zhengzhou 450002, China; more

Corresponding email(s):   xg1226@126.com

Key Words:  Software-defined networking (SDN), Network function virtualization, Quantum genetic algorithm, Middlebox

Gang Xiong, Yu-xiang Hu, Le Tian, Ju-long Lan, Jun-fei Li, Qiao Zhou. A virtual service placement approach based on improved quantum genetic algorithm[J]. Frontiers of Information Technology & Electronic Engineering, 2016, 17(7): 661-671.

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A1 - Gang Xiong
A1 - Yu-xiang Hu
A1 - Le Tian
A1 - Ju-long Lan
A1 - Jun-fei Li
A1 - Qiao Zhou
J0 - Frontiers of Information Technology & Electronic Engineering
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.1500494

Despite the critical role that middleboxes play in introducing new network functionality, management and innovation of them are still severe challenges for network operators, since traditional middleboxes based on hardware lack service flexibility and scalability. Recently, though new networking technologies, such as network function virtualization (NFV) and software-defined networking (SDN), are considered as very promising drivers to design cost-efficient middlebox service architectures, how to guarantee transmission efficiency has drawn little attention under the condition of adding virtual service process for traffic. Therefore, we focus on the service deployment problem to reduce the transport delay in the network with a combination of NFV and SDN. First, a framework is designed for service placement decision, and an integer linear programming model is proposed to resolve the service placement and minimize the network transport delay. Then a heuristic solution is designed based on the improved quantum genetic algorithm. Experimental results show that our proposed method can calculate automatically the optimal placement schemes. Our scheme can achieve lower overall transport delay for a network compared with other schemes and reduce 30% of the average traffic transport delay compared with the random placement scheme.




Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article


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