Full Text:   <1155>

Summary:  <365>

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: 2527

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Gang Xiong

http://orcid.org/0000-0002-4249-6820

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

10.1631/FITEE.1500494


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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Abstract: 
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.

一种基于改进量子遗传算法的虚拟服务部署方法

目的:在软件定义网络和网络功能虚拟化技术不断推动网络功能服务演进和创新的同时,如何降低网络业务流量在接受服务处理时的传输时延,进而提高网络整体传输效率并降低带宽资源消耗,成为业界关注的一个新方向。
创新点:文章对当前正不断兴起的网络虚拟服务部署场景进行具体分析,提出了基于整数规划的服务部署优化模型,并利用改进的量子遗传算法对模型求解,有效提高了网络在提供服务处理时的整体传输效率。
方法:首先,对网络虚拟服务的部署场景进行具体分析,将影响业务流量传输时延的因素与网络拓扑结构和服务部署位置相关联。其次,基于网络拓扑结构和服务位置变量参数,利用整数规划模型对服务位置优化部署问题进行建模。然后,针对服务优化部署模型所涉及的NP-hard问题,提出利用改进型的量子遗传算法进行启发式模型求解。最后,实验结果表明,本文方法在降低网络整体传输时延的同时,具有较小的计算时间代价(图7、8);与随机部署策略相比,本文方法可平均降低业务流量的传输时延约30%(图9、10),从而更加有效地保障了网络传输效率。
结论:针对新型网络体系(如软件定义网络和网络功能虚拟化)中虚拟服务场景,提出了一种优化的网络服务部署方法,有效降低了业务流量接受服务处理时的传输时延。

关键词:软件定义网络;网络功能虚拟化;量子遗传算法;网络中间件

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