A virtual service placement approach based on improved quantum genetic algorithm

作     者：Gang XIONG Yu-xiang HU Le TIAN Ju-long LAN Jun-fei LI Qiao ZHOU 

作者机构：National Digital Switching System Engineering&Technological Research CenterZhengzhou 450002China Department of Mathematics and Computer ScienceUniversity of AntwerpAntwerp 2020Belgium 

出 版 物：《Frontiers of Information Technology & Electronic Engineering》 (信息与电子工程前沿（英文版）)

年 卷 期：2016年第17卷第7期

页      面：661-671页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 081104[工学-模式识别与智能系统] 0839[工学-网络空间安全] 0835[工学-软件工程] 0811[工学-控制科学与工程] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Basic Research Program(973)of China(Nos.2012CB315901 and 2013CB329104) the National Natural Science Foundation of China(Nos.61309019,61372121,61572519,and 61502530) the National High-Tech R&D Program(863)of China(Nos.2015AA016102 and 2013AA013505) 

主　　题：Software-defined networking(SDN) Network function virtualization Quantum genetic algorithm Middlebox 

摘      要：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 softwaredefined 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.