Frontiers of Information Technology & Electronic Engineering
>> 2016,
Volume 17,
Issue 7
doi:
10.1631/FITEE.1500494
Article
A virtual service placement approach based on improved quantum genetic algorithm Project 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), and the National High-Tech R&D Program (863) of China (Nos. 2015AA016102 and 2013AA013505)
. National Digital Switching System Engineering & Technological Research Center, Zhengzhou 450002, China.. Department of Mathematics and Computer Science, University of Antwerp, Antwerp 2020, Belgium
Available online: 2016-07-21
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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 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.
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