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A virtual service placement approach based on improved quantum genetic algorithm

机译:一种基于改进量子遗传算法的虚拟服务放置方法

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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.
机译:尽管中间盒在引入新的网络功能方面发挥的关键作用,但它们对网络运营商的管理和创新仍然是严峻的挑战,因为基于硬件的传统中间盒缺乏服务灵活性和可扩展性。最近,虽然网络功能虚拟化(NFV)和软件定义网络(SDN)被视为非常有前途的驱动程序,但是如何为设计具有成本高效的中间箱服务架构,但如何保证传输效率的程度略微关注增加流量虚拟服务进程的条件。因此,我们专注于服务部署问题,以通过NFV和SDN的组合减少网络中的传输延迟。首先,框架设计用于服务放置决策,并且提出了一个整数线性编程模型来解决服务放置并最小化网络传输延迟。然后基于改进的量子遗传算法设计了启发式解决方案。实验结果表明,我们的提出方法可以自动计算最佳放置方案。与其他方案相比,我们的计划可以实现网络的整体运输延迟,并与随机放置方案相比减少平均交通运输延迟的30%。

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