Abstract
With the increase of network scale and the complexity of network structure, the problems of traditional Internet have emerged. At the same time, the appearance of network function virtualization (NFV) and network virtualization technologies has largely solved this problem, they can effectively split the network according to the application requirements, and flexibly provide network functions when needed. During the development of virtual network, how to improve network performance, including reducing the cost of embedding process and shortening the embedding time, has been widely concerned by the academia. Combining genetic algorithm with virtual network embedding problem, this paper proposes a genetic correlation multi-domain virtual network embedding algorithm (GCMD-VNE). The algorithm improves the natural selection stage and crossover stage of genetic algorithm, adds more accurate selection formula and crossover conditions, and improves the performance of the algorithm. Simulation results show that, compared with the existing algorithms, the algorithm has better performance in terms of embedding cost and embedding time.
Highlights
In recent years, the Internet plays a more and more important role in people’s lives and creates great value for the development of society
In the second part, based on the existing genetic algorithm and the cross-domain embedding algorithm, we propose a genetic correlation multi-domain virtual network embedding algorithm (GCMD-VNE), the main steps of our algorithm are as follows
In literature [37], a virtual network model based on genetic algorithm is proposed, which applies the genetic algorithm to the problem of virtual network embedding and maps the virtual network requests to the infrastructure providers managing the substrate network
Summary
The Internet plays a more and more important role in people’s lives and creates great value for the development of society. Many literatures have proposed many methods to solve the single domain embedding problem of virtual networks [3]–[5]. In the cross-domain embedding process of virtual networks, many users constantly request the substrate networks to use its underlying resources. The goal of VNE problem is to find a better embedding scheme under resource constraints, which maps as many virtual request networks as possible to the substrate networks and occupies as few substrate resources as possible. For this reason, this paper proposed a Genetic Correlation Multi-Domain Virtual Network Embedding Algorithm: GCMD.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
