Abstract
At present, network virtualization is an essential technology that aims to resolve shortcomings including network ossification of the current design of the Internet. The Internet's tremendous success have adopted digital business growth and increased competition for bandwidth in communication. Ultra-high-definition videos and vehicle systems require rapid bandwidth rates and increase network connection capacity, respectively. The rapid advancement of network virtualization and 6G technologies is driven by high bandwidth and high speed parallel communication. This innovation often introduces new link allocation problems to existing substrate networks in a network virtualization environment. In order to solve this far-reaching network effects, this paper proposes an Advanced Virtual Multi-Purpose Network Embedding Algorithm (AVMPNEA) through the fuzzy C-mean clustering, which is a learning algorithm. The clustering integrally evaluates the topological node structure, the latency and the related bandwidth between the nodes. The Nodes that enhance the longevity are used for selected mapping. The experimental result shows that the proposed AVMPNEA is outperformed in comparison with other traditional methods with high throughput, low latency and reduced energy consumption. Hence, it improves the throughput and the long-term application support.