Resource Aware Energy Efficiency Optimization by Using 6G Technology Based Advanced Virtual Multi-Purpose Embedding Algorithm

Abstract

Now a days, Network Technology is the one of the most important technology, which is used to resolve the shortcomings including network ossification of the current design of the internet. Because of adopted digital business growth Internet becomes success and it increased the competition for bandwidth in the communication. Ultra-high-definition videos and vehicle systems require more bandwidth rates and increase the network connection capacity respectively. The rapid advancement of network visualization and 6G technologies is driven by high bandwidth and high speed parallel communication. This often introduces a new link allocation problems to existing substrate networks in a network visualization environment. In order to solve this far reaching network effects, this paper proposes a new model called Advanced Virtual Multi-Purpose Network Embedding Algorithm (AVMPNEA). In this AVMPNEA model uses clustering method. Clustering is a learning algorithm. The clustering is a process which integrally evaluates the topological node structure, the latency and the related bandwidth between the nodes. The nodes the longevity which are used for selected mapping. Here, the result shows that the proposed AVMPNEA model is better in comparison with other models. In which throughput is high, latency is low and reduction of energy consumption. Hence, this model improves the throughput and the long-term application support.