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A Machine Learning-Based Migration Strategy for Virtual Network Function Instances
With the growing demand for data connectivity, network service providers are faced with the task of reducing their capital and operational expenses while simultaneously improving network performance and addressing the increased demand.
Depth-Optimized Delay-Aware Tree (DO-DAT) for Virtual Network Function Placement
With the constant increase in demand for data connectivity, network service providers are faced with the task of reducing their capital and operational expenses while ensuring continual improvements to network performance.
Machine Learning for Performance-Aware Virtual Network Function Placement
The model takes several performance-related features from the network as an input and selects the placement of the various VNF instances on network servers with the objective of minimizing the delay between dependent VNF instances.
