Network function virtualization （NFV） is a newly proposed technique designed to construct and manage network fimctions dynamically and efficiently. Allocating physical resources to the virtual network function forwa...Network function virtualization （NFV） is a newly proposed technique designed to construct and manage network fimctions dynamically and efficiently. Allocating physical resources to the virtual network function forwarding graph is a critical issue in NFV. We formulate the forwarding graph embedding （FGE） problem as a binary integer programming problem, which aims to increase the revenue and decrease the cost to a service provider （SP） while considering limited network resources and the requirements of virtual functions. We then design a novel regional resource clustering metric to quantify the embedding potential of each substrate node and propose a topology-aware FGE algorithm called ＇regional resource clustering FGE＇ （RRC-FGE）. After implementing our algorithms in C＋＋, simulation results showed that the total revenue was increased by more than 50 units and the acceptance ratio by more than 15%, and the cost of the service provider was decreased by more than 60 units.展开更多
基金Project supported by the National Natural Science Foundation of China （Nos. 61309020 and 61521003）
文摘Network function virtualization （NFV） is a newly proposed technique designed to construct and manage network fimctions dynamically and efficiently. Allocating physical resources to the virtual network function forwarding graph is a critical issue in NFV. We formulate the forwarding graph embedding （FGE） problem as a binary integer programming problem, which aims to increase the revenue and decrease the cost to a service provider （SP） while considering limited network resources and the requirements of virtual functions. We then design a novel regional resource clustering metric to quantify the embedding potential of each substrate node and propose a topology-aware FGE algorithm called ＇regional resource clustering FGE＇ （RRC-FGE）. After implementing our algorithms in C＋＋, simulation results showed that the total revenue was increased by more than 50 units and the acceptance ratio by more than 15%, and the cost of the service provider was decreased by more than 60 units.
