Network Slicing Algorithms Case Study:Virtual Network Embedding

Abstract

In the 5G telecommunication network, one promising technique is network slicing. The network slicing technique enables infrastructure service providers to create end-to-end virtual networks from radio access network to the core network. This virtual network consists of abstracted functions and resources. One of the network slicing issues is how to efficiently allocate virtual network resources on the substrate network. This can affect network performance in general. Resource allocation is strongly influenced by algorithm and computation time in mapping virtual networks into substrate networks and it is important to note because this affects service quality and profit for infrastructure service providers. From several studies conducted by the authors, the problem of resource allocation in network slicing can be transformed into an optimization problem. The optimization problem in network slicing is known as virtual network embedding (VNE). In this report, the authors test the virtual network embedding algorithms of GRC, MCTS, and RL to compare profit gain for infrastructure service providers using long-term average revenue metrics and computation time in mapping virtual network allocation. It can be concluded that for profit the RL algorithm is 1% better than GRC and MCTS. Meanwhile, the computation time of the GRC algorithm is faster than MCTS and RL.