Abstract
To improve the low acceptance ratio and revenue to cost ratio caused by the poor match between the virtual nodes and the physical nodes in the existing virtual network embedding (VNE) algorithms, we established a multi-objective optimization integer linear programming model for the VNE problem, and proposed a novel two-stage virtual network embedding algorithm based on topology potential (VNE-TP). In the node embedding stage, the field theory once used for data clustering was introduced and a node embedding function designed to find the optimal physical node. In the link embedding stage, both the available bandwidth and hops of the candidate paths were considered, and a path embedding function designed to find the optimal path. Extensive simulation results show that the proposed algorithm outperforms other existing algorithms in terms of acceptance ratio and revenue to cost ratio.
Highlights
In recent years, network virtualization technology has mainly been of academic interest
Inspired by the above theory, we introduced the field theory into the virtual network embedding (VNE) process and used the topology potential to measure the topology importance of nodes
A novel virtual network embedding algorithm based on topology potential (VNE-TP) is proposed
Summary
Network virtualization technology has mainly been of academic interest. First, the authors define several attributes of nodes from both local and global perspectives, and use a multi-criteria decision analysis method to rank the nodes in the network In this way, the most appropriate physical nodes will be selected to host the virtual nodes, which will facilitate subsequent link embedding. To describe the topology importance of a node in a network from a global perspective, a new topological attribute named “node topology potential” is defined, which can be utilized to further improve the embedding performance of VNRs. A novel virtual network embedding algorithm based on topology potential (VNE-TP) is proposed.
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