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Virtual Network Embedding Based on Topology Potential.

Xinbo Liu1, Buhong Wang1, Zhixian Yang1

  • 1Information and Navigation college, Air Force Engineering University, Xi'an 710077, Shaanxi, China.

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|December 3, 2020
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Summary
This summary is machine-generated.

This study introduces a new virtual network embedding algorithm (VNE-TP) to enhance node matching. VNE-TP improves acceptance and revenue-to-cost ratios by optimizing physical node selection and pathfinding.

Keywords:
network virtualizationtopology potentialtopology potential entropyvirtual network embedding

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Area of Science:

  • Computer Science
  • Network Engineering
  • Optimization

Background:

  • Existing virtual network embedding (VNE) algorithms suffer from poor virtual-to-physical node mapping, leading to low acceptance and revenue-to-cost ratios.
  • The mismatch between virtual and physical resources hinders efficient network function virtualization (NFV) and software-defined networking (SDN) deployments.

Purpose of the Study:

  • To develop a novel VNE algorithm that addresses the limitations of current methods.
  • To improve the acceptance ratio and revenue-to-cost ratio in VNE.
  • To optimize the mapping of virtual nodes to physical nodes and virtual links to physical paths.

Main Methods:

  • Formulated a multi-objective optimization integer linear programming model for the VNE problem.
  • Proposed a two-stage virtual network embedding algorithm based on topology potential (VNE-TP).
  • Introduced a node embedding function using field theory for optimal physical node selection.
  • Developed a path embedding function considering bandwidth and hops for optimal path selection.

Main Results:

  • The VNE-TP algorithm demonstrated superior performance compared to existing VNE algorithms.
  • Significant improvements were observed in both acceptance ratio and revenue-to-cost ratio.
  • The node embedding stage effectively identified optimal physical nodes.
  • The link embedding stage successfully optimized path selection based on bandwidth and hops.

Conclusions:

  • The proposed VNE-TP algorithm effectively enhances virtual network embedding by improving node and link mapping.
  • VNE-TP offers a promising solution for increasing the efficiency and profitability of VNE.
  • The topology potential approach provides a robust framework for VNE optimization.