A decomposition approach for large virtual network embedding

TL;DR

This paper presents a novel decomposition-based integer linear programming approach with a column generation scheme and a Price-and-Branch heuristic to improve large virtual network embedding solutions in 5G network slicing.

Contribution

It introduces a new ILP formulation and a decomposition scheme with automatic partitioning, enhancing solution quality and scalability for large VNE problems.

Findings

Better lower bounds than existing methods.

Effective heuristic for large instances.

Improved solutions for resource-sparse scenarios.

Abstract

Virtual Network Embedding (VNE) is the core combinatorial problem of Network Slicing, a 5G technology which enables telecommunication operators to propose diverse service-dedicated virtual networks, embedded onto a common substrate network. VNE asks for a minimum-cost mapping of a virtual network on a substrate network, encompassing simultaneous node placement and edge routing decisions. On a benchmark of large virtual networks with realistic topologies we compiled, the state-of-the art heuristics often provide expensive solutions, or even fail to find a solution when resources are sparse. We introduce a new integer linear formulation together with a decomposition scheme based on an automatic partition of the virtual network. This results in a column generation approach whose pricing problems are also VNE problems. This method allows to compute better lower bounds than state-of-the-art methods. Finally, we devise an efficient Price-and-Branch heuristic for large instances.