Optimal offline virtual network embedding with rent-at-bulk aspects

TL;DR

This paper presents an optimal offline virtual network embedding approach that incorporates rent-at-bulk economies of scale using a mixed-integer linear programming model, improving resource allocation efficiency.

Contribution

It introduces a novel MILP formulation for VNE that explicitly models rent-at-bulk costs and compares it to a baseline ignoring these costs during embedding.

Findings

The proposed model achieves optimal solutions considering rent-at-bulk.

Directly incorporating rent-at-bulk improves resource utilization.

The approach is computationally viable for realistic problem sizes.

Abstract

Network virtualization techniques allow for the coexistence of many virtual networks (VNs) jointly sharing the resources of an underlying substrate network. The Virtual Network Embedding problem (VNE) arises when looking for the most profitable set of VNs to embed onto the substrate. In this paper, we address the offline version of the problem. We propose a Mixed-Integer Linear Programming formulation to solve it to optimality which accounts for acceptance and rejection of virtual network requests, allowing for both splittable and unsplittable (single path) routing schemes. Our formulation also considers a Rent-at-Bulk (RaB) model for the rental of substrate capacities where economies of scale apply. To better emphasize the importance of RaB, we also compare our method to a baseline one which only takes RaB into account a posteriori, once a solution to VNE, oblivious to RaB, has been found. Computational experiments show the viability of our approach, stressing the relevance of addressing RaB directly with an exact formulation