Stochastic Optimization Models for Virtual Content Delivery Network Planning

Session : SS1-2 / SS1 : Challenging Mixed-Integer Problems in Network Optimization
Jeudi 11 février 15:00 - 16:40 Salle : CI2-06
Jocelyne Elias, Michele Mangili, Fabio Martignon et Antonio Capone

Content Delivery Networks (CDNs) have been identified as one of the relevant use cases where the emerging paradigm of Network Functions Virtualization (NFV) will likely be beneficial. In fact, virtualization fosters flexibility, since on-demand resource allocation of virtual CDN nodes can accommodate sudden traffic demand changes. However, there are cases where physical appliances should still be preferred, therefore we envision a mixed architecture in between these two solutions, capable to exploit the advantages of both of them. Motivated by these reasons, in this paper we formulate a novel, two-stage stochastic planning model that can be used by CDN operators to compute the optimal long-term network planning decision, deploying physical CDN appliances in the network and/or leasing resources for virtual CDN nodes in data centers. Since solving this model is computationally cumbersome in large-scale topologies, we further propose a L-shaped decomposition algorithm (an exact method) and a greedy heuristic. Key findings demonstrate that for a large range of pricing options and traffic profiles, NFV can significantly save network costs spent by the operator to provide the content distribution service.

Mots clés : Stochastic Network Planning, Content Distribution, Network Function Virtualization