Multilayer optical networking is an enabling technology to support the exponential growth of traffic and its dynamicity, with sustainable costs. However, automation and collaboration between IP and optical layers are still on an early stage. One of the reasons is the absence of pure multilayer planning and management solutions considering the network as a whole entity, where layers cooperate with each other, instead of the sum of individual layers providing isolated services. Consequently, operators are typically structured into two different departments to manage IP and optical infrastructures. Moreover, to minimize the interaction between these departments, IP/MPLS networks are often over-provisioned and based on static configurations. In this chapter, we will provide readers a reference framework and methodologies to explore real-world multilayer optical networking techniques in order to analyze their networks, perform "what if??" simulations, and so on.
The core of the chapter is divided into three main parts. First, the reader will be introduced into the world of multilayer elastic optical networks. On the one hand, a general model for multilayer elastic optical networks will be presented, starting from a generic technology-agnostic. On the other hand, a methodology for network analysis will be discussed, including aspects such as offline vs online scenarios, ILP models vs (meta-)heuristics, and so on. Second, several variants of the multilayer problem will be introduced (regenerator placement, contention-awareness, adaptive modulation, IP routing protocols, survivability, energy-efficiency and so on), giving some tips about modeling of each specific problem, including some pseudo-code for clarification. Finally, some exercises, followed by their solutions, will be proposed in order to validate the knowledge acquired.
To conclude, the reader will be provided with a corpus of theoretical and practical tools and tips to model and evaluate almost any kind of variant of (single-layer or multilayer) network scenarios, driven through several examples and practical exercises. All software will be released as open-source in sites like GitHub, as an accompanying resource to the chapter. Therefore, practitioners will be able to use this software as a baseline framework to develop their own solution. In fact, one of the key points of the chapter is that, for the first time ever, authors present a framework to model and develop multilayer network scenarios rather than presenting a specific solution for a specific problem, as usual in scientific publications