Characterization, design and re-optimization on multi-layer optical networks

L'augment de volum de tràfic IP provocat per l'increment de serveis multimèdia com HDTV o vídeo conferència planteja nous reptes als operadors de xarxa per tal de proveir transmissió de dades eficient. Tot i que les xarxes mallades amb multiplexació per divisió de longitud d'ona (DWDM) suporten connexions òptiques de gran velocitat, aquestes xarxes manquen de flexibilitat per suportar tràfic d’inferior granularitat, fet que provoca un pobre ús d'ample de banda. Per fer front al transport d'aquest tràfic heterogeni, les xarxes multicapa representen la millor solució. Les xarxes òptiques multicapa permeten optimitzar la capacitat mitjançant l'empaquetament de connexions de baixa velocitat dins de connexions òptiques de gran velocitat. Durant aquesta operació, es crea i modifica constantment una topologia virtual dinàmica gràcies al pla de control responsable d’aquestes operacions. Donada aquesta dinamicitat, un ús sub-òptim de recursos pot existir a la xarxa en un moment donat. En aquest context, una re-optimizació periòdica dels recursos utilitzats pot ser aplicada, millorant així l'ús de recursos. Aquesta tesi està dedicada a la caracterització, planificació, i re-optimització de xarxes òptiques multicapa de nova generació des d’un punt de vista unificat incloent optimització als nivells de capa física, capa òptica, capa virtual i pla de control. Concretament s'han desenvolupat models estadístics i de programació matemàtica i meta-heurístiques. Aquest objectiu principal s'ha assolit mitjançant cinc objectius concrets cobrint diversos temes oberts de recerca. En primer lloc, proposem una metodologia estadística per millorar el càlcul del factor Q en problemes d'assignació de ruta i longitud d'ona considerant interaccions físiques (IA-RWA). Amb aquest objectiu, proposem dos models estadístics per computar l'efecte XPM (el coll d'ampolla en termes de computació i complexitat) per problemes IA-RWA, demostrant la precisió d’ambdós models en el càlcul del factor Q en escenaris reals de tràfic. En segon lloc i fixant-nos a la capa òptica, presentem un nou particionament del conjunt de longituds d'ona que permet maximitzar, respecte el cas habitual, la quantitat de tràfic extra proveït en entorns de protecció compartida. Concretament, definim diversos models estadístics per estimar la quantitat de tràfic donat un grau de servei objectiu, i diferents models de planificació de xarxa amb l'objectiu de maximitzar els ingressos previstos i el valor actual net de la xarxa. Després de resoldre aquests problemes per xarxes reals, concloem que la nostra proposta maximitza ambdós objectius. En tercer lloc, afrontem el disseny de xarxes multicapa robustes davant de fallida simple a la capa IP/MPLS i als enllaços de fibra. Per resoldre aquest problema eficientment, proposem un enfocament basat en sobre-dimensionar l'equipament de la capa IP/MPLS i recuperar la connectivitat i el comparem amb la solució convencional basada en duplicar la capa IP/MPLS. Després de comparar solucions mitjançant models ILP i heurístiques, concloem que la nostra solució permet obtenir un estalvi significatiu en termes de costos de desplegament. Com a quart objectiu, introduïm un mecanisme adaptatiu per reduir l'ús de ports opto-electrònics (O/E) en xarxes multicapa sota escenaris de tràfic dinàmic. Una formulació ILP i diverses heurístiques són desenvolupades per resoldre aquest problema, que permet reduir significativament l’ús de ports O/E en temps molt curts. Finalment, adrecem el problema de disseny resilient del pla de control GMPLS. Després de proposar un nou model analític per quantificar la resiliència en topologies mallades de pla de control, usem aquest model per proposar un problema de disseny de pla de control. Proposem un procediment iteratiu lineal i una heurística i els usem per resoldre instàncies reals, arribant a la conclusió que es pot reduir significativament la quantitat d'enllaços del pla de control sense afectar la qualitat de servei a la xarxa.The explosion of IP traffic due to the increase of IP-based multimedia services such as HDTV or video conferencing poses new challenges to network operators to provide a cost-effective data transmission. Although Dense Wavelength Division Multiplexing (DWDM) meshed transport networks support high-speed optical connections, these networks lack the flexibility to support sub-wavelength traffic leading to poor bandwidth usage. To cope with the transport of that huge and heterogeneous amount of traffic, multilayer networks represent the most accepted architectural solution. Multilayer optical networks allow optimizing network capacity by means of packing several low-speed traffic streams into higher-speed optical connections (lightpaths). During this operation, a dynamic virtual topology is created and modified the whole time thanks to a control plane responsible for the establishment, maintenance, and release of connections. Because of this dynamicity, a suboptimal allocation of resources may exist at any time. In this context, a periodically resource reallocation could be deployed in the network, thus improving network resource utilization. This thesis is devoted to the characterization, planning, and re-optimization of next-generation multilayer networks from an integral perspective including physical layer, optical layer, virtual layer, and control plane optimization. To this aim, statistical models, mathematical programming models and meta-heuristics are developed. More specifically, this main objective has been attained by developing five goals covering different open issues. First, we provide a statistical methodology to improve the computation of the Q-factor for impairment-aware routing and wavelength assignment problems (IA-RWA). To this aim we propose two statistical models to compute the Cross-Phase Modulation variance (which represents the bottleneck in terms of computation time and complexity) in off-line and on-line IA-RWA problems, proving the accuracy of both models when computing Q-factor values in real traffic scenarios. Second and moving to the optical layer, we present a new wavelength partitioning scheme that allows maximizing the amount of extra traffic provided in shared path protected environments compared with current solutions. Specifically, we define several statistical models to estimate the traffic intensity given a target grade of service, and different network planning problems for maximizing the expected revenues and net present value. After solving these problems for real networks, we conclude that our proposed scheme maximizes both revenues and NPV. Third, we tackle the design of survivable multilayer networks against single failures at the IP/MPLS layer and WSON links. To efficiently solve this problem, we propose a new approach based on over-dimensioning IP/MPLS devices and lightpath connectivity and recovery and we compare it against the conventional solution based on duplicating backbone IP/MPLS nodes. After evaluating both approaches by means of ILP models and heuristic algorithms, we conclude that our proposed approach leads to significant CAPEX savings. Fourth, we introduce an adaptive mechanism to reduce the usage of opto-electronic (O/E) ports of IP/MPLS-over-WSON multilayer networks in dynamic scenarios. A ILP formulation and several heuristics are developed to solve this problem, which allows significantly reducing the usage of O/E ports in very short running times. Finally, we address the design of resilient control plane topologies in GMPLS-enabled transport networks. After proposing a novel analytical model to quantify the resilience in mesh control plane topologies, we use this model to propose a problem to design the control plane topology. An iterative model and a heuristic are proposed and used to solve real instances, concluding that a significant reduction in the number of control plane links can be performed without affecting the quality of service of the network

Routage résilient dans les réseaux SDN

International audienceLes réseaux SDN (software-defined networking) permettentàpermettent`permettentà un contrôleur centralisé de décider du routage. Afin d'´ etablir des routes fiables, il est souvent nécessaire de trouver plusieurs chemins dans le réseau ne partageant pas les mêmes ressouresàressoures`ressouresà risque, communément appelé SRLG pour Shared Risk Link Group. Tout en assurant cette fiabilité, l'objectif est aussi de minimiser un coût, qui intègre des indicateurs de congestion ou de latence. Ceprobì eme peutêtrepeutˆpeutêtre modélisé par un programme linéaire en nombres entiers (ILP). Nous proposons ici une méthode efficace pour sa résolution qui utilise une relaxation fractionnaire bien choisie, dont nous montrerons qu'elle m` ene en fait la plupart du tempsàtemps`tempsà une solutionentì ere. La résolution de ceprobì eme relaxé utilise une méthode de génération de colonnes (CG), o` u chaque colonne représente un chemin dans le réseau avec une notion de coût modifié prenant en compte les SRLGs ; les nouvelles colonnes peuventêtrepeuventˆpeuventêtre obtenues par un algorithme efficace de programmation dynamique quí etend les algorithmes classiques de calcul de plus court chemin. Afin de limiter l'explosion combinatoire potentielle, nous présentonsprésentons´présentonségalement une heuristique qui accélére le calcul d'une solution résiliente tout en préservant de très bonnes performances. Les résultats numériques montrent que notre approche donne une solution de très bonne qualité dans un temps de calcul raisonnable sur des instances de réseau réalistes

Towards cognitive in-operation network planning

Next-generation internet services such as live TV and video on demand require high bandwidth and ultra-low latency. The ever-increasing volume, dynamicity and stringent requirements of these services’ demands are generating new challenges to nowadays telecom networks. To decrease expenses, service-layer content providers are delivering their content near the end users, thus allowing a low latency and tailored content delivery. As a consequence of this, unseen metro and even core traffic dynamicity is arising with changes in the volume and direction of the traffic along the day. A tremendous effort to efficiently manage networks is currently ongoing towards the realisation of 5G networks. This translates in looking for network architectures supporting dynamic resource allocation, fulfilling strict service requirements and minimising the total cost of ownership (TCO). In this regard, in-operation network planning was recently proven to successfully support various network reconfiguration use cases in prospective scenarios. Nevertheless, additional research to extend in-operation planning capabilities from typical reactive optimization schemes to proactive and predictive schemes based on the analysis of network monitoring data is required. A hot topic raising increasing attention is cognitive networking, where an elevated knowledge about the network could be obtained as a result of introducing data analytics in the telecom operator’s infrastructure. By using predictive knowledge about the network traffic, in-operation network planning mechanisms could be enhanced to efficiently adapt the network by means of future traffic prediction, thus achieving cognitive in-operation network planning. In this thesis, we focus on studying mechanisms to enable cognitive in-operation network planning in core networks. In particular, we focus on dynamically reconfiguring virtual network topologies (VNT) at the MPLS layer, covering a number of detailed objectives. First, we start studying mechanisms to allow network traffic flow modelling, from monitoring and data transformation to the estimation of predictive traffic model based on this data. By means of these traffic models, then we tackle a cognitive approach to periodically adapt the core VNT to current and future traffic, using predicted traffic matrices based on origin-destination (OD) predictive models. This optimization approach, named VENTURE, is efficiently solved using dedicated heuristic algorithms and its feasibility is demonstrated in an experimental in-operation network planning environment. Finally, we extend VENTURE to consider core flows dynamicity as a result of metro flows re-routing, which represents a meaningful dynamic traffic scenario. This extension, which entails enhancements to coordinate metro and core network controllers with the aim of allowing fast adaption of core OD traffic models, is evaluated and validated in terms of traffic models accuracy and experimental feasibility.Els serveis d’internet de nova generació tals com la televisió en viu o el vídeo sota demanda requereixen d’un gran ample de banda i d’ultra-baixa latència. L’increment continu del volum, dinamicitat i requeriments d’aquests serveis està generant nous reptes pels teleoperadors de xarxa. Per reduir costs, els proveïdors de contingut estan disposant aquests més a prop dels usuaris finals, aconseguint així una entrega de contingut feta a mida. Conseqüentment, estem presenciant una dinamicitat mai vista en el tràfic de xarxes de metro amb canvis en la direcció i el volum del tràfic al llarg del dia. Actualment, s’està duent a terme un gran esforç cap a la realització de xarxes 5G. Aquest esforç es tradueix en cercar noves arquitectures de xarxa que suportin l’assignació dinàmica de recursos, complint requeriments de servei estrictes i minimitzant el cost total de la propietat. En aquest sentit, recentment s’ha demostrat com l’aplicació de “in-operation network planning” permet exitosament suportar diversos casos d’ús de reconfiguració de xarxa en escenaris prospectius. No obstant, és necessari dur a terme més recerca per tal d’estendre “in-operation network planning” des d’un esquema reactiu d’optimització cap a un nou esquema proactiu basat en l’analítica de dades provinents del monitoritzat de la xarxa. El concepte de xarxes cognitives es també troba al centre d’atenció, on un elevat coneixement de la xarxa s’obtindria com a resultat d’introduir analítica de dades en la infraestructura del teleoperador. Mitjançant un coneixement predictiu sobre el tràfic de xarxa, els mecanismes de in-operation network planning es podrien millorar per adaptar la xarxa eficientment basant-se en predicció de tràfic, assolint així el que anomenem com a “cognitive in-operation network Planning”. En aquesta tesi ens centrem en l’estudi de mecanismes que permetin establir “el cognitive in-operation network Planning” en xarxes de core. En particular, ens centrem en reconfigurar dinàmicament topologies de xarxa virtual (VNT) a la capa MPLS, cobrint una sèrie d’objectius detallats. Primer comencem estudiant mecanismes pel modelat de fluxos de tràfic de xarxa, des del seu monitoritzat i transformació fins a l’estimació de models predictius de tràfic. Posteriorment, i mitjançant aquests models predictius, tractem un esquema cognitiu per adaptar periòdicament la VNT utilitzant matrius de tràfic basades en predicció de parells origen-destí (OD). Aquesta optimització, anomenada VENTURE, és resolta eficientment fent servir heurístiques dedicades i és posteriorment avaluada sota escenaris de tràfic de xarxa dinàmics. A continuació, estenem VENTURE considerant la dinamicitat dels fluxos de tràfic de xarxes de metro, el qual representa un escenari rellevant de dinamicitat de tràfic. Aquesta extensió involucra millores per coordinar els operadors de metro i core amb l’objectiu d’aconseguir una ràpida adaptació de models de tràfic OD. Finalment, proposem dues arquitectures de xarxa necessàries per aplicar els mecanismes anteriors en entorns experimentals, emprant protocols estat-de-l’art com són OpenFlow i IPFIX. La metodologia emprada per avaluar el treball anterior consisteix en una primera avaluació numèrica fent servir un simulador de xarxes íntegrament dissenyat i desenvolupat per a aquesta tesi. Després d’aquesta validació basada en simulació, la factibilitat experimental de les arquitectures de xarxa proposades és avaluada en un entorn de proves distribuït.Postprint (published version

Towards cognitive in-operation network planning

Next-generation internet services such as live TV and video on demand require high bandwidth and ultra-low latency. The ever-increasing volume, dynamicity and stringent requirements of these services’ demands are generating new challenges to nowadays telecom networks. To decrease expenses, service-layer content providers are delivering their content near the end users, thus allowing a low latency and tailored content delivery. As a consequence of this, unseen metro and even core traffic dynamicity is arising with changes in the volume and direction of the traffic along the day. A tremendous effort to efficiently manage networks is currently ongoing towards the realisation of 5G networks. This translates in looking for network architectures supporting dynamic resource allocation, fulfilling strict service requirements and minimising the total cost of ownership (TCO). In this regard, in-operation network planning was recently proven to successfully support various network reconfiguration use cases in prospective scenarios. Nevertheless, additional research to extend in-operation planning capabilities from typical reactive optimization schemes to proactive and predictive schemes based on the analysis of network monitoring data is required. A hot topic raising increasing attention is cognitive networking, where an elevated knowledge about the network could be obtained as a result of introducing data analytics in the telecom operator’s infrastructure. By using predictive knowledge about the network traffic, in-operation network planning mechanisms could be enhanced to efficiently adapt the network by means of future traffic prediction, thus achieving cognitive in-operation network planning. In this thesis, we focus on studying mechanisms to enable cognitive in-operation network planning in core networks. In particular, we focus on dynamically reconfiguring virtual network topologies (VNT) at the MPLS layer, covering a number of detailed objectives. First, we start studying mechanisms to allow network traffic flow modelling, from monitoring and data transformation to the estimation of predictive traffic model based on this data. By means of these traffic models, then we tackle a cognitive approach to periodically adapt the core VNT to current and future traffic, using predicted traffic matrices based on origin-destination (OD) predictive models. This optimization approach, named VENTURE, is efficiently solved using dedicated heuristic algorithms and its feasibility is demonstrated in an experimental in-operation network planning environment. Finally, we extend VENTURE to consider core flows dynamicity as a result of metro flows re-routing, which represents a meaningful dynamic traffic scenario. This extension, which entails enhancements to coordinate metro and core network controllers with the aim of allowing fast adaption of core OD traffic models, is evaluated and validated in terms of traffic models accuracy and experimental feasibility.Els serveis d’internet de nova generació tals com la televisió en viu o el vídeo sota demanda requereixen d’un gran ample de banda i d’ultra-baixa latència. L’increment continu del volum, dinamicitat i requeriments d’aquests serveis està generant nous reptes pels teleoperadors de xarxa. Per reduir costs, els proveïdors de contingut estan disposant aquests més a prop dels usuaris finals, aconseguint així una entrega de contingut feta a mida. Conseqüentment, estem presenciant una dinamicitat mai vista en el tràfic de xarxes de metro amb canvis en la direcció i el volum del tràfic al llarg del dia. Actualment, s’està duent a terme un gran esforç cap a la realització de xarxes 5G. Aquest esforç es tradueix en cercar noves arquitectures de xarxa que suportin l’assignació dinàmica de recursos, complint requeriments de servei estrictes i minimitzant el cost total de la propietat. En aquest sentit, recentment s’ha demostrat com l’aplicació de “in-operation network planning” permet exitosament suportar diversos casos d’ús de reconfiguració de xarxa en escenaris prospectius. No obstant, és necessari dur a terme més recerca per tal d’estendre “in-operation network planning” des d’un esquema reactiu d’optimització cap a un nou esquema proactiu basat en l’analítica de dades provinents del monitoritzat de la xarxa. El concepte de xarxes cognitives es també troba al centre d’atenció, on un elevat coneixement de la xarxa s’obtindria com a resultat d’introduir analítica de dades en la infraestructura del teleoperador. Mitjançant un coneixement predictiu sobre el tràfic de xarxa, els mecanismes de in-operation network planning es podrien millorar per adaptar la xarxa eficientment basant-se en predicció de tràfic, assolint així el que anomenem com a “cognitive in-operation network Planning”. En aquesta tesi ens centrem en l’estudi de mecanismes que permetin establir “el cognitive in-operation network Planning” en xarxes de core. En particular, ens centrem en reconfigurar dinàmicament topologies de xarxa virtual (VNT) a la capa MPLS, cobrint una sèrie d’objectius detallats. Primer comencem estudiant mecanismes pel modelat de fluxos de tràfic de xarxa, des del seu monitoritzat i transformació fins a l’estimació de models predictius de tràfic. Posteriorment, i mitjançant aquests models predictius, tractem un esquema cognitiu per adaptar periòdicament la VNT utilitzant matrius de tràfic basades en predicció de parells origen-destí (OD). Aquesta optimització, anomenada VENTURE, és resolta eficientment fent servir heurístiques dedicades i és posteriorment avaluada sota escenaris de tràfic de xarxa dinàmics. A continuació, estenem VENTURE considerant la dinamicitat dels fluxos de tràfic de xarxes de metro, el qual representa un escenari rellevant de dinamicitat de tràfic. Aquesta extensió involucra millores per coordinar els operadors de metro i core amb l’objectiu d’aconseguir una ràpida adaptació de models de tràfic OD. Finalment, proposem dues arquitectures de xarxa necessàries per aplicar els mecanismes anteriors en entorns experimentals, emprant protocols estat-de-l’art com són OpenFlow i IPFIX. La metodologia emprada per avaluar el treball anterior consisteix en una primera avaluació numèrica fent servir un simulador de xarxes íntegrament dissenyat i desenvolupat per a aquesta tesi. Després d’aquesta validació basada en simulació, la factibilitat experimental de les arquitectures de xarxa proposades és avaluada en un entorn de proves distribuït

Topological Design of Multiple Virtual Private Networks UTILIZING SINK-TREE PATHS

With the deployment of MultiProtocol Label Switching (MPLS) over a core backbone networks, it is possible for a service provider to built Virtual Private Networks (VPNs) supporting various classes of services with QoS guarantees. Efficiently mapping the logical layout of multiple VPNs over a service provider network is a challenging traffic engineering problem. The use of sink-tree (multipoint-to-point) routing paths in a MPLS network makes the VPN design problem different from traditional design approaches where a full-mesh of point-to-point paths is often the choice. The clear benefits of using sink-tree paths are the reduction in the number of label switch paths and bandwidth savings due to larger granularities of bandwidth aggregation within the network. In this thesis, the design of multiple VPNs over a MPLS-like infrastructure network, using sink-tree routing, is formulated as a mixed integer programming problem to simultaneously find a set of VPN logical topologies and their dimensions to carry multi-service, multi-hour traffic from various customers. Such a problem formulation yields a NP-hard complexity. A heuristic path selection algorithm is proposed here to scale the VPN design problem by choosing a small-but-good candidate set of feasible sink-tree paths over which the optimal routes and capacity assignments are determined. The proposed heuristic has clearly shown to speed up the optimization process and the solution can be obtained within a reasonable time for a realistic-size network. Nevertheless, when a large number of VPNs are being layout simultaneously, a standard optimization approach has a limited scalability. Here, the heuristics termed the Minimum-Capacity Sink-Tree Assignment (MCSTA) algorithm proposed to approximate the optimal bandwidth and sink-tree route assignment for multiple VPNs within a polynomial computational time. Numerical results demonstrate the MCSTA algorithm yields a good solution within a small error and sometimes yields the exact solution. Lastly, the proposed VPN design models and solution algorithms are extended for multipoint traffic demand including multipoint-to-point and broadcasting connections

Survivable Cloud Network Mapping for Disaster Recovery Support

Network virtualization is a key provision for improving the scalability and reliability of cloud computing services. In recent years, various mapping schemes have been developed to reserve VN resources over substrate networks. However, many cloud providers are very concerned about improving service reliability under catastrophic disaster conditions yielding multiple system failures. To address this challenge, this work presents a novel failure region-disjoint VN mapping scheme to improve VN mapping survivability. The problem is first formulated as a mixed integer linear programming problem and then two heuristic solutions are proposed to compute a pair of failure region-disjoint VN mappings. The solution also takes into account mapping costs and load balancing concerns to help improve resource efficiencies. The schemes are then analyzed in detail for a variety of networks and their overall performances compared to some existing survivable VN mapping scheme

Regenerator Location Problem and survivable extensions: A hub covering location perspective

Cataloged from PDF version of article.In a telecommunications network the reach of an optical signal is the maximum distance it can traverse before its quality degrades. Regenerators are devices to extend the optical reach. The regenerator placement problem seeks to place the minimum number of regenerators in an optical network so as to facilitate the communication of a signal between any node pair. In this study, the Regenerator Location Problem is revisited from the hub location perspective directing our focus to applications arising in transportation settings. Two new dimensions involving the challenges of survivability are introduced to the problem. Under partial survivability, our designs hedge against failures in the regeneration equipment only, whereas under full survivability failures on any of the network nodes are accounted for by the utilization of extra regeneration equipment. All three variations of the problem are studied in a unifying framework involving the introduction of individual flow-based compact formulations as well as cut formulations and the implementation of branch and cut algorithms based on the cut formulations. Extensive computational experiments are conducted in order to evaluate the performance of the proposed solution methodologies and to gain insights from realistic instances. (C) 2014 Elsevier Ltd. All rights reserved

Optimised Design and Analysis of All-Optical Networks

This PhD thesis presents a suite of methods for optimising design and for analysing blocking probabilities of all-optical networks. It thus contributes methodical knowledge to the field of computer assisted planning of optical networks. A two-stage greenfield optical network design optimiser is developed, based on shortest-path algorithms and a comparatively new metaheuristic called simulated allocation. It is able to handle design of all-optical mesh networks with optical cross-connects, considers duct as well as fibre and node costs, and can also design protected networks. The method is assessed through various experiments and is shown to produce good results and to be able to scale up to networks of realistic sizes. A novel method, subpath wavelength grouping, for routing connections in a multigranular all-optical network where several wavelengths can be grouped and switched at band and fibre level is presented. The method uses an unorthodox routing strategy focusing on common subpaths rather than individual connections, and strives to minimise switch port count as well as fibre usage. It is shown to produce cheaper network designs than previous methods when fibre costs are comparatively high. A new optical network concept, the synchronous optical hierarchy, is proposed, in which wavelengths are subdivided into timeslots to match the traffic granularity. Various theoretical properties of this concept are investigated and compared in simulation studies. An integer linear programming model for optical ring network design is presented. Manually designed real world ring networks are studied and it is found that the model can lead to cheaper network design. Moreover, ring and mesh network architectures are compared using real world costs, and it is found that optical cros..

Cross-layer modeling and optimization of next-generation internet networks

Scaling traditional telecommunication networks so that they are able to cope with the volume of future traffic demands and the stringent European Commission (EC) regulations on emissions would entail unaffordable investments. For this very reason, the design of an innovative ultra-high bandwidth power-efficient network architecture is nowadays a bold topic within the research community. So far, the independent evolution of network layers has resulted in isolated, and hence, far-from-optimal contributions, which have eventually led to the issues today's networks are facing such as inefficient energy strategy, limited network scalability and flexibility, reduced network manageability and increased overall network and customer services costs. Consequently, there is currently large consensus among network operators and the research community that cross-layer interaction and coordination is fundamental for the proper architectural design of next-generation Internet networks. This thesis actively contributes to the this goal by addressing the modeling, optimization and performance analysis of a set of potential technologies to be deployed in future cross-layer network architectures. By applying a transversal design approach (i.e., joint consideration of several network layers), we aim for achieving the maximization of the integration of the different network layers involved in each specific problem. To this end, Part I provides a comprehensive evaluation of optical transport networks (OTNs) based on layer 2 (L2) sub-wavelength switching (SWS) technologies, also taking into consideration the impact of physical layer impairments (PLIs) (L0 phenomena). Indeed, the recent and relevant advances in optical technologies have dramatically increased the impact that PLIs have on the optical signal quality, particularly in the context of SWS networks. Then, in Part II of the thesis, we present a set of case studies where it is shown that the application of operations research (OR) methodologies in the desing/planning stage of future cross-layer Internet network architectures leads to the successful joint optimization of key network performance indicators (KPIs) such as cost (i.e., CAPEX/OPEX), resources usage and energy consumption. OR can definitely play an important role by allowing network designers/architects to obtain good near-optimal solutions to real-sized problems within practical running times