Artificial intelligence (AI) methods in optical networks: A comprehensive survey

Producción CientíficaArtificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.Ministerio de Economía, Industria y Competitividad (Project EC2014-53071-C3-2-P, TEC2015-71932-REDT

Towards a Virtualized Next Generation Internet

A promising solution to overcome the Internet ossification is network virtualization in which Internet Service Providers (ISPs) are decoupled into two tiers: service providers (SPs), and infrastructure providers (InPs). The former maintain and customize virtual network(s) to meet the service requirement of end-users, which is mapped to the physical network infrastructure that is managed and deployed by the latter via the Virtual Network Embedding (VNE) process. VNE consists of two major components: node assignment, and link mapping, which can be shown to be NP-Complete. In the first part of the dissertation, we present a path-based ILP model for the VNE problem. Our solution employs a branch-and-bound framework to resolve the integrity constraints, while embedding the column generation process to effectively obtain the lower bound for branch pruning. Different from existing approaches, the proposed solution can either obtain an optimal solution or a near-optimal solution with guarantee on the solution quality. A common strategy in VNE algorithm design is to decompose the problem into two sequential sub-problems: node assignment (NA) and link mapping (LM). With this approach, it is inexorable to sacrifice the solution quality since the NA is not holistic and not-reversible. In the second part, we are motivated to answer the question: Is it possible to maintain the simplicity of the Divide-and-Conquer strategy while still achieving optimality? Our answer is based on a decomposition framework supported by the Primal-Dual analysis of the path-based ILP model. This dissertation also attempts to address issues in two frontiers of network virtualization: survivability, and integration of optical substrate. In the third part, we address the survivable network embedding (SNE) problem from a network flow perspective, considering both splittable and non-splittable flows. In addition, the explosive growth of the Internet traffic calls for the support of a bandwidth abundant optical substrate, despite the extra dimensions of complexity caused by the heterogeneities of optical resources, and the physical feature of optical transmission. In this fourth part, we present a holistic view of motivation, architecture, and challenges on the way towards a virtualized optical substrate that supports network virtualization

Multicast Aware Virtual Network Embedding in Software Defined Networks

The Software Defined Networking (SDN) provides not only a higher level abstraction of lower level functionalities, but also flexibility to create new multicast framework. SDN decouples the low level network elements (forwarding/data plane) from the control/management layer (control plane), where a centralized controller can access and modify the configuration of each distributed network element. The centralized framework allows to develop more network functionalities that can not be easily achieved in the traditional network architecture. Similarly, Network Function Virtualization (NFV) enables the decoupling of network services from the underlying hardware infrastructure to allow the same Substrate (Physical) Network (SN) shared by multiple Virtual Network (VN) requests. With the network virtualization, the process of mapping virtual nodes and links onto a shared SN while satisfying the computing and bandwidth constraints is referred to as Virtual Network Embedding (VNE), an NP-Hard problem. The VNE problem has drawn a lot of attention from the research community. In this dissertation, we motivate the importance of characterizing the mode of communication in VN requests, and we focus our attention on the problem of embedding VNs with one-to-many (multicast) communication mode. Throughout the dissertation, we highlight the unique properties of multicast VNs and explore how to efficiently map a given Virtual Multicast Tree/Network (VMT) request onto a substrate IP Network or Elastic Optical Networks (EONs). The major objective of this dissertation is to study how to efficiently embed (i) a given virtual request in IP or optical networks in the form of a multicast tree while minimizing the resource usage and avoiding the redundant multicast tranmission, (ii) a given virtual request in optical networks while minimizing the resource usage and satisfying the fanout limitation on the multicast transmission. Another important contribution of this dissertation is how to efficiently map Service Function Chain (SFC) based virtual multicast request without prior constructed SFC while minimizing the resource usage and satisfying the SFC on the multicast transmission

Routing, Modulation and Spectrum Assignment Algorithm Using Multi-Path Routing and Best-Fit

Producción CientíficaElastic Optical Networks (EONs) are a promising optical technology to deal with the ever-increasing traffic and the vast number of connected devices of the next generation of the Internet, associated to paradigms like the Internet of Things (IoT), the Tactile Internet or the Industry 4.0, to name just a few. In this kind of optical network, each optical circuit or lightpath is provisioned by means of superchannels of variable bandwidth. In this manner, only the necessary bandwidth to accommodate the demand is allocated, improving the spectrum usage. When establishing a connection, the EON control layer determines the modulation format to be used and allocates a portion of the spectrum in a sequence of fibers from the source to the destination node providing the user-demanded bandwidth. This is known as the routing, modulation level and spectrum assignment (RMSA) problem. In this work, we firstly review the most important contributions in that area, and then, we propose a novel RMSA algorithm, multi-path best-fit (MP-BF), which uses a split spectrum multi-path strategy together with a spectrum assignment technique (best-fit), and which jointly exploit the flexibility of EONs. A simulation study has been conducted comparing the performance of EONs when using MP-BF with other proposals from the literature. The results of this study show that, by using MP-BF, the network can increase its performance in terms of lightpath request blocking ratio and supported traffic load, without affecting the energy per bit or the computation time required to find a solution

A RMSA algorithm resilient to multiple node failures on elastic optical networks

An Elastic Optical Network (EON) provides a lot of flexibility on the way an optical network supports the demands of multiple services. This flexibility is given by the Routing, Modulation and Spectrum Assignment (RMSA) algorithm whose primary goal is to use the spectrum resources of the network in an efficient way. Recently, large-scale failures are becoming a concern and one source of such failures is malicious human activities. In terrorist attacks, although node shutdowns are harder to realize than link cuts, they are the most rewarding in the attackers’ perspective since the shutdown of one node also shuts down all its connected links. In order to obtain a RMSA algorithm resilient to multiple node failures, we propose the use of a path disaster availability metric which measures the probability of each path not being affected by a multiple node failure. We present computational results considering a mix of unicast and anycast services in 3 well-known topologies. We assess the trade-off between spectrum usage efficiency and resilience to multiple node failures of our proposal against other previous known algorithms. The results show that the RMSA decision is always better when the disaster path availability metric is used. Moreover, the best way to use the path disaster availability metric in the RMSA decision depends on the traffic load of the EON.publishe

A metaheuristic and simheuristic approach for the p-Hub median problem from a telecommunication perspective

Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2018.Avanços recentes no setor das telecomunicações oferecem grandes oportunidades para cidadãos e organizações em um mundo globalmente conectado, ao mesmo tempo em que surge um vasto número de desafios complexos que os engenheiros devem enfrentar. Alguns desses desafios podem ser modelados como problemas de otimização. Alguns exemplos incluem o problema de alocação de recursos em redes de comunicações, desenho de topologias de rede que satisfaça determinadas propriedades associadas a requisitos de qualidade de serviço, sobreposição de redes multicast e outros recursos importantes para comunicação de origem a destino. O primeiro objetivo desta tese é fornecer uma revisão sobre como as metaheurísticas têm sido usadas até agora para lidar com os problemas de otimização associados aos sistemas de telecomunicações, detectando as principais tendências e desafios. Particularmente, a análise enfoca os problemas de desenho, roteamento e alocação de recursos. Além disso, devido á natureza desses desafios, o presente trabalho discute como a hibridização de metaheurísticas com metodologias como simulação pode ser empregada para ampliar as capacidades das metaheurísticas na resolução de problemas de otimização estocásticos na indústria de telecomunicações. Logo, é analisado um problema de otimização com aplicações práticas para redes de telecomunica ções: o problema das p medianas não capacitado em que um número fixo de hubs tem capacidade ilimitada, cada nó não-hub é alocado para um único hub e o número de hubs é conhecido de antemão, sendo analisado em cenários determinísticos e estocásticos. Dada a sua variedade e importância prática, o problema das p medianas vem sendo aplicado e estudado em vários contextos. Seguidamente, propõem-se dois algoritmos imune-inspirados e uma metaheurística de dois estágios, que se baseia na combinação de técnicas tendenciosas e aleatórias com uma estrutura de busca local iterada, além de sua integração com a técnica de simulação de Monte Carlo para resolver o problema das p medianas. Para demonstrar a eficiência dos algoritmos, uma série de testes computacionais é realizada, utilizando instâncias de grande porte da literatura. Estes resultados contribuem para uma compreensão mais profunda da eficácia das metaheurísticas empregadas para resolver o problema das p medianas em redes pequenas e grandes. Por último, uma aplicaçã o ilustrativa do problema das p medianas é apresentada, bem como alguns insights sobre novas possibilidades para ele, estendendo a metodologia proposta para ambientes da vida real.Recent advances in the telecommunication industry o er great opportunities to citizens and organizations in a globally-connected world, but they also arise a vast number of complex challenges that decision makers must face. Some of these challenges can be modeled as optimization problems. Examples include the framework of network utility maximization for resource allocation in communication networks, nding a network topology that satis es certain properties associated with quality of service requirements, overlay multicast networks, and other important features for source to destination communication. First, this thesis provides a review on how metaheuristics have been used so far to deal with optimization problems associated with telecommunication systems, detecting the main trends and challenges. Particularly the analysis focuses on the network design, routing, and allocation problems. In addition, due to the nature of these challenges, this work discusses how the hybridization of metaheuristics with methodologies such as simulation can be employed to extend the capabilities of metaheuristics when solving stochastic optimization problems. Then, a popular optimization problem with practical applications to the design of telecommunication networks: the Uncapacitated Single Allocation p-Hub Median Problem (USApHMP) where a xed number of hubs have unlimited capacity, each non-hub node is allocated to a single hub and the number of hubs is known in advance is analyzed in deterministic and stochastic scenarios. p-hub median problems are concerned with optimality of telecommunication and transshipment networks, and seek to minimize the cost of transportation or establishing. Next, two immune inspired metaheuristics are proposed to solve the USApHMP, besides that, a two-stage metaheuristic which relies on the combination of biased-randomized techniques with an iterated local search framework and its integration with simulation Monte Carlo technique for solving the same problem is proposed. In order to show their e ciency, a series of computational tests are carried out using small and large size instances from the literature. These results contribute to a deeper understanding of the e ectiveness of the employed metaheuristics for solving the USApHMP in small and large networks. Finally, an illustrative application of the USApHMP is presented as well as some insights about some new possibilities for it, extending the proposed methodology to real-life environments.Els últims avenços en la industria de les telecomunicacions ofereixen grans oportunitats per ciutadans i organitzacions en un món globalment connectat, però a la vegada, presenten reptes als que s'enfronten tècnics i enginyers que prenen decisions. Alguns d'aquests reptes es poden modelitzar com problemes d'optimització. Exemples inclouen l'assignació de recursos a les xarxes de comunicació, trobant una topologia de xarxa que satisfà certes propietats associades a requisits de qualitat de servei, xarxes multicast superposades i altres funcions importants per a la comunicació origen a destinació. El primer objectiu d'aquest treball és proporcionar un revisió de la literatura sobre com s'han utilitzat aquestes tècniques, tradicionalment, per tractar els problemes d'optimització associats a sistemes de telecomunicació, detectant les principals tendències i desa aments. Particularment, l'estudi es centra en els problemes de disseny de xarxes, enrutament i problemes d'assignació de recursos. Degut a la naturalesa d'aquests problemes, aquest treball també analitza com es poden combinar les tècniques metaheurístiques amb metodologies de simulació per ampliar les capacitats de resoldre problemes d'optimització estocàstics. A més, es tracta un popular problema d'optimització amb aplicacions pràctiques per xarxes de telecomunicació, el problema de la p mediana no capacitat, analitzant-lo des d'escenaris deterministes i estocàstics. Aquest problema consisteix en determinar el nombre d'instal lacions (medianes) en una xarxa, minimitzant la suma de tots els costs o distàncies des d'un punt de demanda a la instal lació més propera. En general, el problema de la p mediana està lligat amb l'optimització de xarxes de telecomunicacions i de transport, i busquen minimitzar el cost de transport o establiment de la xarxa. Es proposa dos algoritmes immunològics i un algoritme metaheurístic de dues etapes basat en la combinació de tècniques aleatòries amb simulacions Monte Carlo. L'e ciència de les algoritmes es posa a prova mitjançant alguns dels test computacionals més utilitzats a la literatura, obtenint uns resultats molt satisfactoris, ja que es capaç de resoldre casos petits i grans en qüestió de segons i amb un baix cost computacional. Finalment, es presenta una aplicació il lustrativa del problema de la p mediana, així com algunes noves idees sobre aquest, que estenen la metodologia proposta a problemes de la vida real

RMSA algorithms resilient to multiple node failures in dynamic EONs

In Elastic Optical Networks (EONs), the way different service demands are supported in the network is ruled by the Routing, Modulation and Spectrum Assignment (RMSA) algorithm, which decides how the spectrum resources of the optical network are assigned to each service demand. In a dynamic EON, demand requests arrive randomly one at a time and the accepted demands last in the network for a random time duration. So, one important goal of the RMSA algorithm is the efficient use of the spectrum resources to maximize the acceptance probability of future demand requests. On the other hand, multiple failure events are becoming a concern to network operators as such events are becoming more frequent in time. In this work, we consider the case of multiple node failure events caused by malicious attacks against network nodes. In order to obtain RMSA algorithms resilient to such events, a path disaster availability metric was recently proposed which takes into account the probability of each path not being disrupted by an attack. This metric was proposed in the offline variant of the RMSA problem where all demands are assumed to be known at the beginning. Here, we exploit the use of the path disaster availability metric in the RMSA of dynamic EONs. In particular, we propose RMSA algorithms combining the path disaster availability metric with spectrum usage metrics in a dynamic way based on the network load level. The aim is that the efficient use of the resources is relaxed for improved resilience to multiple node failures when the EON is lightly loaded, while it becomes the most important goal when the EON becomes heavily loaded. We present simulation results considering a mix of unicast and anycast services in 3 well-known topologies. The results show that the RMSA algorithms combining the path disaster availability metric with spectrum usage metrics are the best trade-off between spectrum usage efficiency and resilience to multiple node failures.publishe

Modulation-Adaptive Link-Disjoint Path Selection Model for 1 + 1 Protected Elastic Optical Networks

In elastic optical networks (EONs), an appropriate modulation technique is adapted according to the distance of an optical path. A robust modulation technique with a large number of spectrum slots is considered for longer distance optical paths, and a less robust modulation technique with a small number of spectrum slots is used for shorter distance optical paths. When an optical path is configured, the number of required spectrum slots is determined based on the nonlinear relationship between the optical path length and the number of utilized spectrum slots. Minimizing the total path lengths does not always minimize the total number of required spectrum slots for configuring an optical path, which decreases the spectrum utilization. This paper introduces a modulation-adaptive link-disjoint path selection model by considering a step function based on realistic modulation formats in order to minimize the total number of utilized spectrum slots in 1 + 1 protected EONs. We formulate the modulation-adaptive link-disjoint path selection problem as an integer linear programming (ILP). We prove that the modulation-adaptive link-disjoint path selection problem is NP-complete. By using an optimization solver, we solve the ILP problem for different backbone networks, namely, Japan Photonic Network (JPN48), German 17 Network, and COST 239 Network, within a practical time. Numerical results obtained from performance evaluation indicate that the introduced model reduces the number of utilized spectrum slots compared to the conventional schemes

Resilient Resource Allocation Schemes in Optical Networks

Recent studies show that deliberate malicious attacks performed by high-power sig- nals can put large amount of data under risk. We investigate the problem of sur- vivable optical networks resource provisioning scheme against malicious attacks, more specically crosstalk jamming attacks. These types of attacks may cause ser- vice disruption (or possibly service denial). We consider optical networks based on wavelength-division multiplexing (WDM) technology and two types of jamming at- tacks: in-band and out-of-band attacks. We propose an attack-aware routing and wavelength assignments (RWA) scheme to avoid or reduce the damaging effects of potential attacking signals on individual or multiple legitimate lightpaths travers- ing the same optical switches and links. An integer linear programs (ILPs) as well as heuristic approaches were proposed to solve the problem. We consider dynamic traffic where each demand is dened by its start time and a duration. Our results show that the proposed approaches were able to limit the vulnerability of lightpaths to jamming attacks. Recently, large-scale failures caused by natural disasters and/or deliberate at- tacks have left major parts of the networks damaged or disconnected. We also investigate the problem of disaster-aware WDM network resource provisioning in case of disasters. We propose an ILP and efficient heuristic to route the lightpaths in such a way that provides protection against disasters and minimize the network vi resources such as the number of wavelength links used in the network. Our models show that signicant resource savings can be achieved while accommodating users demands. In the last few years, optical networks using Space Division Multiplexing (SDM) has been proposed as a solution to the speed bottleneck anticipated in data center (DC) networks. To our knowledge the new challenges of designing such communica- tion systems have not been addressed yet. We propose an optimal approach to the problem of developing a path-protection scheme to handle communication requests in DC networks using elastic optical networking and space division multiplexing. We have formulated our problem as an ILP. We have also proposed a heuristic that can handle problems of practical size. Our simulations explore important features of our approach