An Overview on Application of Machine Learning Techniques in Optical Networks

Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc. Advanced mathematical tools are required to extract meaningful information from these data and take decisions pertaining to the proper functioning of the networks from the network-generated data. Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration and fault management. The adoption of ML techniques in the field of optical communication networks is motivated by the unprecedented growth of network complexity faced by optical networks in the last few years. Such complexity increase is due to the introduction of a huge number of adjustable and interdependent system parameters (e.g., routing configurations, modulation format, symbol rate, coding schemes, etc.) that are enabled by the usage of coherent transmission/reception technologies, advanced digital signal processing and compensation of nonlinear effects in optical fiber propagation. In this paper we provide an overview of the application of ML to optical communications and networking. We classify and survey relevant literature dealing with the topic, and we also provide an introductory tutorial on ML for researchers and practitioners interested in this field. Although a good number of research papers have recently appeared, the application of ML to optical networks is still in its infancy: to stimulate further work in this area, we conclude the paper proposing new possible research directions

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

Traffic engineering in dynamic optical networks

Traffic Engineering (TE) refers to all the techniques a Service Provider employs to improve the efficiency and reliability of network operations. In IP over Optical (IPO) networks, traffic coming from upper layers is carried over the logical topology defined by the set of established lightpaths. Within this framework then, TE techniques allow to optimize the configuration of optical resources with respect to an highly dynamic traffic demand. TE can be performed with two main methods: if the demand is known only in terms of an aggregated traffic matrix, the problem of automatically updating the configuration of an optical network to accommodate traffic changes is called Virtual Topology Reconfiguration (VTR). If instead the traffic demand is known in terms of data-level connection requests with sub-wavelength granularity, arriving dynamically from some source node to any destination node, the problem is called Dynamic Traffic Grooming (DTG). In this dissertation new VTR algorithms for load balancing in optical networks based on Local Search (LS) techniques are presented. The main advantage of using LS is the minimization of network disruption, since the reconfiguration involves only a small part of the network. A comparison between the proposed schemes and the optimal solutions found via an ILP solver shows calculation time savings for comparable results of network congestion. A similar load balancing technique has been applied to alleviate congestion in an MPLS network, based on the efficient rerouting of Label-Switched Paths (LSP) from the most congested links to allow a better usage of network resources. Many algorithms have been developed to deal with DTG in IPO networks, where most of the attention is focused on optimizing the physical resources utilization by considering specific constraints on the optical node architecture, while very few attention has been put so far on the Quality of Service (QoS) guarantees for the carried traffic. In this thesis a novel Traffic Engineering scheme is proposed to guarantee QoS from both the viewpoint of service differentiation and transmission quality. Another contribution in this thesis is a formal framework for the definition of dynamic grooming policies in IPO networks. The framework is then specialized for an overlay architecture, where the control plane of the IP and optical level are separated, and no information is shared between the two. A family of grooming policies based on constraints on the number of hops and on the bandwidth sharing degree at the IP level is defined, and its performance analyzed in both regular and irregular topologies. While most of the literature on DTG problem implicitly considers the grooming of low-speed connections onto optical channels using a TDM approach, the proposed grooming policies are evaluated here by considering a realistic traffic model which consider a Dynamic Statistical Multiplexing (DSM) approach, i.e. a single wavelength channel is shared between multiple IP elastic traffic flows

Effect Of Reconfiguration On Ip Packet Traffic In Wdm Networks

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2007Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2007Günümüzde iletişim ağlarına erişen insan sayısı ve iletişim uygulamalarının ihtiyaç duyduğu band genişliği ihtiyacı hızla artmaya devam etmektedir. Artan trafik istekleri daha geniş band genişliği kullanımına olanak verebilen optik iletişim ağlarının tasarımını tetiklemektedir. Bir veya daha fazla sayıda optik fiberi kapsayabilen bir ışıkyolu alt katmanda yer alan optik altyapının üzerinde iletişim kanalları sağlamaktadır. Sanal topoloji tasarımı, verilen bir trafik matrisine göre bir grup ışık yolunun kurulması olarak tanımlanabilir. Trafikte meydana gelecek bir değişiklik yeniden konfigürasyon kararının alınmasına neden olabilir. Sanal topoloji yeniden konfigürasyonu, hem yeni sanal topolojinin belirlenmesini hem de bu yeni topolojiye geçişi içermektedir. Bu tez çalışmasında IP/WDM ağlarda sanal topoloji yeniden konfigürasyonunun IP paket trafiği üzerindeki etkileri incelenmiştir. Çalışma kapsamında, çeşitli yeniden kofigürasyon algoritmaları gerçeklenmiş ve Fishnet tabanlı bir IP simülatörü üzerinde test edilmiştir. Gerçeklenen sanal topoloji tasarım algoritmalarına ait paket gecikmeleri/kayıpları incelenmiş ve algoritmaların başarımları karşılaştırılmıştır.Today, both the amount of people accessing communication networks and new communication applications which require high data transfer rates are exponentially increasing. Growing traffic demands triggered the design of optical communication networks which will be able to provide larger bandwidth utilization. A lightpath, which can span multiple fiber links, provides communication channels over the underlying optical communication infrastructure. Virtual Topology Design (VTD) means establishment of a set of lightpaths under a given traffic pattern. A change in traffic pattern may trigger reconfiguration decision. Virtual Topology Reconfiguration (VTR) contains determination of a new virtual topology and migration between the old and new virtual topologies. In this thesis, the effects of virtual topology reconfiguration on Internet Protocol (IP) packet traffic on IP over WDM networks were studied. Various reconfiguration algorithms were implemented and tested on a Fishnet based IP simulator. Packet delays/losses are investigated during reconfiguration procedure for performance comparison of implemented reconfiguration algorithms.Yüksek LisansM.Sc

Multi-layer traffic engineering in optical networks under physical layer impairments

Ankara : The Department of Electrical and Electronics Engineering and the Institute of Engineering and Sciences of Bilkent University, 2010.Thesis (Ph. D.) -- Bilkent University, 2010.Includes bibliographical references leaves 153-165.We study Traffic Engineering (TE) in Multiprotocol Label Switching (MPLS)/Wavelength Division Multiplexing (WDM) networks and propose a multi-layer TE method. MPLS provides powerful TE features for IP networks and is widely deployed in backbone networks. WDM can increase the transmission capacity of optical fibers to tremendous amounts, therefore it has been the dominant multiplexing technology used in the optical layer. The proposed multi-layer TE solution facilitates efficient use of network resources where the TE mechanisms in the MPLS and WDM layers coordinate. We consider a static WDM layer and available traffic expectation information. The TE problem arising in the considered scenario is the Virtual Topology Design (VTD) problem, which involves the decision of WDM lightpaths to be established, calculation of MPLS Label Switched Paths (LSPs) on the resulting virtual topology, and calculation of the routes and wavelengths in the physical topology that correspond to the lightpaths in the virtual topology. We assume a daily traffic pattern changing with the time of day and aim to design a static virtual topology that satisfies as much of the offered traffic as possible, over the whole day. In our proposed solution, the multi-layer VTD problem is solved by decomposing it into two sub-problems, each involving in a single layer. The decomposition approach is used in the thesis due to the huge computational burden of the combined solution for real-life networks. The sub-problem in the MPLS layer is the design of the lightpath topology and calculation of the LSP routes on this virtual topology. This problem is known to be NP-complete and finding its optimum solution is possible only for small networks. We propose a Tabu Search based heuristic method to solve two versions of this problem, resource oriented and performance oriented. Integer Linear Programming (ILP) relaxations are also developed for obtaining upper and lower bounds. We show that the gap between the produced solutions and the lower and upper bounds are around 10% and 7% for the resource and performance oriented problems, respectively. Since the actual traffic can show deviations from the expected values, we also developed an MPLS layer online TE method to compensate the instantaneous fluctuations of the traffic flows. In the proposed method, the LSPs are rerouted dynamically using a specially designed cost function. Our numerical studies show that using the designed cost function results in much lower blockings than using commonly used Widest Shortest Path First and Available Shortest Path First approaches in the literature. The corresponding sub-problem of the multi-layer VTD problem in the WDM layer is the Static Lightpath Establishment (SLE) problem. Along with the capacity and wavelength continuity constraints, we also consider the Bit Error Rate (BER) constraints due to physical layer impairments such as attenuation, polarization mode dispersion and switch crosstalk. This problem is NP-complete even without the BER constraints. We propose a heuristic solution method and develop an exact ILP formulation to evaluate the performance of the proposed method for small problem sizes. Our proposed method produces solutions close to the optimum solutions for the cases in which the ILP formulation could be solved to optimality. Then, these solution methods for the single layer sub-problems are combined in a multi-layer TE scheme to solve the VTD problem in both layers jointly. The proposed TE scheme considers the physical layer limitations and optical impairments. This TE scheme can be applied by keeping each layer’s information hidden from the other layer, but our simulations show that it can produce more effective and efficient solutions when the physical layer topology information is shared with the MPLS layer. We also investigate the effect of non-uniform optical components in terms of impairment characteristics. The numerical results show that more traffic can be routed when all the components in the network have moderate impairment characteristics, compared to the case in which some components have better and some have worse impairment characteristics.Şengezer, NamıkPh.D

SDN-based traffic engineering in data centers, Interconnects, and Carrier Networks

Server virtualization and cloud computing have escalated the bandwidth and performance demands on the DCN (data center network). The main challenges in DCN are maximizing network utilization and ensuring fault tolerance to address multiple node-and-link failures. A multitenant and highly dynamic virtualized environment consists of a large number of endstations, leading to a very large number of flows that challenge the scalability of a solution to network throughput maximization. The challenges are scalability, in terms of address learning, forwarding decision convergence, and forwarding state size, as well as flexibility for offloading with VM migration. Geographically distributed data centers are inter-connected through service providers’ carrier network. Service providers offer wide-area network (WAN) connection such as private lines and MPLS circuits between edges of data centers. DC sides of network operators try to maximize the utilization of such defined overlay WAN connection i.e. data center interconnection (DCI), which applies to edges of DC networks. Service provider sides of network operators try to optimize the core of carrier network. Along with the increasing adoption of ROADM, OTN, and packet switching technologies, traditional two-layer IP/MPLS-over-WDM network has evolved into three-layer IP/MPLS-over-OTN-over-DWDM network and once defined overlay topology is now transitioning to dynamic topologies based on on-demand traffic demands. Network operations are thus divided into three physical sub-networks: DCN, overlay DCI, and multi-layer carrier network. Server virtualization, cloud computing and evolving multilayer carrier network challenge traffic engineering to maximize utilization on all physical subnetworks. The emerging software-defined networking (SDN) architecture moves path computation towards a centralized controller, which has global visibility. Carriers indicate a strong preference for SDN to be interoperable between multiple vendors in heterogeneous transport networks. SDN is a natural way to create a unified control plane across multiple administrative divisions. This thesis contributes SDN-based traffic engineering techniques for maximizing network utilization of DCN, DCI, and carrier network. The first part of the thesis focuses on DCN traffic engineering. Traditional forwarding mechanisms using a single path are not able to take advantages of available multiple physical paths. The state-of-the-art MPTCP (Multipath Transmission Control Protocol) solution uses multiple randomly selected paths, but cannot give total aggregated capacity. Moreover, it works as a TCP process, and so does not support other protocols like UDP. To address these issues, this thesis presents a solution using adaptive multipath routing in a Layer-2 network with static (capacity and latency) metrics, which adapts link and path failures. This solution provides innetwork aggregated path capacity to individual flows, as well as scalability and multitenancy, by separating end-station services from the provider’s network. The results demonstrate an improvement of 14% in the worst bisection bandwidth utilization, compared to the MPTCP with 5 sub-flows. The second part of the thesis focuses on DCI traffic engineering. The existing approaches to reservation services provide limited reservation capabilities, e.g. limited connections over links returned by the traceroute over traditional IP-based networks. Moreover, most existing approaches do not address fault tolerance in the event of node or link failures. To address these issues, this thesis presents ECMP-like multipath routing algorithm and forwarding assignment scheme that increase reservation acceptance rate compared to state-of-art reservation frameworks in the WAN-links between data centers, and such reservations can be configured with a limited number of static forwarding rules on switches. Our prototype provides the RESTful web service interface for link-fail event management and re-routes paths for all the affected reservations. In the final part of the thesis, we focused on multi-layer carrier network traffic engineering. New dynamic traffic trends in upper layers (e.g. IP routing) require dynamic configuration of the optical transport to re-direct the traffic, and this in turn requires an integration of multiple administrative control layers. When multiple bandwidth path requests come from different nodes in different layers, a distributed sequential computation cannot optimize the entire network. Most prior research has focused on the two-layer problem, and recent three-layer research studies are limited to the capacity dimensioning problem. In this thesis, we present an optimization model with MILP formulation for dynamic traffic in a three-layer network, especially taking into account the unique technological constraints of the distinct OTN layer. Our experimental results show how unit cost values of different layers affect network cost and parameters in the presence of multiple sets of traffic loads. We also demonstrate the effectiveness of our proposed heuristic approach

An Overview on Application of Machine Learning Techniques in Optical Networks

Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc. Advanced mathematical tools are required to extract meaningful information from these data and take decisions pertaining to the proper functioning of the networks from the network-generated data. Among these mathematical tools, machine learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration and fault management. The adoption of ML techniques in the field of optical communication networks is motivated by the unprecedented growth of network complexity faced by optical networks in the last few years. Such complexity increase is due to the introduction of a huge number of adjustable and interdependent system parameters (e.g., routing configurations, modulation format, symbol rate, coding schemes, etc.) that are enabled by the usage of coherent transmission/reception technologies, advanced digital signal processing, and compensation of nonlinear effects in optical fiber propagation. In this paper we provide an overview of the application of ML to optical communications and networking. We classify and survey relevant literature dealing with the topic, and we also provide an introductory tutorial on ML for researchers and practitioners interested in this field. Although a good number of research papers have recently appeared, the application of ML to optical networks is still in its infancy: to stimulate further work in this area, we conclude this paper proposing new possible research directions

Learning Maximum Margin Channel Decoders

The problem of learning a channel decoder is considered for two channel models. The first model is an additive noise channel whose noise distribution is unknown and nonparametric. The learner is provided with a fixed codebook and a dataset comprised of independent samples of the noise, and is required to select a precision matrix for a nearest neighbor decoder in terms of the Mahalanobis distance. The second model is a non-linear channel with additive white Gaussian noise and unknown channel transformation. The learner is provided with a fixed codebook and a dataset comprised of independent input-output samples of the channel, and is required to select a matrix for a nearest neighbor decoder with a linear kernel. For both models, the objective of maximizing the margin of the decoder is addressed. Accordingly, for each channel model, a regularized loss minimization problem with a codebook-related regularization term and hinge-like loss function is developed, which is inspired by the support vector machine paradigm for classification problems. Expected generalization error bounds for the error probability loss function are provided for both models, under optimal choice of the regularization parameter. For the additive noise channel, a theoretical guidance for choosing the training signal-to-noise ratio is proposed based on this bound. In addition, for the non-linear channel, a high probability uniform generalization error bound is provided for the hypothesis class. For each channel, a stochastic sub-gradient descent algorithm for solving the regularized loss minimization problem is proposed, and an optimization error bound is stated. The performance of the proposed algorithms is demonstrated through several examples