1,099 research outputs found

    Attack-Aware Routing and Wavelength Assignment of Scheduled Lightpath Demands

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    In Transparent Optical Networks, tra c is carried over lightpaths, creating a vir- tual topology over the physical connections of optical bers. Due to the increasingly high data rates and the vulnerabilities related to the transparency of optical network, security issues in transparent wavelength division multiplexing (WDM) optical net- works have become of great signi cance to network managers. In this thesis, we intro- duce some basic concepts of transparent optical network, the types and circumstances of physical-layer attacks and analysis of related work at rst. In addition, based on the previous researches, we present a novel approach and several new objective cri- terions for the problem of attack-aware routing and wavelength assignment. Integer Linear Programming (ILP) formulation is used to solve the routing sub-problem with the objective to minimize the disruption of physical-layer attack as well as to opti- mize Routing and Wavelength Assignment (RWA) of scheduled transparent optical network

    Survivability aspects of future optical backbone networks

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    In huidige glasvezelnetwerken kan een enkele vezel een gigantische hoeveelheid data dragen, ruwweg het equivalent van 25 miljoen gelijktijdige telefoongesprekken. Hierdoor zullen netwerkstoringen, zoals breuken van een glasvezelkabel, de communicatie van een groot aantal eindgebruikers verstoren. Netwerkoperatoren kiezen er dan ook voor om hun netwerk zo te bouwen dat zulke grote storingen automatisch opgevangen worden. Dit proefschrift spitst zich toe op twee aspecten rond de overleefbaarheid in toekomstige optische netwerken. De eerste doelstelling die beoogd wordt is het tot stand brengen vanrobuuste dataverbindingen over meerdere netwerken. Door voldoende betrouwbare verbindingen tot stand te brengen over een infrastructuur die niet door een enkele entiteit wordt beheerd kan men bv. weredwijd Internettelevisie van hoge kwaliteit aanbieden. De bestudeerde oplossing heeft niet enkel tot doel om deze zeer betrouwbare verbinding te berekenen, maar ook om dit te bewerkstelligen met een minimum aan gebruikte netwerkcapaciteit. De tweede doelstelling was om een antwoord te formuleren om de vraag hoe het toepassen van optische schakelsystemen gebaseerd op herconfigureerbare optische multiplexers een impact heeft op de overleefbaarheid van een optisch netwerk. Bij lagere volumes hebben optisch geschakelde netwerken weinig voordeel van dergelijke gesofistikeerde methoden. Elektronisch geschakelde netwerken vertonen geen afhankelijkheid van het datavolume en hebben altijd baat bij optimalisatie

    Link Fault Localization using Bi-directional M-Trails in All-Optical Mesh Networks

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    Failure Localization Aware Protection in All-Optical Networks

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    The recent development of optical signal processing and switching makes the all-optical networks a potential candidate for the underlying transmission system in the near future. However, despite its higher transmission data rate and efficiency, the lack of optical-electro-optical (OEO) conversions makes fault management a challenge. A single fiber cut can interrupt several connections, disrupting many services which results in a massive loss of data. With the ever-growing demand for time-sensitive applications, the ability to maintain service continuity in communication networks has only been growing in importance. In order to guarantee network survivability, fast fault localization and fault recovery are essential. Conventional monitoring-trail (m-trail) based schemes can unambiguously localize link failures. However, the deployment of m-trail requires extra transceivers and wavelengths dedicated to monitoring the link state. Non-negligible overhead makes m-trail schemes neither scalable nor practicable. In this thesis, we propose two Failure Localization Aware (FLA) routing schemes to aid failure localization. When a link fails, all traversing lightpaths become dark, and the transceiver at the end node of each interrupted ligthpath issues an alarm signal to report the path failure. By correlating the information of all affected and unaffected paths, it is possible to narrow down the number of possible fault locations to just a few possible locations. However, without the assistance of dedicated supervisory lightpaths, and based solely on the alarm generated by the interrupted lightpaths, ambiguity in failure localization may be unavoidable. Hence, we design a Failure Localization Aware Routing and Wavelength Assignment (FLA-RWA) scheme, the Least Ambiguous Path (LAP) routing scheme, to dynamically allocate connection requests with minimum ambiguity in the localization of a link failure. The performance of the proposed heuristic is evaluated and compared with traditional RWA algorithms via network simulations. The results show that the proposed LAP algorithm achieves the lowest ambiguity among all examined schemes, at the cost of slightly higher wavelength consumption than the alternate shortest path scheme. We also propose a Failure Localization Aware Protection (FLA-P) scheme that is based on the idea of also monitoring the protection paths in a system with path protection for failure localization. The Least Ambiguous Protection Path (LAPP) routing algorithm arranges the protection path routes with the objective of minimizing the ambiguity in failure localization. We evaluate and compare the ambiguity in fault localization when monitoring only the working paths and when monitoring both working and protection paths. We also compare the performance of protection paths with different schemes in regards to fault localization

    Physical-Layer Attacks in Transparent Optical Networks

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    Neighborhood Failure Localization in All-Optical Networks via Monitoring Trails

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    Shared protection, such as failure dependent protection (FDP), is well recognized for its outstanding capacity efficiency in all-optical mesh networks, at the expense of lengthy restoration time due to multi-hop signaling mechanisms for failure localization, notification, and device configuration. This paper investigates a novel monitoring trail (m-trail) scenario, called Global Neighborhood Failure Localization (G-NFL), that aims to enable any shared protection scheme, including FDP, for achieving all-optical and ultra-fast failure restoration. We firstly define neighborhood of a node, which is a set of links whose failure states should be known to the node in restoration of the corresponding working lightpaths (W-LPs). By assuming every node can obtain the on-off status of traversing m-trails and W-LPs via lambda monitoring, the proposed G-NFL problem routes a set of m-trails such that each node can localize any failure in its neighborhood. Bound analysis is performed on the minimum bandwidth required for m-trails under the proposed G-NFL problem. Then a simple yet efficient heuristic approach is presented. Extensive simulation is conducted to verify the proposed G-NFL scenario under a number of different definitions of nodal neighborhood which concern the extent of dependency between the monitoring plane and data plane. The effect of reusing the spare capacity by FDP for supporting m-trails is examined. We conclude that the proposed G-NFL scenario enables a general shared protection scheme, toward signaling-free and ultra-fast failure restoration like p-Cycle, while achieving optimal capacity efficiency as FDP

    A Tutorial on Machine Learning for Failure Management in Optical Networks

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    Failure management plays a role of capital importance in optical networks to avoid service disruptions and to satisfy customers' service level agreements. Machine learning (ML) promises to revolutionize the (mostly manual and human-driven) approaches in which failure management in optical networks has been traditionally managed, by introducing automated methods for failure prediction, detection, localization, and identification. This tutorial provides a gentle introduction to some ML techniques that have been recently applied in the field of the optical-network failure management. It then introduces a taxonomy to classify failure-management tasks and discusses possible applications of ML for these failure management tasks. Finally, for a reader interested in more implementative details, we provide a step-by-step description of how to solve a representative example of a practical failure-management task

    Fault Localization in All-Optical Mesh Networks

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    Fault management is a challenging task in all-optical wavelength division multiplexing (WDM) networks. However, fast fault localization for shared risk link groups (SRLGs) with multiple links is essential for building a fully survival and functional transparent all-optical mesh network. Monitoring trail (m-trail) technology is an effective approach to achieve the goal, whereby a set of m-trails are derived for unambiguous fault localization (UFL). However, an m-trail traverses through a link by utilizing a dedicated wavelength channel (WL), causing a significant amount of resource consumption. In addition, existing m-trail methods incur long and variable alarm dissemination delay. We introduce a novel framework of real-time fault localization in all-optical WDM mesh networks, called the monitoring-burst (m-burst), which aims at initiating a balanced trade-off between consumed monitoring resources and fault localization latency. The m-burst framework has a single monitoring node (MN) and requires one WL in each unidirectional link if the link is traversed by any m-trail. The MN launches short duration optical bursts periodically along each m-trail to probe the links of the m-trail. Bursts along different m-trails are kept non-overlapping through each unidirectional link by scheduling burst launching times from the MN and multiplexing multiple bursts, if any, traversing the link. Thus, the MN can unambiguously localize the failed links by identifying the lost bursts without incurring any alarm dissemination delay. We have proposed several novel m-trail allocation, burst launching time scheduling, and node switch fabric configuration schemes. Numerical results show that the schemes, when deployed in the m-burst framework, are able to localize single-link and multi-link SRLG faults unambiguously, with reasonable fault localization latency, by using at most one WL in each unidirectional link. To reduce the fault localization latency further, we also introduce a novel methodology called nested m-trails. At first, mesh networks are decomposed into cycles and trails. Each cycle (trail) is realized as an independent virtual ring (linear) network using a separate pair of WLs (one WL in each direction) in each undirected link traversed by the cycle (trail). Then, sets of m-trails, i.e., nested m-trails, derived in each virtual network are deployed independently in the m-burst framework for ring (linear) networks. As a result, the fault localization latency is reduced significantly. Moreover, the application of nested m-trails in adaptive probing also reduces the number of sequential probes significantly. Therefore, practical deployment of adaptive probing is now possible. However, the WL consumption of the nested m-trail technique is not limited by one WL per unidirectional link. Thus, further investigation is needed to reduce the WL consumption of the technique.1 yea

    Failure Location in Transparent Optical Networks: The Asymmetry Between False and Missing Alarms

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    Failure location in transparent optical networks is difficult because of the large amount of alarms that a failure can trigger and because of corrupted alarms. One problem that network operators often face is how to set the thresholds in monitoring devices. Setting the thresholds low results in false alarms, whereas setting them high presents the risk of missing a significant degradation in network performance because of missing alarms. In this work, we study the time complexity of the failure location problem in transparent optical networks and provide an efficient algorithm to solve this problem. More significantly, we show that for a network with binary alarms (alarms are either present or not), there is an asymmetry between false and missing alarms. We prove that false alarms can be corrected in polynomial time, but that the correction of missing alarms is NP-hard. Because of this asymmetry between false and missing alarms, false alarms have lesser effect on the accuracy of the diagnosis results than missing alarms do. Network operators therefore, when allowed, should set the threshold low to favor false alarms rather than high

    Machine Learning for Optical Network Security Monitoring: A Practical Perspective

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    In order to accomplish cost-efficient management of complex optical communication networks, operators are seeking automation of network diagnosis and management by means of Machine Learning (ML). To support these objectives, new functions are needed to enable cognitive, autonomous management of optical network security. This paper focuses on the challenges related to the performance of ML-based approaches for detectionand localization of optical-layer attacks, and to their integration with standard Network Management Systems (NMSs). We propose a framework for cognitive security diagnostics that comprises an attack detection module with Supervised Learning (SL), Semi-Supervised Learning (SSL) and Unsupervised Learning (UL) approaches, and an attack localization module that deduces the location of a harmful connection and/or a breached link. The influence of false positives and false negatives is addressed by a newly proposed Window-based Attack Detection (WAD) approach. We provide practical implementation\ua0guidelines for the integration of the framework into the NMS and evaluate its performance in an experimental network testbed subjected to attacks, resulting with the largest optical-layer security experimental dataset reported to date
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