| 1. |
- Gajic, Marija, et al.
(författare)
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A Framework for Spatial and Temporal Evaluation of Network Disaster Recovery
- 2020
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Ingår i: Proceedings of the 32nd International Teletraffic Congress, ITC 2020. ; , s. 37-45
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Konferensbidrag (refereegranskat)abstract
- The support of vital societal functions requires a reliable communication network, especially in the presence of crises and disastrous events. Disasters caused by natural factors including earthquakes, fires, floods or hurricanes can disable network elements such as links and nodes and cause widespread disruption in end users connectivity to network services. Effects of disasters can vary over space and time due to disaster escalation and propagation. Network recovery from disasters requires understanding of both the spatial properties of the hazard at hand, and their temporal evolution. While the former has already been addressed in the literature, existing models and measures are unable to capture the temporal aspects of disaster recovery.This paper proposes a framework for spatial and temporal evaluation of network disaster recovery. It allows for modelling random spatial patterns of disasters in a geographical grid. The temporal aspects captured in our framework include changes due to the progression of a potentially shape-changing disaster across the affected area, as well as to the recovery actions of adaptive network reconfiguration and topology reconstruction undertaken by the network operator. The framework applicability is demonstrated on a content delivery network use case example, where we capture the evolving network performance in terms of the average shortest path length between the peers and the content replicas hosted by servers. By providing insights into the spatial and temporal effects of both disaster escalation and remediation measures, our proposed framework lays down the groundwork for flexible disaster modelling and recovery sequence optimization.
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| 2. |
- Gajic, Marija, et al.
(författare)
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Survivability Assessment of 5G Network Slicing During Massive Outages
- 2023
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Ingår i: Proceedings of 2023 13th International Workshop on Resilient Networks Design and Modeling, RNDM 2023.
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Konferensbidrag (refereegranskat)abstract
- Mobile networks support variety of heterogeneous services, including the emergency and mission-critical ones. The next generation of mobile networks introduces the concept of network slicing where different services can have a dedicated, logically separated virtual network running over a shared physical infrastructure. Each slice may have a specific set of functional and non-functional requirements including performance, security, resilience, and survivability. Given the importance of emergency services during massive outages caused by a natural disaster, the network operators need an efficient way to evaluate the performance of the sliced network in such adverse circumstances. In this paper, we describe how survivability quantification framework can be applied to assess and compare the performance of different slicing configurations during and after massive outages. We demonstrate our proposal in a simplified use-case scenario where the performance metric for each stage of the recovery is represented with delay and throughput of the clients at a sliced, shared bottleneck. The metrics are acquired from OMNeT++ simulations. Survivability is then obtained from an analytical model and the time until the critical services (for the first responders) are recovered is of particular interest. In the scenario we consider 8 application types, 4 priority levels, and 5 approaches to map clients to slices. The results show significant performance variations between different slicing configurations, both for the critical and non-critical applications and thus highlight the importance of having a slicing configuration optimally tailored to the use case.
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| 3. |
- Abedifar, Vahid, et al.
(författare)
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Routing, Modulation and Spectrum Assignment in Programmable Networks based on Optical White Boxes
- 2018
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Ingår i: Journal of Optical Communications and Networking. - : Optical Society of America. - 1943-0620 .- 1943-0639. ; 10:9, s. 723-735
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Tidskriftsartikel (refereegranskat)abstract
- Elastic optical networks (EONs) can help overcome the flexibility challenges imposed by emerging heterogeneous and bandwidth-intensive applications. Among the different solutions for flexible optical nodes, optical white box switches implemented by architecture on demand (AoD) have the capability to dynamically adapt their architecture and module configuration to the switching and processing requirements of the network traffic. Such adaptability allows for unprecedented flexibility in balancing the number of required nodal components in the network, spectral resource usage, and length of the established paths. To investigate these trade-offs and achieve cost-efficient network operation, we formulate the routing, modulation, and spectrum assignment (RMSA) problem in AoD-based EONs and propose three RMSA strategies aimed at optimizing a particular combination of these performance indicators. The strategies rely on a newly proposed internal node configuration matrix that models the structure of optical white box nodes in the network, thus facilitating hardware-aware routing of connection demands. The proposed strategies are evaluated in terms of the number of required modules and the related cost, spectral resource usage, and average path length. Extensive simulation results show that the proposed RMSA strategies can achieve remarkable cost savings by requiring fewer switching modules than the benchmarking approaches, at a favorable trade-off with spectrum usage and path length.
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| 4. |
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| 5. |
- Abeywickrama, Sandu, et al.
(författare)
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Protecting core networks with dual-homing: A study on enhanced network availability, resource efficiency, and energy-savings
- 2016
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Ingår i: Optics Communications. - : Elsevier. - 0030-4018 .- 1873-0310. ; 381, s. 327-335
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Tidskriftsartikel (refereegranskat)abstract
- Core network survivability affects the reliability performance of telecommunication networks and remains one of the most important network design considerations. This paper critically examines the benefits arising from utilizing dual-homing in the optical access networks to provide resource-efficient protection against link and node failures in the optical core segment. Four novel, heuristic-based RWA algorithms that provide dedicated path protection in networks with dual-homing are proposed and studied. These algorithms protect against different failure scenarios (i.e. single link or node failures) and are implemented with different optimization objectives (i.e., minimization of wavelength usage and path length). Results obtained through simulations and comparison with baseline architectures indicate that exploiting dual-homed architecture in the access segment can bring significant improvements in terms of core network resource usage, connection availability, and power consumption.
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| 6. |
- Aparicio Pardo, Ramon, et al.
(författare)
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Balancing CapEx reduction and network stability with stable routing-virtual topology capacity adjustment (SR-VTCA)
- 2013
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Ingår i: Optical Switching and Networkning Journal. - : Elsevier. - 1573-4277 .- 1872-9770. ; 10:4, s. 343-353
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Tidskriftsartikel (refereegranskat)abstract
- This paper investigates the merits of the SR–VTCA (stable routing–virtual topology capacity adjustment) approach as a mechanism to find a beneficial trade-off between network stability and reduction in capital expenditures (CapEx). These are two main objectives for the entities that own the optical infrastructure, such as network operators (NOs), and those also acting as Internet service providers (ISPs). The SR–VTCA scheme is a novel approach to adapt transparent optical networks to time-varying traffic by adjusting the number of lightpaths between node pairs, while keeping the IP routing unchanged. Lightpath bundling (LB) and anycast (AS) switching are combined in SR–VTCA operation to advertise lightpath additions/removals to the IP layer as mere adjustments (increments or decrements) in the capacity, allowing to keep the IP routing stable, and thus, simplifying control plane operations. On the contrary, a fully-reconfigurable (FR) network design, where IP routing can be also modified, would increase the burden in the control plane, but at a higher CapEx reduction, since the optical infrastructure is used more efficiently. In this work, we investigate the CapEx overprovision introduced by SR–VTCA with respect to a FR scheme. In order to do this, SR–VTCA planning problem is first modeled as a MILP formulation. A heuristic procedure based on traffic domination is then proposed to solve large instances of the problem. Exhaustive experiments are conducted comparing the SR–VTCA solutions obtained by the aforementioned MILP and heuristic proposal with solutions found by other optimization methods presented in the literature to solve the FR planning problem. Finally, the results show that SR–VTCA can achieve similar results to the FR case in terms of CapEx reduction, while a huge number of IP reroutings are saved by maintaining IP stability. Thus, SR–VTCA provides an advantageous balance between CapEx overprovisioning and the control plane overhead associated with IP rerouting.
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| 7. |
- Archambault, Emile, et al.
(författare)
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Routing and spectrum assignment in elastic filterless optical networks
- 2016
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Ingår i: IEEE/ACM Transactions on Networking. - : IEEE. - 1063-6692 .- 1558-2566. ; 24:6, s. 3578-3592
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Tidskriftsartikel (refereegranskat)abstract
- Elastic optical networking is considered a promising candidate to improve the spectral efficiency of optical networks. One of the most important planning challenges of elastic optical networks is the NP-hard routing and spectrum assignment (RSA) problem. In this paper, we investigate offline RSA in elastic filterless optical networks, which use a passive broadcast-and-select architecture to offer network agility. Here elastic optical network is referred to as the optical network that can adapt the channel bandwidth, data rate, and transmission format for each traffic demand in order to offer maximum throughput. In elastic filterless networks, the presence of unfiltered signals resulting from the drop-and-continue node architecture must be considered as an additional constraint in the RSA problem. In this paper, first the RSA problem in elastic filterless networks is formulated by using integer linear program (ILP) to obtain optimal solutions for small networks. Due to the problem complexity, two efficient RSA heuristics are also proposed to achieve suboptimal solutions for larger networks in reasonable time. Simulation results show that significant bandwidth savings in elastic filterless networks can be achieved compared to the fixed-grid filterless solutions. The proposed approach is further tested in multi-period traffic scenarios and combined with periodical spectrum defragmentation, leading to additional improvement in spectrum utilization of elastic filterless optical networks.
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| 8. |
- Casellas, Ramon, et al.
(författare)
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Introduction to the ONDM2020 special issue
- 2021
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Ingår i: Journal of Optical Communications and Networking. - 1943-0620 .- 1943-0639. ; 13:6, s. ONDM1-ONDM2
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This JOCN special issue includes extended versions of selected papers that were presented at the 24th International Conference on Optical Network Design and Modeling (ONDM2020), which took place virtually on May 18-21, 2020. The topics covered by the papers represent clear trends in current optical networking research including filterless optical networks and their applicability in metropolitan scenarios; programmable, software-defined-networking-enabled sliceable bandwidth variable transceivers supporting multi-dimensionality; and two applications of machine learning-the cognitive reconfiguration of data-center networks in support of high-performance computing, and quality of transmission estimation for reduced margins.
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| 9. |
- Chan, Vincent, et al.
(författare)
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Network-wide localization of optical-layer attacks
- 2020
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. ; 11616 LNCS, s. 310-322
-
Konferensbidrag (refereegranskat)abstract
- Optical networks are vulnerable to a range of attacks targeting service disruption at the physical layer, such as the insertion of harmful signals that can propagate through the network and affect co-propagating channels. Detection of such attacks and localization of their source, a prerequisite for secure network operation, is a challenging task due to the limitations in optical performance monitoring, as well as the scalability and cost issues. In this paper, we propose an approach for localizing the source of a jamming attack by modeling the worst-case scope of each connection as a potential carrier of a harmful signal. We define binary words called attack syndromes to model the health of each connection at the receiver which, when unique, unambiguously identify the harmful connection. To ensure attack syndrome uniqueness, we propose an optimization approach to design attack monitoring trails such that their number and length is minimal. This allows us to use the optical network as a sensor for physical-layer attacks. Numerical simulation results indicate that our approach obtains network-wide attack source localization at only 5.8% average resource overhead for the attack monitoring trails.
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| 10. |
- de Sousa, Amaro, et al.
(författare)
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Structural Methods to Improve the Robustness of Anycast Communications to Large-Scale Failures
- 2020
-
Ingår i: Guide to Disaster-Resilient Communication Networks. - Cham : Springer International Publishing. - 9783030446857 ; , s. 401-425
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- This chapter is dedicated to the description of structural methods aiming to improve the robustness of anycast communications to large-scale failures, either due to natural disasters or malicious human activities. The chapter considers both software-defined networks (SDNs) where the anycast nodes are the nodes hosting SDN controllers, and content delivery networks (CDNs) where the anycast nodes are the nodes hosting content replicas. Most of the structural methods described in this chapter aim to optimally select the anycast nodes in a given network. The chapter first addresses the robustness of anycast communications to natural disasters based on geodiversity routing. Then, different methods are described to select the SDN controller locations aiming to maximize the SDN control plane robustness to malicious node attacks. Finally, the chapter addresses the robustness of CDNs to malicious link cuts by describing methods for the network upgrade (based either on the addition of new links or new replica locations) and for the optimal selection of content replica locations.
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| 11. |
- Dobrijevic, O., et al.
(författare)
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Another price to pay : An availability analysis for SDN virtualization with network hypervisors
- 2018
-
Ingår i: Proceedings of 2018 10th International Workshop on Resilient Networks Design and Modeling, RNDM 2018. - : Institute of Electrical and Electronics Engineers Inc.. - 9781538670309
-
Konferensbidrag (refereegranskat)abstract
- Communication networks are embracing the software defined networking (SDN) paradigm. Its architectural shift assumes that a remote SDN controller (SDNC) in the control plane is responsible for configuring the underlying devices of the forwarding plane. In order to support flexibility-motivated network slicing, SDN-based networks employ another entity in the control plane, a network hypervisor (NH). This paper first discusses different protection strategies for the control plane with NHs and presents the corresponding availability models, which assume possible failures of links and nodes in the forwarding plane and the control plane. An analysis of these protection alternatives is then performed so as to compare average control plane availability, average path length for the control communication that traverses NH, and infrastructure resources required to support them. Our results confirm the intuition that the NH introduction generally results in a reduction of the control plane availability, which stresses the need for appropriate protection. However, the availability achieved by each of the considered strategies is impacted differently by the node availability and the link failure probability, thus calling for a careful selection that is based on the infrastructure features.
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| 12. |
- Dzanko, Matija, et al.
(författare)
-
Dedicated path protection for optical networks based on function programmable nodes
- 2018
-
Ingår i: Optical Switching and Networkning Journal. - : Elsevier BV. - 1573-4277 .- 1872-9770. ; 27, s. 79-87
-
Tidskriftsartikel (refereegranskat)abstract
- Due to the constantly increasing volumes and tightening reliability requirements of network traffic, survivability is one of the key concerns in optical network design. Optical "white box" nodes based on the Architecture on Demand (AoD) paradigm allow for self-healing of nodal component failures due to their architectural flexibility and the ability to employ idle components for failure recovery. By incorporating node-level survivability with network-level protection from link failures, resiliency of optical networks can be significantly improved. To this end, we propose a survivable routing algorithm for AoD-based networks called Dedicated Path Protection with Enforced Fiber Switching (DPP-EFS), which combines self-healing at the node level with dedicated path protection at the network level. The algorithm aims at improving the self-healing capabilities of the nodes by increasing the percentage of fiber switching (FS). Namely, fiber-switched lightpaths require a minimal amount of processing within the node (i.e. only signal switching), while other aspects of processing (e.g. demultiplexing, bandwidth virtualization) and the related components (i.e. demultiplexers, splitters, wavelength selective switches) remain unused and may be used as redundancy. On the other hand, lightpaths that are not eligible for FS have to be re-routed to alternative, longer paths in order to allow for FS between certain ports within the node. Therefore, the proposed algorithm pursues an advantageous trade-off between the increase of the number of idle components which can be used as redundancy at the node level and the unwanted length increase of lightpaths re-routed to render components redundant. For particular cases when DPP-EFS is not able to reduce the mean down time (MDT) in the network merely by increasing the percentage of fiber switching, we propose an algorithm for Dedicated Path Protection with Fixed Shortest Path routing and added Redundancy (DPP-FSP-RED) which adds additional spare components at strategic nodes to ensure that all connections have at least one redundant node component along their path. Simulation results show a significant reduction in MDT with minimal extra capital expenses.
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| 13. |
- Dzanko, Matija, et al.
(författare)
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Self-healing optical networks with Architecture on Demand nodes
- 2013
-
Ingår i: 39th European Conference and Exhibition on Optical Communication, ECOC 2013. - : IEEE conference proceedings.
-
Konferensbidrag (refereegranskat)abstract
- Architecture on Demand (AoD) can provide self-healing at the optical node level due to its flexibility and the ability to employ idle components for failure recovery. We study the impact of AoD on network availability at different traffic switching granularities, showing significant improvements compared to traditional static node architecture.
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| 14. |
- Etezadi, Ehsan, 1993, et al.
(författare)
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Deep reinforcement learning for proactive spectrum defragmentation in elastic optical networks [Invited]
- 2023
-
Ingår i: Journal of Optical Communications and Networking. - 1943-0620 .- 1943-0639. ; 15:10, s. E86-E96
-
Tidskriftsartikel (refereegranskat)abstract
- The immense growth of Internet traffic calls for advanced techniques to enable the dynamic operation of optical networks, efficient use of spectral resources, and automation. In this paper, we investigate the proactive spectrum defragmentation (SD ) problem in elastic optical networks and propose a novel deep reinforcement learning-based framework DeepDefrag to increase spectral usage efficiency. Unlike the conventional, often threshold-based heuristic algorithms that address a subset of the defragmentation related tasks and have limited automation capabilities, DeepDefrag jointly addresses the three main aspects of the SD process: determining when to perform defragmentation, which connections to reconfigure, and which part of the spectrum to reallocate them to. By considering services attributes, spectrum occupancy state expressed by several different fragmentation metrics, as well as reconfiguration cost, DeepDefragmis able to consistently select appropriate reconfiguration actions over the network lifetime and adapt to changing conditions. Extensive simulation results reveal superior performance of the proposed scheme over a scenario with exhaustive defragmentation and a well-known benchmark heuristic from the literature, achieving lower blocking probability at a smaller defragmentation overhead.
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| 15. |
- Etezadi, Ehsan, 1993, et al.
(författare)
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DeepDefrag: A deep reinforcement learning framework for spectrum defragmentation
- 2022
-
Ingår i: 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings. ; , s. 3694-3699
-
Konferensbidrag (refereegranskat)abstract
- Exponential growth of bandwidth demand, spurred by emerging network services with diverse characteristics and stringent performance requirements, drives the need for dynamic operation of optical networks, efficient use of spectral resources, and automation. One of the main challenges of dynamic, resource-efficient Elastic Optical Networks (EONs) is spectrum fragmentation. Fragmented, stranded spectrum slots lead to poor resource utilization and increase the blocking probability of incoming service requests. Conventional approaches for Spectrum Defragmentation (SD) apply various criteria to decide when, and which portion of the spectrum to defragment. However, these polices often address only a subset of tasks related to defragmentation, are not adaptable, and have limited automation potential. To address these issues, we propose DeepDefrag, a novel framework based on reinforcement learning that addresses the main aspects of the SD process: determining when to perform defragmentation, which connections to reconfigure, and which part of the spectrum to reallocate them to. DeepDefrag outperforms the well-known Older-First First-Fit (OF-FF) defragmentation heuristic, achieving lower blocking probability under smaller defragmentation overhead.
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| 16. |
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| 17. |
- Etezadi, Ehsan, 1993, et al.
(författare)
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Proactive Spectrum Defragmentation Leveraging Spectrum Occupancy State Information
- 2023
-
Ingår i: International Conference on Transparent Optical Networks. - 2162-7339. ; 2023-July
-
Konferensbidrag (refereegranskat)abstract
- One of the main obstacles to efficient resource usage under dynamic traffic in elastic optical networks (EONs) is spectrum fragmentation (SF), leading to blocking of incoming service requests. Proactive spectrum defragmentation (SD) approaches periodically reallocate services to ensure better alignment of available spectrum slots across different links and alleviate blocking. The services for reallocation are commonly selected based on their properties, e.g., age, without detailed consideration of prior or posterior spectrum occupancy states. In this paper, we propose a heuristic algorithm for proactive SD that considers different spectrum fragmentation metrics to select services for reallocation. We analyze the relationship between these metrics and the resulting service blocking probability. Simulation results show that the proposed heuristic outperforms the benchmarking proactive SD algorithms from the literature in reducing blocking probability.
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| 18. |
- Etezadi, Ehsan, 1993, et al.
(författare)
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Programmable Filterless Optical Networks: Architecture, Design and Resource Allocation
- 2024
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Ingår i: IEEE/ACM Transactions on Networking. - 1558-2566 .- 1063-6692. ; 32:2, s. 1096-1109
-
Tidskriftsartikel (refereegranskat)abstract
- Filterless optical networks (FONs) are a costeffective optical networking technology that replaces reconfigurable optical add-drop multiplexers, used in conventional, wavelength-switched optical networks (WSONs), by passive optical splitters and couplers. FONs follow the drop-and-waste transmission scheme, i.e., broadcast signals without filtering, which generates spectrum waste. Programmable filterless optical networks (PFONs) reduce this waste by equipping network nodes with programmable optical white box switches that support arbitrary interconnections of passive elements. Cost-efficient PFON solutions require optimal routing, modulation format and spectrum assignment (RMSA) to connection requests, as well as optimal design of the node architecture. This paper presents an optimization framework for PFONs. We formulate the RMSA problem in PFONs as a single-step integer linear program (ILP) that jointly minimizes the total spectrum and optical component usage. As RMSA is an NP-complete problem, we propose a two-step ILP formulation that addresses the RMSA sub-problems separately and seeks sub-optimal solutions to larger problem instances in acceptable time. Simulation results indicate a beneficial trade-off between component usage and spectrum consumption in proposed PFON solutions. They use up to 64% less spectrum than FONs, up to 84% fewer active switching elements than WSONs, and up to 81% fewer optical amplifiers at network nodes than FONs or WSONs.
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| 19. |
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| 20. |
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| 21. |
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| 22. |
- Fan, Yuchuan, et al.
(författare)
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EVM Estimation for Performance Monitoring in Coherent Optical Systems : An Approach of Linear Regression
- 2022
-
Ingår i: Optics InfoBase Conference Papers. - : Optica Publishing Group (formerly OSA). - 9781557528209
-
Konferensbidrag (refereegranskat)abstract
- We experimentally demonstrate the effectiveness of a simple linear regression scheme for optical performance monitoring when applied after modulation format identification. It outperforms the FFNN-based benchmark scheme providing 0.2% mean absolute error for EVM estimation., © 2022 The Author(s)
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| 23. |
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| 24. |
- Fan, Yuchuan, et al.
(författare)
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Experimental validation of CNNs versus FFNNs for time- and energy-efficient EVM estimation in coherent optical systems
- 2021
-
Ingår i: Journal of Optical Communications and Networking. - : OPTICAL SOC AMER. - 1943-0620 .- 1943-0639. ; 13:10, s. E63-E71
-
Tidskriftsartikel (refereegranskat)abstract
- Error vector magnitude (EVM) has proven to be one of the optical performance monitoring metrics providing the quantitative estimation of error statistics. However, the EVM estimation efficiency has not been fully exploited in terms of complexity and energy consumption. Therefore, in this paper, we explore two deep-learning-based EVM estimation schemes. The first scheme exploits convolutional neural networks (CNNs) to extract EVM information from images of the constellation diagram in the in-phase/quadrature (IQ) complex plane or amplitude histograms (AHs). The second scheme relies on feedforward neural networks (FFNNs) extracting features from a vectorized representation of AHs. In both cases, we use short sequences of 32 Gbaud m-ary quadrature amplitude modulation (mQAM) signals captured before or after a carrier phase recovery. The impacts of the sequence length, neural network structure, and data set representation on the EVM estimation accuracy as well as the model training time are thoroughly studied. Furthermore, we validate the performance of the proposed schemes using the experimental implementation of 28 Gbaud 64QAM signals. We achieve a mean absolute estimation error below 0.15%, with short signals consisting of only 100 symbols per IQ cluster. Considering the estimation accuracy, the implementation complexity, and the potential energy savings, the proposed CNN- and FFNN-based schemes can be used to perform time-sensitive and accurate EVM estimation for mQAM signal quality monitoring purposes.
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| 25. |
- Fan, Yuchuan, et al.
(författare)
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Fast signal quality monitoring for coherent communications enabled by CNN-based EVM estimation
- 2021
-
Ingår i: Journal of Optical Communications and Networking. - : Institute of Electrical and Electronics Engineers Inc.. - 1943-0620 .- 1943-0639. ; 13:4, s. B12-B20
-
Tidskriftsartikel (refereegranskat)abstract
- We propose a fast and accurate signal quality monitoring scheme that uses convolutional neural networks for error vector magnitude (EVM) estimation in coherent optical communications. We build a regression model to extract EVM information from complex signal constellation diagrams using a small number of received symbols. For the additive-white-Gaussian-noise-impaired channel, the proposed EVM estimation scheme shows a normalized mean absolute estimation error of 3.7% for quadrature phase-shift keying, 2.2% for 16-Ary quadrature amplitude modulation (16QAM), and 1.1% for 64QAM signals, requiring only 100 symbols per constellation cluster in each observation period. Therefore, it can be used as a low-complexity alternative to conventional bit-error-rate estimation, enabling solutions for intelligent optical performance monitoring.
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| 26. |
- Fan, Yuchuan, et al.
(författare)
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Feedforward Neural Network-Based EVM Estimation : Impairment Tolerance in Coherent Optical Systems
- 2022
-
Ingår i: IEEE Journal of Selected Topics in Quantum Electronics. - : Institute of Electrical and Electronics Engineers Inc.. - 1077-260X .- 1558-4542. ; 28:4
-
Tidskriftsartikel (refereegranskat)abstract
- Error vector magnitude (EVM) is commonly used for evaluating the quality of m-ary quadrature amplitude modulation (mQAM) signals. Recently proposed deep learning techniques for EVM estimation extend the functionality of conventional optical performance monitoring (OPM). In this article, we evaluate the tolerance of our developed EVM estimation scheme against various impairments in coherent optical systems. In particular, we analyze the signal quality monitoring capabilities in the presence of residual in-phase/quadrature (IQ) imbalance, fiber nonlinearity, and laser phase noise. We use feedforward neural networks (FFNNs) to extract the EVM information from amplitude histograms of 100 symbols per IQ cluster signal sequence captured before carrier phase recovery. We perform simulations of the considered impairments, along with an experimental investigation of the impact of laser phase noise. To investigate the tolerance of the EVM estimation scheme to each impairment type, we compare the accuracy for three training methods: 1) training without impairment, 2) training one model for all impairments, and 3) training an independent model for each impairment. Results indicate a good generalization of the proposed EVM estimation scheme, thus providing a valuable reference for developing next-generation intelligent OPM systems.
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| 27. |
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| 28. |
- Furdek, Marija, 1985-, et al.
(författare)
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Attack-aware dedicated path protection in optical networks
- 2016
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Ingår i: Journal of Lightwave Technology. - : IEEE. - 0733-8724 .- 1558-2213. ; 34:4, s. 1050-1061
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Tidskriftsartikel (refereegranskat)abstract
- Due to the high data rates in optical networks,physical-layer attacks targeting service degradation, such as powerjamming, can potentially lead to large data and revenue losses.Conventional network survivability approaches which establishlink-disjoint working and backup paths to protect from componentfaults may not provide adequate protection for such attacks.Namely, the working and the backup paths, although link-disjoint,might both be affected by a single attack scenario due to specificattack propagation characteristics. To enhance the existing survivabilityapproaches, we utilize the concept of an attack group(AG) which incorporates these characteristics to identify connectionswhich can simultaneously be affected by a single attack. Weapply this concept to dedicated path protection (DPP) and developattack-aware DPP (AA-DPP) approaches which aim to establishAG-disjoint primary and backup paths in a cost-effective manner.We provide a two-step ILP formulation for the routing and wavelengthassignment of the working and backup paths, as well as aheuristic for larger problem instances. Numerical results indicatethat the proposed approaches provide dedicated path protectionschemes with enhanced attack protection without using more resources(i.e., wavelengths, average path lengths) than standardDPPmethods.
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| 29. |
- Furdek, Marija, 1985-, et al.
(författare)
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Attack-aware wavelength assignment for localization of in-band crosstalk attack propagation
- 2010
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Ingår i: Journal of Optical Communications and Networking. - : IEEE Press. - 1943-0620 .- 1943-0639. ; 2:11, s. 1000-1009
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Tidskriftsartikel (refereegranskat)abstract
- The high data rates employed by wavelength division multiplexing transparent optical networks make them most suitable for today's growing network traffic demands. However, their transparency imposes several vulnerabilities in network security, enabling malicious signals to propagate from the source to other parts of the network without losing their attacking capabilities. Furthermore, detecting, locating the source, and localizing the spreading of such physical-layer attacks is more difficult since monitoring must be performed in the optical domain. While most failure and attack management approaches focus on network recovery after a fault or an attack has already occurred, we suggest a novel safety strategy, proposing a prevention-oriented method to aid attack localization and source identification in the planning phase. In this paper, we propose attack-aware wavelength assignment that minimizes the worst-case potential propagation of in-band crosstalk jamming attacks. We define a new objective criterion for the wavelength assignment (WA) problem, called the propagating crosstalk attack radius (P-CAR), and develop heuristic algorithms aimed at minimizing both the P-CAR and the number of wavelengths used. Our aim is to achieve better protection, but without the need for extra resources. We compare our algorithms with existing WA approaches, illustrating their benefits with respect to transparent optical networks' security, as well as the associated wavelength utilization.
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| 30. |
- Furdek, Marija, 1985-, et al.
(författare)
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Attack-survivable routing and wavelength assignment for high-power jamming
- 2013
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Ingår i: 2013 17TH INTERNATIONAL CONFERENCE ON OPTICAL NETWORKING DESIGN AND MODELING (ONDM). - : IEEE conference proceedings.
-
Konferensbidrag (refereegranskat)abstract
- Transparent optical networks (TONs) are vulnerable to high-power jamming attacks aimed at service disruption by exploiting the inherent characteristics of optical fibers, amplifiers and switches. In this type of attack, a high-power jamming signal is injected in the network to degrade the quality of legitimate user signals. Conventional survivability approaches which protect transmission in occurrences of component faults might not provide protection from attacks as the working and the backup path of a connection might both be within the reach of the attacking signal. In this paper, we propose a novel concept of identifying a so-called Attack Group (AG) of each lightpath and develop a dedicated path protection approach which ensures that the primary and the backup path of each connection be attack group disjoint, i.e., not within the reach of a same potential attacker. Furthermore, the proposed attack-survivable routing and wavelength assignment is aimed at reducing the maximum potential damage from these attacks, measured by an objective criterion called Attack Radius (AR), as well as minimizing the number of used wavelengths to be resource-effective. In comparison with generic dedicated path protection without attack awareness, the proposed approach shows a significant enhancement of network survivability in the presence of attacks at a small trade-off of increased wavelength usage.
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| 31. |
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| 32. |
- Furdek, Marija, 1985-, et al.
(författare)
-
Programmable Filterless Network Architecture Based on Optical White Boxes
- 2016
-
Ingår i: 20Th International Conference On Optical Network Design And Modeling (Ondm 2016). - : IEEE conference proceedings.
-
Konferensbidrag (refereegranskat)abstract
- We propose and evaluate a novel architecture enabling high-capacity, resource efficient and agile elastic optical networks. It is based on sliceable bandwidth-variable transponders and optical white box switches which route optical signals without filtering them. Instead of using active filtering components, each node is equipped with an optical white box based on a programmable optical switch that serves as an optical backplane. It provides interconnections between input/output ports and passive splitters and couplers. Due to signal broadcast and the absence of filtering (so-called drop-and-waste transmission), some of the signals appear on unintended links which can lead to an overhead in spectrum usage. To address this issue, we formulate the problem of signal routing, modulation format and spectrum assignment in programmable filterless networks based on optical white boxes as an integer linear program (ILP) with the objective to minimize the total spectrum usage. Simulation results indicate that our proposed solution obtains a beneficial tradeoff between component usage and spectrum consumption, using a drastically lower number of active switching elements than the conventional networks based on hard-wired reconfigurable add/drop multiplexers, and lowering the maximum used frequency slot by up to 48% compared to existing passive filterless networks.
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| 33. |
- Furdek, Marija, 1985-, et al.
(författare)
-
Survivable manycast, anycast and replica placement in optical inter-datacenter networks
- 2017
-
Ingår i: 2017 19th International Conference on Transparent Optical Networks (ICTON). - : IEEE Computer Society. - 9781538608586
-
Konferensbidrag (refereegranskat)abstract
- Inter-datacenter networks need to support datacenter communication with the end-users, as well as content replication and synchronization between datacenters in a reliable manner. This paper presents a survivable manycast, anycast and replica placement strategy for optical inter-datacenter networks resulting in reduced overall network resource consumption.
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| 34. |
- Furdek, Marija, 1985-
(författare)
-
Towards Secure and Self-Diagnosable Optical Networks
- 2018
-
Ingår i: Proceedings of the 2018 Photonics in Switching and Computing, PSC 2018. - : Institute of Electrical and Electronics Engineers Inc.. - 9781538693926
-
Konferensbidrag (refereegranskat)abstract
- Given the pivotal role of optical networks in supporting critical societal services, their robustness to deliberate attacks targeting disruption at the physical layer requires advanced approaches for security assurance, diagnostics and response. This paper analyzes the necessary advancements in optical network security needed to achieve secure and self-diagnosable systems.
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| 35. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
-
Demonstration of Machine-Learning-Assisted Security Monitoring in Optical Networks
- 2019
-
Ingår i: Proceedings of the 45th European Conference on Optical Communication, ECOC 2019.
-
Konferensbidrag (refereegranskat)abstract
- We report on the first demonstration of machine-learning-assisted detection, identification and localisation of optical-layer attacks integrated into network management system and verified on real-life experimental attack traces from a network operator testbed.
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| 36. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
-
Design of Programmable Filterless Optical Networks
- 2020
-
Ingår i: 2020 Photonics North, PN 2020.
-
Konferensbidrag (refereegranskat)abstract
- We present the main operating principles and guidelines for the design of programmable filterless networks.
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| 37. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
-
Enhancing optical network security with machine learning
- 2019
-
Ingår i: International Conference on Transparent Optical Networks. - 2162-7339. ; 2019-July
-
Konferensbidrag (refereegranskat)abstract
- As critical communication infrastructure, optical networks have a vital role in safe and dependable transmission of massive amounts of data, supporting essential societal services. However, these networks are inherently vulnerable to a multitude of deliberate, man-made attacks targeting service disruption at the physical layer. Physical-layer attack techniques can range in their scope and effects, level of sophistication, locality, detectability, etc. An example of a relatively unsophisticated attack method is a deliberate fiber cut, typically targeting critical network elements (e.g., links with the highest betweenness) and resulting in straightforward transmission interruption [1]. More refined attack techniques rely on the insertion of harmful signal (e.g. in- and out-of-band jamming) [2], or on external tampering with the fiber to degrade the transmission quality (e.g., polarization scrambling via fiber squeezing) [3]. Diverse attack techniques cause different effects, which complicates their detectability. For example, some attacks add unfilterable noise, some reduce the power of the affected optical channels, while some inflict changes in the state of polarization too quick for the coherent receiver to compensate [3]. Therefore, monitoring only the spectrum [4], or individual signal parameters such as the power, optical signal-to-noise ratio (OSNR), or presence of errors may result in inaccurate diagnostics and root cause attribution. This obstacle in quick recovery of affected services is further pronounced for newly emerging attack techniques whose effects may deviate from the attack signatures previously known to the network management system [5].The complexity of the evolving physical-layer security landscape and the intricate interplay of different optical performance monitoring (OPM) parameters in the presence of diverse attack methods can greatly benefit from the application of machine learning techniques capable of deep data analysis. In this talk, we present how different data analytics and machine learning approaches can be applied to interpret the OPM data reported from the commercially available coherent receivers to identify anomalous operation and trigger security threat warnings. The analytical techniques are applied to experimental data obtained from an operator's metropolitan testbed subjected to in- and out-of-band jamming, and external polarization scrambling attacks. We begin with an analysis of the optical signal degradation caused by the different attack methods. We then investigate the application of several supervised learning approaches that, once trained on the experimental data, can detect the presence of an attack and identify its type and intensity. The accuracy of several classifiers is scrutinized, along with the relevance of OPM parameters reported by the coherent receivers and the impact of missing features. To gain insight into the potential of the network to detect emerging, previously unseen attack techniques, we further analyse the performance of unsupervised learning techniques that detect the anomalies in signal parameters introduced by attacks. The presented findings help achieve timely and accurate detection of physical-layer attacks and serve as a prerequisite for fast and effective attack response and network recovery.
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| 38. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
-
Experiment-based detection of service disruption attacks in optical networks using data analytics and unsupervised learning
- 2019
-
Ingår i: Metro and Data Center Optical Networks and Short-Reach Links II; 109460D. - : SPIE. - 0277-786X .- 1996-756X. - 9781510625341 ; 10946
-
Konferensbidrag (refereegranskat)abstract
- The paper addresses the detection of malicious attacks targeting service disruption at the optical layer as a key prerequisite for fast and effective attack response and network recovery. We experimentally demonstrate the effects of signal insertion attacks with varying intensity in a real-life scenario. By applying data analytics tools, we analyze the properties of the obtained dataset to determine how the relationships among different optical performance monitoring (OPM) parameters of the signal change in the presence of an attack as opposed to the normal operating conditions. In addition, we evaluate the performance of an unsupervised learning technique, i.e., a clustering algorithm for anomaly detection, which can detect attacks as anomalies without prior knowledge of the attacks. We demonstrate the potential and the challenges of unsupervised learning for attack detection, propose guidelines for attack signature identification needed for the detection of the considered attack methods, and discuss remaining challenges related to optical network security.
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| 39. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
-
Guest Editorial Photonic Networks and Devices
- 2019
-
Ingår i: Journal of Lightwave Technology. - 0733-8724 .- 1558-2213. ; 37:16, s. 3872-3874
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 40. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
-
Introduction to the ONDM 2021 special issue
- 2022
-
Ingår i: Journal of Optical Communications and Networking. - 1943-0620 .- 1943-0639. ; 14:5, s. ONDM1-ONDM2
-
Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- This JOCN special issue contains extended versions of selected papers presented at the 25th International Conference on Optical Network Design and Modeling (ONDM 2021), which took place virtually from 28 June through 1 July 2021. The topics covered by the papers represent clear trends in current optical networking research, including capacity upgrade through transmission parameter optimization in multiband systems, spectral efficiency improvement through probabilistic constellation shaping in Flex Grid/multicore fiber networks, novel point-to-multipoint optical architectures based on digital subcarrier multiplexing that enable a rethink of multilayer network design, and trustworthy inter-operator sharing of passive optical network capacity based on a smart contract.
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| 41. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
-
Introduction to the Photonic Networks and Devices (NETWORKS) Special Issue
- 2020
-
Ingår i: Journal of Optical Communications and Networking. - 1943-0620 .- 1943-0639. ; 12:4, s. NET1-NET2
-
Tidskriftsartikel (refereegranskat)abstract
- This special issue comprises extended versions of some of the top-scored papers that were presented at the OSA Photonic Networks and Devices (NETWORKS) meeting that was part of the OSA Advanced Photonics Congress held in Burlingame, California, USA, July 29–August 1, 2019. Here, we highlight relevant topics from included papers relating to photonic communication network development.
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| 42. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
-
Machine Learning for Cognitive Optical Network Security Management
- 2020
-
Ingår i: Optics InfoBase Conference Papers. - 2162-2701.
-
Konferensbidrag (refereegranskat)abstract
- This talk surveys the security threats pertinent to the optical network and outlines the progress and challenges in developing machine learning approaches for cognitive management of optical network security.
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| 43. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
-
Machine learning for network security management, attacks, and intrusions detection
- 2022
-
Ingår i: Machine Learning for Future Fiber-Optic Communication Systems. ; , s. 317-336
-
Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- This chapter focuses on challenges, progress and pitfalls in applying ML to physical-layer security management. In the context of trustworthy networks, we motivate the need for automation in support of the work of network security professionals. We summarize the characteristics of known attack techniques targeting the physical layer and outline the framework for optical network security management. Supervised, semisupervised and unsupervised learning techniques that can aid automation of network security management are described with a focus on their performance requirements in the context of security. Accuracy, complexity, and interpretability of these techniques are examined on a use case of jamming and polarization scrambling attacks performed experimentally in a telecom operator network testbed. Finally, several open research challenges in the context of optical network security are outlined along with possible avenues to tackle some of them.
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| 44. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
-
Machine Learning for Optical Network Security Management
- 2020
-
Ingår i: Conference on Optical Fiber Communication, Technical Digest Series. - 9781943580712 ; Part F174-OFC 2020
-
Konferensbidrag (refereegranskat)abstract
- We discuss the role of supervised, unsupervised and semi-supervised learning techniques in identification of optical network security breaches. The applicability, performance and challenges related to practical deployment of these techniques are examined.
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| 45. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
-
Machine Learning for Optical Network Security Monitoring: A Practical Perspective
- 2020
-
Ingår i: Journal of Lightwave Technology. - 0733-8724 .- 1558-2213. ; 38:11, s. 2860-2871
-
Forskningsöversikt (refereegranskat)abstract
- 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 detection and 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 guidelines 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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| 46. |
- Furdek Prekratic, Marija, 1985, et al.
(författare)
-
Optical Network Security Management: Requirements, Architecture and Efficient Machine Learning Models for Detection of Evolving Threats [Invited]
- 2021
-
Ingår i: Journal of Optical Communications and Networking. - 1943-0620 .- 1943-0639. ; 13:2, s. A144-A155
-
Tidskriftsartikel (refereegranskat)abstract
- As the communication infrastructure that sustains critical societal services, optical networks need to function in a secure and agile way. Thus, cognitive and automated security management functionalities are needed, fueled by the proliferating machine learning (ML) techniques and compatible with common network control entities and procedures. Automated management of optical network security requires advancements both in terms of performance and efficiency of ML approaches for security diagnostics, as well as novel management architectures and functionalities. This paper tackles these challenges by proposing a novel functional block called Security Operation Center (SOC), describing its architecture, specifying key requirements on the supported functionalities and providing guidelines on its integration with optical layer controller. Moreover, to boost efficiency of ML-based security diagnostic techniques when processing high-dimensional optical performance monitoring data in the presence of previously unseen physical-layer attacks, we combine unsupervised and semi-supervised learning techniques with three different dimensionality reduction methods and analyze the resulting performance and trade-offs between ML accuracy and run time complexity.
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| 47. |
- Goscien, R., et al.
(författare)
-
Impact of high-power jamming attacks on SDM networks
- 2018
-
Ingår i: 22nd Conference on Optical Network Design and Modelling, ONDM 2018 - Proceedings. - : Institute of Electrical and Electronics Engineers (IEEE). - 9783903176072 ; , s. 77-81
-
Konferensbidrag (refereegranskat)abstract
- Space Division Multiplexing (SDM) is a promising solution to provide ultra-high capacity optical network infrastructure for rapidly increasing traffic demands. Such network infrastructure can be a target of deliberate attacks that aim at disrupting a large number of vital services. This paper assesses the effects of high-power jamming attacks in SDM optical networks utilizing Multi-Core Fibers (MCFs), where the disruptive effect of the inserted jamming signals may spread among multiple cores due to increased Inter-Core CrossTalk (ICo-XT). We first assess the jamming-induced reduction of the signal reach for different bit rates and modulation formats. The obtained reach limitations are then used to derive the maximal traffic disruption at the network level. Results indicate that connections provisioned satisfying the normal operating conditions are highly vulnerable to these attacks, potentially leading to huge data losses at the network level.
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| 48. |
- Grigoreva, Elena, et al.
(författare)
-
Energy Consumption and Reliability Performance of Survivable Passive Optical Converged Networks: Public ITS Case Study
- 2017
-
Ingår i: Journal of Optical Communications and Networking. - : Optical Society of America. - 1943-0620 .- 1943-0639. ; 9:4, s. C98-C107
-
Tidskriftsartikel (refereegranskat)abstract
- Access networks are evolving fast by increasing their capacity and coverage area, coping with a larger number of users and variety of terminals. Operators aim at keeping high network performance and quality of service but limiting their capital and operational expenditures by, e.g., minimizing investments and energy consumption using power saving at the network components. To address these challenges this paper evaluates the energy consumption, connection availability, and failure detection time of three protection schemes applicable for converged access networks: disjoint fiber protection, energy-efficient disjoint fiber protection, and reflective disjoint fiber protection. The schemes are assessed by a case study considering a public intelligent transport system (ITS). The studied ITS deploys a dedicated short-range communications radio access network connected to the service server through a protected passive access network. Comparison with unprotected architecture shows that reflective disjoint fiber protection offers low energy consumption and high connection availability, while it significantly reduces the failure detection time and, hence, the connection interruption time.
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| 49. |
- Izquierdo-Zaragoza, J. -L, et al.
(författare)
-
On the dimensioning of survivable optical metro/core networks with dual-homed access
- 2016
-
Ingår i: IEEE International Conference on High Performance Switching and Routing, HPSR. - : IEEE Computer Society.
-
Konferensbidrag (refereegranskat)abstract
- Long-reach passive optical networks (LR-PONs) are able to effectively support the growing demand of traffic originating from residential and business customers. Failures of metro/core (M/C) nodes serving the traffic to/from the access networks covered by LR-PONs, may potentially affect hundreds or thousands of customers. One way of guaranteeing 100% survivability from single-node failures is to apply dual-homing, where each LR-PON is connected to two M/C nodes, and combine it with node-disjoint dedicated-path protection (DPP). In this paper, we present a new approach to provide network survivability against single M/C node failures. Instead of applying dedicated path protection (DPP) strategy, which can require huge amount of extra resources, we combine an unprotected network design with a dynamic multilayer restoration algorithm. Our aim is to determine a suitable amount of resource overbuild (in terms of extra transponders) needed to provide average connection availability close to that guaranteed by DPP. Preliminary results show that dimensioning for the worst-case scenario among a set of predefined M/C node failures, i.e., the one disrupting the highest number of connections, yields to a cost-effective strategy requiring up to 35% less transponders than DPP, while offering the same average connection availability.
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| 50. |
- Licciardello, M., et al.
(författare)
-
Performance evaluation of abstraction models for orchestration of distributed data center networks
- 2017
-
Ingår i: 2017 19th International Conference on Transparent Optical Networks (ICTON). - : IEEE Computer Society. - 9781538608586
-
Konferensbidrag (refereegranskat)abstract
- Cloud computing is increasingly based on geographically distributed data centers interconnected by high performance networks. Application of Software Defined Networking (SDN) is studied as an emerging solution to support dynamic network resource management for distributed data centers (DCs) jointly with extensive use of Network Function Virtualization (NFV). SDN/NFV operation takes advantage of orchestration of network control functions according to distributed DCs communication needs. Orchestration relies on a set of logical information related to the underlying infrastructure, called abstraction, which offers different levels of visibility of available resources, depending on the abstraction strategy adopted.
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