Optical Network Infrastructure Research Articles

Cluster-based unsupervised method for eavesdropping detection and localization in WDM systems

Ensuring the secure and reliable operation of optical networks is crucial for various societal functions. However, optical network infrastructures are susceptible to unauthorized interception, posing a significant security risk at the physical layer. This necessitates the development of effective detection and localization methods of eavesdropping events. To address this challenge, we present a clustering-based method and a comprehensive eavesdropping diagnosis framework tailored for wavelength division multiplexing (WDM) systems. The framework is designed to handle diverse eavesdropping scenarios, including dynamic detection, classification, and localization of eavesdropping events. To mitigate the data dependency issue while detecting and localizing eavesdropping events, we propose a clustering algorithm utilizing basic optical performance monitoring (OPM) data, thus eliminating the need for sophisticated measurement equipment. A coarse localization requires only the OPM data from the receiver, while a finer localization requires the power monitoring data at all nodes as the input. The feasibility of the proposed scheme is validated using simulation-generated data, in which single and multiple eavesdropping can be detected and localized with a 100% label matching rate. Single-point eavesdropping detection and localization are experimentally validated with data collected from a fiber transmission system comprising three spans of 40 km each. Coarse localization with a 99.79% label matching rate and fine localization with 100% accuracy is achieved. As expected, experimental data shows a less concentrated distribution than the simulated data, which leads to inferior clustering results.

High performance efficiency of optical networking infrastructure characteristics with maximum speed of commercial fiber optic line cables employment

Abstract Fiber optic communications have made great strides, and it is now the foundation of our telecommunications and data networking infrastructures. Due to its beneficial characteristics, including low attenuation, a large bandwidth, and immunity to electromagnetic interference, optical fiber is frequently acknowledged as a superior transmission medium. Optical fibers have been widely used to create high speed lines that can transmit either a single wavelength channel or many wavelength channels using wavelength division multiplexing due to their special features (WDM). The maximum speed of commercial fiber-optic cables was only 2.5 Gb/s and can be extended to 1 Tb/s for short and medium distance. The study clarifies the possible transmission distance for different transmission media silica/plastic optical fibers with various optical fiber window transmissions versus environmental ambient temperature variations. The study demonstrated the bad effects of the temperature effects on the optical fiber transmission media (silica/plastic fibers) for various transmission windows.

Flexible and scalable ML-based diagnosis module for optical networks: a security use case [Invited

To support the pervasive digital evolution, optical network infrastructures must be able to quickly and effectively adapt to changes arising from traffic dynamicity or external factors such as faults and attacks. Network automation is crucial for enabling dynamic, scalable, resource-efficient, and trustworthy network operations. Novel telemetry solutions enable optical network management systems to obtain fine-grained monitoring data from devices and channels as the first step toward the near-real-time diagnosis of anomalies such as security threats and soft failures. However, the collection of large amounts of data creates a scalability challenge related to processing the data within the desired monitoring cycle regardless of the number of optical services being analyzed. This paper proposes a module that leverages the cloud native software deployment approach to achieve near-real-time machine learning (ML)-assisted diagnosis of optical channels. The results obtained over an emulated physical-layer security scenario demonstrate that the architecture successfully scales the necessary components according to the computational load and consistently achieves the desired monitoring cycle duration over a varying number of monitored optical channels.

The Real-Time System for Distribution of Clock, Control and Monitoring Commands With Fixed Latency of the LHCb Experiment at CERN

The Large Hadron Collider beauty (LHCb) experiment has gone through a major upgrade for LHC Run 3 at European Organization for Nuclear Research (CERN), scheduled to start in the middle of 2022. The entire readout system of the experiment has been replaced by front-end and back-end electronics that are able to record LHC events at the full LHC bunch crossing rate of 40 MHz. To maintain synchronicity across the full system, clock and control commands are originated from a single readout supervisor (SODIN) and distributed downstream through a passive optical network (PON) infrastructure, reaching all the back-end cards of the readout system, via a two-level hierarchy and using PON splitters. A field programmable gate arrays (FPGA) firmware core, called LHCb-PON and based on the CERN timing, trigger, and control (TTC)-PON, is instantiated on SODIN and all back-end cards and provides the communication protocol while ensuring a stable distribution of control commands within the readout period of 25 ns and a clock signal with fixed and deterministic latency with a precision of a few hundreds of picoseconds. This is achieved by the firmware backbone that provides clock recovery and ensures the transmission of a control word downstream with fixed latency. In addition, the LHCb-PON also provides monitoring functionalities over the upstream link, with less strict timing requirements, connecting multiple back-end cards to the central SODIN. This is achieved by having each back-end card send data upstream through a time-division multiplexing (TDM) scheme. This article describes the implementation, measurements, and results from the usage of the system during the startup of the LHC Run 3.

Machine Learning-Enabled Intelligent Fiber-Optic Communications: Major Obstacles and the Way Forward

Machine learning (ML) has achieved phenomenal success in revolutionizing a number of science and engineering disciplines over the last decade. Naturally, it is also being reckoned as a powerful technology to transform future fiber-optic communication systems. Over the past few years, we have seen extensive research efforts by both academia and industry to assimilate and gain from ML paradigm in several aspects of optical communications and networking. However, despite years of rigorous research, ML has not yet gained broad acceptance in commercial fiber-optic networks. In this article, we identify major common factors which are currently hindering widespread adoption of ML in practical optical networks. As ML-based methods are inherently data driven, we particularly highlight critical data-related issues as well as intrinsic limitations of the ML algorithms. Taking two important use-cases, i.e., quality-of-transmission estimation, and proactive fault detection and management as examples, we elucidate how these limiting factors shrink the deployment prospects of ML-based solutions. We also briefly discuss main challenges faced by ML-assisted methods in seven other key areas of fiber-optic communications. Finally, we suggest some useful strategies that can help alleviate existing obstacles, thus paving the way for vast deployment of ML -powered tools in real optical network infrastructures.

Fiber to The Home (FTTH) Network Design Using Gigabit Passive Optical Network (GPON) Technology Using Link Power Budget and Rise Time Budget Analysis in Cibeber Village Tasikmalaya

Fiber optic is a transmission medium that can transmit information with large capacity. One of the developments in local fiber access networks is FTTH (Fiber to The Home). The construction of the FTTH network uses Gigabit Passive Optical Network (GPON) technology so that it can provide broadband services to customers with a wider range. This research was studied by designing FTTH based on GPON technology in Cibeber Village, Manonjaya District. The existing condition of the FTTH network in Cibeber Village is that there are 2 Optical Distribution Points (ODP) for 20 customers with each ODP having 10 subscribers. From the results of the location survey by measuring the distance to each customer, the furthest distance to the customer for the two ODPs was obtained, so that 2 new ODPs were needed for the design. From the design of the new optical network infrastructure, it has been analyzed using the link power budget and rise time budget method based on the customer with the farthest distance before the addition of ODP has a Power Receive sensitivity of -16.631 dBm to -15.631 dBm on the uplink and -16.644 dBm to -15.574 dBm on the downlink, these results are in accordance with the expected standard, which ranges from -8 dBm to -27 dBm. In calculating the value of the rise time budget for customers after the addition of ODP, it has a value of 0.2044 ns to 0.2039 ns on the uplink and 0.2188 ns to 0.21574 ns on the downlink. This value is still below the standard time limit set by PT. Telkom Indonesia 0.56 ns for uplink and 0.292 ns for downlink. So based on this the results of the design are feasible to implement.

Securing Optical Networks Using Quantum-Secured Blockchain: An Overview.

The deployment of optical network infrastructure and development of new network services are growing rapidly for beyond 5/6G networks. However, optical networks are vulnerable to several types of security threats, such as single-point failure, wormhole attacks, and Sybil attacks. Since the uptake of e-commerce and e-services has seen an unprecedented surge in recent years, especially during the COVID-19 pandemic, the security of these transactions is essential. Blockchain is one of the most promising solutions because of its decentralized and distributed ledger technology, and has been employed to protect these transactions against such attacks. However, the security of blockchain relies on the computational complexity of certain mathematical functions, and because of the evolution of quantum computers, its security may be breached in real-time in the near future. Therefore, researchers are focusing on combining quantum key distribution (QKD) with blockchain to enhance blockchain network security. This new technology is known as quantum-secured blockchain. This article describes different attacks in optical networks and provides a solution to protect networks against security attacks by employing quantum-secured blockchain in optical networks. It provides a brief overview of blockchain technology with its security loopholes, and focuses on QKD, which makes blockchain technology more robust against quantum attacks. Next, the article provides a broad view of quantum-secured blockchain technology. It presents the network architecture for the future research and development of secure and trusted optical networks using quantum-secured blockchain. The article also highlights some research challenges and opportunities.

Agent-based distributed protocol for resource discovery and allocation of virtual networks over elastic optical networks

Network virtualization is a key enabling technology for “Infrastructure as a Service” provisioning, increasing the flexibility and cost savings offered to customers. By extending the concept of server virtualization to the network infrastructure, the allocation of different, independent virtual networks over a single physical network is carried out on demand. A fundamental challenge in network virtualization systems is to choose which physical nodes and links to use for hosting virtual networks in the physical infrastructure, known as the “virtual network allocation” problem. All virtual network allocation proposals on elastic optical networks assume a centralized operation, deploying a single node with access to the network state global information and assigning resources accordingly. However, such configuration might exhibit the inherent problems of centralized systems: survivability and scalability. In this paper, we present a distributed protocol for resource discovery, mapping, and allocation of network virtualization systems. The distributed protocol is generic enough as to be used with different substrate networks. However, in this paper, it has been adapted to work over an elastic optical network infrastructure, where further considerations regarding the spectrum continuity and contiguity constraints must also be taken into account. The distributed protocol is based on the concept of alliances: upon the arrival of a virtual network request, agents located in the physical network nodes compete to form the first alliance able to host the virtual network. Because the first alliances to be formed are also the ones composed by nearby nodes, a good network resource usage is achieved. The feasibility of the distributed protocol was studied by evaluating its ability to successfully establish virtual networks within acceptable time and with low bandwidth consumption from the coordination messages.

A Sustainable Business Model for a Neutral Host Supporting 5G and beyond (5GB) Ultra-Dense Networks: Challenges, Directions, and Architecture.

With the deployment of the fifth generation (5G) mobile network systems and the envisioned heterogeneous ultra-dense networks (UDNs), both small cell (SmC) and distributed antenna system (DAS) technologies are required by mobile network operators (MNOs) and venue owners to support multiple spectrum bands, multiple radio access technologies (RATs), multiple optical central offices (COs), and multiple MNOs. As a result, the neutral host business model representing a third party responsible for managing the network enterprise on behalf of multiple MNOs has emerged as a potential solution, mainly influenced by the desire to provide a high user experience without significantly increasing the total cost of ownership (TCO). However, designing a sustainable business model for a neutral host is a nontrivial task, especially when considered in the context of 5G and beyond (5GB) UDNs. In this paper, under an integrated optical wireless network infrastructure, we review how SmC and DAS technologies are evolving towards the adoption of the neutral host business model and identify key challenges and requirements for 5GB support. Thus, we explore recent candidate advancements in heterogeneous network integration technologies for the realization of an efficient 5GB neutral host business model design capable of accommodating both SmC and DAS. Furthermore, we propose a novel design architecture that relies on virtual radio access network (vRAN) to enable real-time dynamic resource allocation and radio over Ethernet (RoE) for flexible and reconfigurable fronthaul. The results from our simulations using MATLAB over two real-life deployment scenarios validate the feasibility of utilizing switched RoE considering end-to-end delay requirements of 5GB under different switching schemes, as long as the queuing delay is kept to a minimum. Finally, the results show that incorporating RoE and vRAN technologies into the neutral host design results in substantial TCO reduction by about 81% in an indoor scenario and 73% in an outdoor scenario.

Broadband optical network design for the future aircraft cabin

Bringing an optical network infrastructure into civil aircraft cabins is one of the major technological evolutions of the aeronautic industry. During the last decade, copper networks installed in aircraft cabins have proven to be unable to support new technologies and services throughout the life of the aircraft. With severe constraints and high maintenance costs in the aeronautical field, there is also a significant increase in aircraft weight and hence fuel consumption with the current cabin infrastructure. In order to overcome these problems while offering the best trade-off in terms of heterogeneous service transport, we propose therein various optical network architectures for future civil aircraft cabins combining point to multi-point time division multiplexing transport over passive optical networks with wavelength division multiplexing technology. These architectures offer promising solutions for commercial aircraft with capacities up to about 500 seats, while allowing for a significant decrease in operating costs and maintenance/installation time, thus facilitating the intervention on the aircraft.

Performance Measurements Within Asynchronous Task-Based Runtime Systems: A Double White Dwarf Merger as an Application

Analyzing performance within asynchronous many-task-based runtime systems is challenging because millions of tasks are launched concurrently. Especially for long-term runs the amount of data collected becomes overwhelming. We study HPX and its performance-counter framework and APEX to collect performance data and energy consumption. We added HPX application-specific performance counters to the Octo-Tiger full 3D AMR astrophysics application. This enables the combined visualization of physical and performance data to highlight bottlenecks with respect to different solvers. We examine the overhead introduced by these measurements, which is around 1%, with respect to the overall application runtime. We perform a convergence study for four different levels of refinement and analyze the application's performance with respect to adaptive grid refinement. The measurements' overheads are small, enabling the combined use of performance data and physical properties with the goal of improving the code's performance. All of these measurements were obtained on NERSC's Cori, Louisiana Optical Network Infrastructure's QueenBee2, and Indiana University's Big Red 3.

Experimental Assessment of Automatic Optical Metro Edge Computing Network for Beyond 5G Applications and Network Service Composition

The upcoming 5G and beyond 5G heterogeneous applications with different quality of service (QoS) will impose strict latency, bandwidth, and flexibility requirements on optical metro access networks. Conventional cloud computing is gradually unable to fulfill the application requirements, especially on latency due to the distance causing propagation and networking delay. Therefore, the edge computing that distributed in metro access networks is promising to serve the applications with the requirements of ultra-low latency. As the resources of edge computing nodes are restricted and light compared with cloud data centers (DC), it is significant to manage across multiple edge computing nodes to enable joint allocation of the distributed resources. To address this issue, the optical metro network infrastructure should be flexible on the data plane and able to interact with the control and orchestration plane to automatically adapt to the communication requirements of multiple edge computing nodes. Related works have been focused on the simulation and numerical study. In this paper, an experimental testbed of a flexible optical metro access network including hardware and software components is built, and the performance is validated with real server traffic. The presented network system is based on the field-programmable gate array (FPGA), and hardware adapted open source network management and telemetry tools. Different from the commercial electrical switches, FPGA is fully programmable making it able to flexibly forward and monitor the traffic, in the meantime, to dynamically control the optical devices according to the feedback from the control plane. By exploiting dynamic software defined networking (SDN) control and network service orchestration, the proposed network is able to establish capacity adapted network slices for edge computing connections. Successful telemetry-assisted dynamic network service chain (NSC) generation, automatic bandwidth resources assignment, and QoS protection are demonstrated.

Open whitebox architecture for smart integration of optical networking and data center technology [Invited

In this paper, we identify challenges in developing future optical network infrastructure for new services based on technologies such as 5G, virtual reality, and artificial intelligence, and we suggest approaches to handling these challenges that include a business model, architecture, and diversity. Through activities in multiservice agreement and de facto standard organizations, we have shown how the hardware abstraction layer interfaces of optical transceivers are implemented for multivendor and heterogeneous environments, coherent digital signal processor interoperability, and optical transport whiteboxes. We have driven the effort to define the transponder abstraction interface with partners. The feasibility of such implementation was verified through demonstrations and trials. In addition, we are constructing an open-transport platform by combining existing open-source software and implementing software components that automate and enhance operations. An open architecture maintains a healthy ecosystem for industry and allows for a flexible, operator-driven network.

Predicting the actual location of faults in underground optical networks using linear regression

AbstractOptical cables are enormous transmission media that carry high‐speed data across transatlantic, intercontinental, international boundaries, and cities. The optical cable is essential in data communication. The cable has become an indispensable component in optical communications infrastructure; hence, conscious efforts are always adopted to prevent or minimize faults in the optical network infrastructure. Typically, tracing fault in the underground optical network has been difficult even though the optical time‐domain reflectometer (OTDR) has been used to measure the distance of faults in the underground fiber cable. The methodologies deployed in the reviewed literature indicate a vast gap between the fault distance measured by the OTDR and the actual distance of fault. This paper observed the difficulties involved in tracing the actual spot of fault in the underground optical networks. The difficulty of tracing these underground faults mostly result in an undue delay and loss of revenue. This research presents a machine learning approach to predict the actual location of a fiber cable fault in an underground optical transmission link. Linear regression in the python sci‐kit learn library was used to predict the actual location of a fault in an underground optical network. The mean square error and MAE evaluation matrix used provided good accuracy results of 0.061291 and 0.080143, respectively. The result obtained in this paper indicates that faults in underground optical networks can be found quickly to avoid the delays in the fault tracing process, which leads to an excessive revenue loss.

Comparison of domain adaptation and active learning techniques for quality of transmission estimation with small-sized training datasets [Invited

Machine learning (ML) is currently being investigated as an emerging technique to automate quality of transmission (QoT) estimation during lightpath deployment procedures in optical networks. Even though the potential network-resource savings enabled by ML-based QoT estimation has been confirmed in several studies, some practical limitations hinder its adoption in operational network deployments. Among these, the lack of a comprehensive training dataset is recognized as a main limiting factor, especially in the early network deployment phase. In this study, we compare the performance of two ML methodologies explicitly designed to augment small-sized training datasets, namely, active learning (AL) and domain adaptation (DA), for the estimation of the signal-to-noise ratio (SNR) of an unestablished lightpath. This comparison also allows us to provide some guidelines for the adoption of these two techniques at different life stages of a newly deployed optical network infrastructure. Results show that both AL and DA permit us, starting from limited datasets, to reach a QoT estimation capability similar to that achieved by standard supervised learning approaches working on much larger datasets. More specifically, we observe that a few dozen additional samples acquired from selected probe lightpaths already provide significant performance improvement for AL, whereas a few hundred samples gathered from an external network topology are needed in the case of DA.

Adopting Intelligent Modelling to Trace Fault in Underground Optical Network: A Comprehensive Survey

Aiming at building new global optical network infrastructure optimized with fault tracing capabilities, light transmission monitoring, packets re-routing and reconfigurations require an intelligent optical transmission system. An intelligent approach to solve the increasingly complex problems, to enhance fault tracing in the underground optical network infrastructure need to be adopted. For over forty decades now, Optical Time Domain Reflectometry (OTDR) technology has been used to determine faults distance in Fiber Optic Cable (FOC). When it comes to underground optical networking, using OTDR measurements to trace fault on the earth surface takes much longer time since the device only measures the length of underground FOC from the optical transmitter to the point of the fault. Finding the exact spot of fault on earth is a complicated task due to several factors identified in this study. A comprehensive review of previous papers on how OTDR device and other scientific techniques have been used to trace faults in underground FOC were presented in this study. Due to the identified drawbacks in the OTDR to precisely trace fault in underground FOC networks, an intelligent fault tracing technique has been proposed to aid the process. The objective of this paper sought to conduct a comprehensive systematic review of previous studies on fault-finding techniques in underground FOC. To give a clear view of the available technologies used to conduct fault finding activities in underground FOC. The available intelligent systems and the possible future directions of tracing faults in FOC promptly and in a more economical manner.

Analog fiber-wireless downlink transmission of IFoF/mmWave over in-field deployed legacy PON infrastructure for 5G fronthauling

We present a fixed mobile convergence topology for analog intermediate frequency over fiber (A-IFoF)/millimeter-wave (mmWave) transmission, benefiting from the reuse of the deployed passive optical network (PON) infrastructure, towards future mobile fronthaul architectures. Powerful fully programmable gate array boards located inside the access nodes convert the Ethernet-based traffic to orthogonal frequency-division multiplexing (OFDM)-modulated intermediate frequency (IF) waveforms, supporting the A-IFoF propagation through the optical legacy infrastructure. Coexistence of the 5G traffic with the residential legacy traffic for the field propagation is achieved through utilization of unused C-band channels and wavelength-division multiplexing. To this extent, we experimentally demonstrate the downlink operation of a converged A-IFoF/mmWave link, over Telecom Italia’s legacy infrastructure located at Turin. Four-quadrature amplitude modulation (QAM)-OFDM and 16QAM-OFDM IF signals with ∼ 200 M H z and 400 MHz bandwidth [considered within the 3rd Generation Partnership Project (3GPP) New Radio specifications] were generated through a radio frequency system-on-chip platform and optically multiplexed with the legacy fiber-to-the-home services. After propagation to the field, the A-IFoF stream was directly fed to a directional wireless link operating at 60 GHz. Successful PON/over-the-air transmission with error vector magnitude (EVM) values well below the 3GPP ( < 12.5 % ) requirements for 5G New Radio was demonstrated, with a 10.5% EVM for 16QAM-OFDM modulated with 400 MHz bandwidth.

Differential Phase-Shift QKD in a 2:16-Split Lit PON with 19 Carrier-Grade Channels

We investigate the practical network integration of differential phase shift quantum key distribution following a cost-optimized deployment scheme where complexity is off-loaded to a centralized location. User terminal equipment for quantum state preparation at 1 GHz symbol rate is kept technologically lean through use of a directly-modulated laser as optical encoder. Integration in a passive optical network infrastructure is experimentally studied for legacy and modern optical access standards. We analyze the implications that result from Raman scattering arising from different spectral allocations of the classical channels in the O-, S-, C- and L-band, and prove that the quantum channel can co-exist with up to 19 classical channels of a fully-loaded modern access standard. Secure-key generation at a rate of 5.1 times 10e-7 bits per pulse at a quantum bit error ratio of 3.28 percent is obtained over a 13.5 km reach, 2 to 16 split passive network configuration. The high power difference of 93.8 dB between launched classical and quantum signals in the lit access network leads to a low penalty of 0.52 percent in terms of error ratio.

Content placement in 5G‐enabled edge/core data center networks resilient to link cut attacks

AbstractHigh throughput, resilience, and low latency requirements drive the development of 5G‐enabled content delivery networks (CDNs) which combine core data centers (cDCs) with edge data centers (eDCs) that cache the most popular content closer to the end users for traffic load and latency reduction. Deployed over the existing optical network infrastructure, CDNs are vulnerable to link cut attacks aimed at disrupting the overlay services. Planning a CDN to balance the stringent service requirements and increase resilience to attacks in a cost‐efficient way entails solving the content placement problem (CPP) across the cDCs and eDCs. This article proposes a framework for finding Pareto‐optimal solutions with minimal user‐to‐content distance and maximal robustness to targeted link cuts, under a defined budget. We formulate two optimization problems as integer linear programming (ILP) models. The first, denoted as K‐best CPP with minimal distance (K‐CPP‐minD), identifies the eDC/cDC placement solutions with minimal user‐to‐content distance. The second performs critical link set detection to evaluate the resilience of the K‐CPP‐minD solutions to targeted fiber cuts. Extensive simulations verify that the eDC/cDC selection obtained by our models improves network resilience to link cut attacks without adversely affecting the user‐to‐content distances or the core network traffic mitigation benefits.

DSP-Based Flexible-Waveform and Multi-Application 5G Fiber-Wireless System

This article reports the implementation and experimental performance investigation of a DSP-based flexible-waveform fiber-wireless (FiWi) system for 5G enhanced mobile broadband (eMBB) and new vertical applications. Our radio over fiber-based fronthaul solution uses a wavelength-division-multiplexing passive optical network (WDM-PON) infrastructure, from a commercial Internet service provider, to enable 5G operation over multiple frequency bands, including: a DSP and flexible waveform-based signal at 788 MHz, which can be set as generalized frequency division multiplexing (GFDM) or filtered orthogonal frequency division multiplexing (F-OFDM); 5G new radio (NR) signals at 3.5 or 26 GHz in accordance to 3GPP Release 15; an additional vector 26 GHz signal with bandwidth of up to 800 MHz. The DSP-based functionality provides digital pre-distortion (DPD), besides the real-time waveform generation. Experimental results demonstrate 4.41 Gbit/s total throughput in the air in accordance to the 3GPP requirements, as well as an innovative low-latency M2M application based on PROFINET standard.