Future 6G X-haul networks must satisfy strict latency and service reliability requirements, placing significant pressure on metro-access transport architectures. As deployments become denser, longer and more heterogeneous routes intensify physical-layer impairments, making feasibility assurance and Quality-of-Transport (QoT) evaluation increasingly complex. To address these challenges, this work proposes an AI-driven converged metro-access Optical Network-as-a-Service (ONaaS) architecture based on coherent Point-to-Multipoint (P2MP) transmission using Digital Subcarrier Multiplexing (DSCM). An experimentally characterized transceiver impairment model is embedded into a network-level simulator to perform end-to-end feasibility analysis under strict latency and BER constraints. The results show that connectivity is primarily bounded by accumulated impairments, while Distributed Unit (DU) densification improves performance mainly by shortening path lengths, with limited benefit beyond moderate routing depth. To enable scalable operation, a lightweight machine-learning-based BER estimator is developed for rapid QoT prediction. Trained on a minimal deployment scenario, the Random Forest model generalizes across DU densities and topologies with R 2 > 0 . 98 , reducing evaluation time by several orders of magnitude. A techno-economic assessment further indicates up to 75% reduction in DU-site transceivers and 27%–30% energy savings compared to Point-to-Point (P2P) provisioning, demonstrating the efficiency and scalability of AI-enabled P2MP metro-access convergence for 6G.

This article investigates robust design methodologies for cost-effective and resilient design of filterless Point-to-Multipoint (P2MP) optical networks by minimizing the number of amplifiers, which are often compromised by parameter uncertainties, for example inaccurate fiber loss. To overcome the inefficiencies of traditional, overly or insufficiently conservative margin-based designs, this study investigates Deterministic Optimization (DO), Robust Optimization (RO), and Adjustable Robust Optimization (ARO) of optical filterless horseshoe networks. All these techniques are explained in detail using a simple Linear Program (LP) model example. The findings of this manuscript demonstrate that ARO is a significantly superior technique, leveraging a two-stage, “wait-and-see” approach that allows for adaptive adjustments, by modifying amplifier gains after uncertainty is revealed. This adaptability reduces the conservatism of standard RO, achieving full resiliency with a much lower “price of robustness”. Specifically, for the considered scenarios, at a 20% uncertainty level, ARO required only a 16% increase in amplifiers compared to 40% for RO, ultimately providing a more efficient trade-off between performance and robustness.

Recent progress in hollow-core fiber (HCF) technology is raising the prospects for the deployment of this type of fiber in future infrastructure upgrades. Although earlier deployments of HCF will take advantage of its low latency property to realize point-to-point links (e.g., in the metro and aggregation network segments), HCF generations with better specifications (improving performance and deployment robustness) may become suitable for more demanding regional and long-haul network applications. In these scenarios, they may co-exist with traditional fiber types in order to ensure, at the network-level, an appropriate balance between latency reduction and the increase of capital expenses associated to both the higher cost of HCF spans and the potential reductions in reach. Therefore, fiber infrastructure owners will face a new design problem, which consists of optimizing the spans where HCF is to be used to minimize service latency while meeting optical performance degradation and cost increase bounds. This paper describes an optimal method to solve this problem, by leveraging the approximation of incoherent accumulation of noise to derive an integer linear programming (ILP) model, and two variants of a heuristic algorithm. A set of detailed simulations over a reference optical transport network highlight the optimality and scalability of the proposed method.

We present Rûm, a randomized asynchronous multivalued byzantine consensus algorithm designed for mobile ad-hoc networks, operating under the message omission/loss model of Santoro-Widmayer. Rûm is optimal with respect to the byzantine fault bound, and makes progress in rounds where the number of message omissions is bounded, while always ensuring safety. Through network simulations conducted in ns-3, Rûm’s performance is evaluated against Turquois and Ezhilchelvan et al.’s multivalued consensus algorithm, demonstrating its ability to achieve consensus in the presence of byzantine faults and message loss. The results indicate that Rûm can efficiently handle message omissions and byzantine faults, maintaining reliable decision-making processes, making it a suitable solution for consensus in mobile ad-hoc networks.

While horseshoe filterless networks with point-to-multipoint (P2MP) transceivers offer a cost-effective solution with inherent survivability against single-link failures, certain scenarios may demand an even higher degree of network resilience. This is particularly true in regions with frequent power outages and/or where load shedding is enforced. Addressing this problem requires a careful design and trade-off between survivability and cost. This paper describes a multi-objective optimization framework based on Integer Linear Programming (ILP) that accurately models the problem and can be used to obtain solutions that prioritize one or the other metric. Moreover, the paper reports a study using a set of randomly generated horseshoe topologies that demonstrates how strategically placing amplifiers and unbalanced couplers can significantly enhance network resilience, while also keeping the minimum number of additional optical amplifiers required.

Horseshoe filterless networks with point-to-multipoint (P2MP) transceivers are cost-effective but may lack resilience in regions with power outages. This paper addresses this gap by strategically placing amplifiers and couplers to enhance network resiliency. We evaluate the effectiveness of this approach through a network availability analysis.

The utilization of hybrid Erbium-doped fiber (EDF)/Raman amplifiers enables to extend the reach of optical channels and, consequently, reduce the number of expensive 3R regenerators required in long-haul optical networks. However, hybrid amplifiers are costlier than the widely deployed EDF amplifiers (EDFAs). Therefore, it is critical to place them only at selected fiber spans of the network such that their number is also kept to a minimum. Hybrid amplifier placement is a complex task in mesh networks due to the diverse optical channels (i.e., with different source and destination nodes) traversing each fiber span. This paper proposes an optimal method to solve the problem of placing hybrid amplifiers in mesh networks. It builds on the approximation that noise adds up incoherently along the transmission path to derive an integer linear programming (ILP) model that determines the minimum number and location of hybrid EDF/Raman amplifiers required to reach a target set of feasible optical channels (i.e., without intermediate 3R regenerators). A comprehensive set of network simulations using a reference optical network provides evidence that the proposed method outperforms existing approaches.

This paper proposes an Integer Linear Programming (ILP) framework to optimize the multi-period planning of metro-aggregation networks exploiting both point-to-multipoint coherent pluggable transceivers and a filterless line system architecture. We investigate several planning strategies to minimize cost while also considering traffic prediction and operational expenditures. The results of a reference network provide evidence of transceiver cost reductions between 20% and 32% compared to the point-to-point approach over a five-year planning period.

Emerging applications are driving traffic requirements to new heights, from IoT and autonomous driving to augmented reality and Industry 4.0. Urban areas, which have a significant fraction of the telecom infrastructure capital expenditures (CAPEX), are experiencing even more growth than other segments. Noteworthy, the traffic pattern in aggregation networks is hub-and-leaf, with only a few hub nodes communicating with multiple leaf nodes. Traditional point-to-point optical solutions are not the best fit for this pattern. A novel optical technology enabling point-to-multipoint operation has recently been proposed to address this limitation. Since this solution relies on broadcasting the optical signal over a virtual tree, its optimal deployment in generic fiber topologies (with failure survivability conditions) requires specific designs. This paper describes an integer linear programming model to optimize the design of survivable metro-aggregation networks exploiting point-to-multipoint coherent transceivers. Results obtained on a mesh network show evidence that transceiver expenditures can be reduced by a figure between 25% and 60%.

The ever-increasing traffic requirements need cost-efficient and reliable solutions. Metropolitan networks are responsible for a large fraction of the telecom infrastructure CAPEX. Albeit the traffic pattern in these networks tends to be hub-and-spoke, the current transceiver deployments do not leverage this feature. This paper describes and models various survivable metro-aggregation network scenarios using point-to-multipoint capable coherent transceivers. The results obtained over a reference mesh network show that these transceivers can reduce total transceiver costs by ~40% on average.

The massive deployment of 5G and beyond will require high capacity and low latency connectivity services, so network operators will have either to overprovision capacity in their transport networks or to upgrade the optical network controllers to make decisions nearly in real time; both solutions entail high capital and operational expenditures. A different approach could be to move the decision making toward the nodes and subsystems, so they can adapt dynamically the capacity to the actual needs and thus reduce operational costs in terms of energy consumption. To achieve this, several technological challenges need to be addressed. In this paper, we focus on the autonomous operation of Digital Subcarrier Multiplexing (DSCM) systems, which enable the transmission of multiple and independent subcarriers (SC). Herein, we present several solutions enabling the autonomous DSCM operation, including: i) SC quality of transmission estimation; ii) autonomous SC operation at the transmitter side and blind SC configuration recognition at the receiver side; and iii) intent-based capacity management implemented through Reinforcement Learning. We provide useful guidelines for the application of autonomous SC management supported by the extensive results presented.

Both spatial-division multiplexing (SDM) and band-division multiplexing (BDM) emerge as possible solutions to increase the optical network capacity to support the traffic demand which has been rising over time. In this work, two different ROADM (Re-configurable Optical Add Drop Multiplexer) switching techniques, namely SDM-InS (Independent switching) and SDM-CCC (Core Continue Constant) are investigated and the resulting network capacity is compared with the BDM approach. In the BDM case, both L- and S-bands have been used in addition to C-band to increase the network capacity. The launch power is optimized to control the QoT (Quality of Transmission) summarized by the generalized SNR (GSNR) per channel. Due to: stimulated Raman scattering, frequency variation of loss, frequency variation of dispersion coefficient and noise figures, an optimum power tilt and offset are calculated for each band. We show that the total network capacity increased by $\sim 2 \times$ and $\sim 3 \times$, when using the L-band and L+S-bands in addition to the C-band, respectively, in both a reference German and a reference US network. Additionally, it was also shown that using additional bands, the increase in network capacity is close to the result of using additional optical fibers in the SDM case.

Recent trends in optical transport networks emphasize the need of adopting a self-driving network in order to operate autonomously and adaptively to the actual network environment. In this context, advances in real-time telemetry platforms allowing to continuously monitor the current performance of an optical channel can avoid the traditional provisioning with end-of-life (EoL) margins, which is characterized by imposing margins large enough to account for worst-case performance degradation profiles (e.g. due to ageing) during network operation. Reducing these margins when provisioning an optical channel, can enable to operate it at higher capacity (e.g. using a higher order modulation format), thereby decreasing capital expenditures (CapEx). However, effectively adopting a more aggressive provisioning strategy requires a sophisticated multi-layer framework to address the higher likelihood that traffic demands might have a longer time to live than that of the optical channel carrying them. This paper exploits the joint availability of real-time performance monitoring platforms and OTN switching technology in order to develop a complete framework to provision services with reduced margins while proactively minimizing the utilization of optical channels that are approaching the performance limit, preventing traffic disruption. The simulation results highlight the benefits of adopting the proposed framework regarding the overall network performance and line interface count.

Typical optical transport networks dimensioning is performed disregarding the client to line ports interconnection restrictions imposed by the node architecture deployed. After the grooming and routing optimization, equipment is mapped in order to implement the obtained solution. However, as some node architectures can impose restrictions in the client to line ports interconnection, some grooming configurations may be unfeasible to map. This is particularly relevant in multi-period scenarios where traffic changes between periods and capacity is already installed at specific modules. In this work, we present an integer linear programming (ILP)-based framework that minimizes the additional number of line interfaces required to overcome unfeasible mappings. The node architectures considered are non-blocking electrical cross connect (EXC), partial non- blocking EXCs, EXCs with extendable backplanes, and EXCs with interconnection via high bit rate client ports. Using the proposed framework we evaluate the impact of node architecture flexibility in the number of line interfaces required.

In order for transport networks to cost-effectively provide higher capacity, it is expected that channel bit-rates beyond 100 Gb/s will be accomplished by resorting to a flexible WDM grid with variable channel spacing. Among the implications of this concept is the need for planning tools that fully exploit the additional degrees of freedom enabled by a flexible grid to further optimize network cost and spectral efficiency. This paper proposes an optimization framework to minimize the transponder and regenerator deployment cost in a translucent WDM network featuring channel bit-rates of 40, 100 and 400 Gb/s and multiple transmission formats per bit-rate, each characterized by its own spectral width, optical reach and cost properties. Firstly, we formulate the problem via a novel Integer Linear Programming (ILP) model, whose resolution finds the optimal (cheapest) feasible network configuration. Secondly, we propose an efficient heuristic called Narrowest First-Iterative Cost Reduction (NF-ICR) to handle network scenarios for which solving the ILP entails an unreasonable computational burden. The NF-ICR heuristic is shown to provide tight optimality bounds where the benchmark given by the ILP solution is attainable. For larger networks, we show that the use of a flexible grid and multiple format options for each bit-rate results in around 10% less cost in transponders and regenerators for metro networks, and a substantial increase in the total traffic load supported by the network. We also conclude that a distinction emerges between metro/regional scenarios and long-haul networks with long paths, wherein the shorter transparent reach of 400 Gb/s channels drives up the cost due to extra regeneration, favoring the use of parallelized solutions of lower bit-rate channels.

A potentially cost-effective approach for augmenting the transmission capacity in an optical transport network (OTN) consists of bundling several optical channels by means of an inverse-multiplexing strategy, e.g. virtual concatenation (VCAT). When VCAT is employed together with multipath routing, the differential delay between concatenated channels needs to be compensated via electrical buffering. To avoid installing large and costly high-speed buffers, this compensation can be dispersed throughout the intermediate path nodes. With this distributed scheme, each intermediate compensation operation requires an optical-electrical-optical (OEO) converter. Such converters, which are typically employed to allow electrical processing (e.g. signal regeneration, traffic switching/grooming, etc.), represent the largest contributor to the capital expenditures of an optical network. Hence, to save on OEO equipment and keep the network cost-effectiveness, we propose the novel approach of collocating the differential delay buffering and the regeneration on the same network element, enabling the implementation of distributed schemes with minimal link capacity levels, OEO count, and buffer size requirements. To effectively design an OTN network under these conditions, we also present a new multi-step optimization framework based on integer linear programming (ILP) modeling. To test our approach, emerging 100 Gb/s Ethernet services are established over two reference networks using virtually-concatenated 40 Gb/s channels. The correspondent results confirm that relevant OEO/regenerator count savings (ranging from 23% to 44%) can be attained with the collocated approach while the buffer sizes are maintained reasonably small. We also show that the end-to-end transmission latency is not affected by the adoption of this collocated strategy

In order to support bit-rates beyond 100 Gb/s in transport networks, flexible-grid networking was proposed as a solution to exploit the spectral efficiency of advanced modulation formats without severely impairing the transmission reach. This increase in the bit-rate highlights the critical role of survivable connectivity. Considering this, we propose a planning solution for flexible-grid translucent networks with shared restoration through an ILP model and a fast, scalable heuristic. Furthermore, we propose an algorithm to calculate the backup transponder redundancy in each node when tunable transponders are in place to restore multiple optical channels. The results show considerable spectral savings from using a shared restoration scheme instead of a dedicated one and that 18% to 30% of the backup transponders can be saved through tunable optics, depending on the tuning range used.

The increasing traffic demand resulting from the widespread use of information and communication technologies is impelling network operators to upgrade the capacity of their existing transport network facilities. Recent advances in the scientific community have led to the first developments in serial 100 Gb/s technology that could provide an adequate solution for solving the capacity expansion problem. Nevertheless, given the complexity of 100 Gb/s transceiver equipment, the initial costs may refrain early adoption of the technology, leading carriers to invest in more cost-effective alternatives. Embedded in the optical transport network (OTN) functionality portfolio, traffic grooming and virtual concatenation can be exploited in order to optimally combine 40 Gb/s and 100 Gb/s equipment for supporting mixed line rate (MLR) demands. Hence, this work proposes an optimization framework for designing optical transport infrastructures with the objective of minimizing the network costs directly related to transceiver and regenerator equipment. The framework models the problem via an integer linear programming formulation that takes into account the relative cost, the maximum optical reach, and the capacity of each optical interface, as well as the optical channel limit per fiber link. As a result, the proposed method is able to select the equipment type and the routing path for each connection which correspond to the most cost-effective solution satisfying the 100G and 40G service demands.

This work proposes a distributed framework for routing path optimization in Optical Burst-Switched (OBS) networks loosely mimicking the foraging behavior of ants, which in the past has originated the Ant Colony Optimization (ACO) metaheuristic. The distributed framework consists of additional data structures stored at the nodes and special control packets used to estimate the goodness of the routing paths and update the routing tables of the nodes. The performance of the ACO-based framework is evaluated, through network simulation, using two reference network topologies and compared with that obtained with shortest path routing and centralized routing path optimization. The simulation results show that the distributed framework significantly improves the performance of OBS networks, when compared to that of using shortest path routing, and attains a comparable performance to that of the centralized strategy. Moreover, the results also suggest that the framework is robust, as it does not require fine tuning its main parameters.

A strategy for minimising the probability of contention in optical burst-switching (OBS) networks, by combining traffic engineering in the wavelength domain with delayed burst scheduling at the ingress nodes, has been proposed. The implementation of this strategy only requires an increase on the processing and electronic buffering capacities of the ingress nodes, while avoiding the use of complex and expensive optical buffers at the core nodes. The performance evaluation study has shown that the proposed strategy outperforms the burst-scheduling strategies described in the literature by several orders of magnitude, in terms of burst-blocking probability. Moreover, the performance improvements have been shown to depend on the average offered traffic load, number of wavelengths per link and maximum delay allowed at the ingress nodes.

Future bandwidth-intensive services, which will have a wide impact on our daily lives, from entertainment, to business and health-care, demand high capacity, flexible, resilient and secure underlying networks. Simultaneously, rising energy costs and climate change concerns are increasing the pressure to adopt power-efficient solutions in communication networks. Most of these requirements are best fulfilled with optical networks, which are expected to provide the targeted high capacities together with an increasing number of functionalities, leaving behind the label of ldquodumb piperdquo associated to them in early deployments. This paper presents an overview of the challenges and some of the trends in optical networking, covering developments in multiple layers of the protocol stack, from the physical up to the application layer, and aimed at different network segments, from the access to the core network.

Optical burst switching (OBS) networks depend on contention resolution strategies to reach reasonable bandwidth utilization efficiency. However, these strategies increase both the complexity and cost of OBS core nodes. Research efforts have suggested that contention minimization strategies based on flexible and optimized burst scheduling at the ingress nodes, exploiting their inexpensive electronic buffers, can assist in the task of relaxing the hardware requirements of the network core nodes. This paper assesses the effectiveness of these contention minimization strategies and the impact of key network and traffic parameters, such as the maximum tolerable burst delay at the ingress nodes, average offered traffic load, number of wavelengths per link, average burst hop count, and node connectivity degree.

Optical burst switching (OBS) networks can benefit from optical buffering at the core nodes. Unfortunately, optical fibre delay line (FDL) buffers require additional switch ports, thereby increasing the switch size and cost. In this paper, an alternative and relatively uncommon view is taken towards core buffering in optical networks. Switch channel ports at underutilized links are replaced by buffer ports to which shared FDL buffers are attached, keeping the switch size fixed. A novel algorithm is proposed to improve the network blocking performance by jointly optimizing the buffers placement and the traffic routes. It is found that joint optimization gives the largest blocking probability improvement and employs only about one half of the number of FDL buffers required if the traffic is simply routed over the shortest paths.

The prospects of Optical Burst Switching (OBS) as a cost-effective switching paradigm for future all-optical transport networks could greatly benefit from avoiding the use of complex and expensive all-optical wavelength converters at the network nodes. However, contention resolution is essential to achieve reasonable bandwidth utilization efficiency in OBS networks and replacing the wavelength converters by Fiber Delay Line (FDL) buffers requires huge numbers of FDLs and large space switches, thus also rendering complex network nodes. This paper proposes combining the use of a priority-based wavelength assignment and burst scheduling strategy at the ingress nodes, which minimizes the probability of contention, with the use of shared FDL buffers at the core nodes to resolve the unavoidable contentions. The objective is to design OBS networks employing only moderate numbers of simple FDL buffers while matching the performance of a network using full-range wavelength converters. Simulation results using a reference network topology show that this goal is feasible. Moreover, the FDL buffer requirements are shown to depend on the offered traffic load, the number of wavelengths per link, and the maximum burst delay at the ingress node.

The prospects of optical burst switching (OBS) as a cost-effective switching paradigm for future all-optical transport networks would greatly benefit from minimizing the number of wavelength converters required at the network nodes. This paper presents a wavelength assignment framework tailored for OBS networks with shared wavelength converters directed to reach this aim. Simulation results using a reference network show that the performance attained with full-range dedicated wavelength converters can be achieved with less than half the number of these converters if shared converters are used instead. Moreover, it is shown that the number of converters can be further decreased by employing the proposed wavelength assignment framework. The extent of this decrease depends on the offered traffic load and the number of wavelengths per link.

The future prospects of optical burst switching (OBS) networks would greatly benefit, in terms of cost and ease of implementation, from limiting or even avoiding the deployment of wavelength conversion capabilities at the network nodes. This paper proposes a new strategy for minimizing wavelength contention in OBS networks. Simulation results suggest that this strategy can significantly reduce the performance penalty of avoiding wavelength conversion at the network nodes. Moreover, the new strategy is shown to outperform a previously proposed strategy, in some cases by several orders of magnitude, in terms of average burst blocking probability.