Raul Muñoz

This special issue brings together seven extended papers originating from the 29th International Conference on Optical Networks Design and Modeling (ONDM 2025), held on 6–9 May 2025 at Scuola Superiore Sant’Anna in Pisa, Italy. ONDM 2025 addressed emerging optical-network technologies and architectures capable of providing the capacity, scalability, programmability, resilience, and energy efficiency required by future digital services. The selected contributions investigate multiband and spatial-division-multiplexing networks, impairment-aware resource allocation and grooming, hierarchical optical cross-connect planning, dedicated protection strategies, programmable filterless metro architectures, hollow-core-fiber deployment, and AI-driven multi-domain orchestration for integrated sensing and communication.

This paper presents a proof-of-concept implementation of a software-defined control framework for multiband over spatial-division multiplexing (MBoSDM) optical networks based on OpenROADM device data models. As optical networks evolve to meet rapidly increasing capacity and flexibility demands, the joint exploitation of spectral and spatial resources emerges as a key enabler for scalable multi-dimensional networking. However, most existing standards primarily target C-band operation and do not fully address multiband and SDM capabilities. In this work, we apply OpenROADM device models and develop SDN agents for multiband sliceable bandwidth-variable transceivers (S-BVTs), ROADMs, and hybrid multigranular nodes supporting wavelength, band, and spatial switching. A disaggregated optical network architecture is implemented, together with an enhanced SDN control plane based on our FlexOpt controller using NETCONF/YANG interfaces and Network Management Datastore Architecture (NMDA) extensions. The proposed solution supports multi-layer provisioning across the OTS/SDM and DWDM layers, including path computation and resource allocation strategies tailored to MBoSDM environments. Experimental validation demonstrates coordinated service provisioning over multiband (C, L, and S) and SDM domains, confirming the feasibility of OpenROADM-based control for next-generation optical networks. The results highlight the potential of model-driven, open, and programmable control frameworks to enable efficient, scalable, and interoperable MBoSDM network deployments.

This tutorial presents an overview of the recent developments of Transport API (TAPI, versions 2.5–2.6) as an open and standard north-bound interface for optical networks and its evolution and challenges to address the control of (coherent) pluggable devices as, for example, per TIP MANTRA reference architectures, along with an in-depth overview of the technologies, abstractions, and control-plane mechanisms required to operate such networks. We first review the softwarization of networks thanks to SDN, the adoption of model-driven development, the transition from discrete transponders to coherent pluggables, and the role of standardized interfaces such as OpenConfig or CMIS. Next, we elaborate on the foundations of TAPI, including its multi-layer information model, recent developments such as impairment extensions, and the representation of transceiver operational modes through TAPI profiles. The key challenge addressed is the control of coherent pluggables within packet–optical devices, where single/dual south-bound interfaces, Open-XR architectures, and MANTRA-inspired IPoWDM control models introduce coordination and synchronization requirements. We consider the role of TAPI in such control models along with the role of streaming telemetry for aspects such as distributed state synchronization and the use of PCE/digital twins for enabling closed-loop and autonomous operation.

Optical transport networks are evolving toward unprecedented capacity, sustainability, and security requirements. We present an SDN-enabled architecture for integrating continuous variable quantum key distribution (CV-QKD) into programmable optical networks, adopting sliceable bandwidth/bitrate variable transceivers (S-BVTs) and/or pluggable modules. The proposed solution combines a TeraFlowSDN-based SD-QKD network controller with a reconfigurable CV-QKD system through interfaces compliant with ETSI GS QKD 015. Experimental validation demonstrates real-time monitoring and dynamic wavelength (re)configuration, facilitating coexistence. Alternative dense wavelength-division multiplexing (DWDM) co-propagation scenarios are presented, and flexible channel allocation strategies are analyzed and discussed. Simulation results further evaluate evolutionary scenarios involving coexistence with 400G pluggable modules at 0 dBm launch power. The analysis identifies the maximum number of supported classical channels (up to 20 over a 20 km fiber link) and suitable spectral allocation in accordance with the experimental results. Furthermore, we compare the coexistence performance of CV-QKD adopting discrete components and an early version of a photonic integrated circuit (PIC) receiver, supporting half the number of 400G channels. Performance enhancement can be envisioned with further PIC design improvement and optimization. The obtained results confirm the viability of SDN-controlled CV-QKD as an enabler for quantum secure operation in future optical transport networks and a promising evolutionary path toward the adoption of this technology.

Previous generations of cellular communication, such as 5G, have been designed with the objective of improving key performance indicators (KPIs) such as throughput, latency, etc. However, to meet the evolving KPI demands and the ambitious sustainability targets for the Information and Communication Technology (ICT) industry, 6G will need to be designed differently. 6G will need to consider both the performance and sustainability targets for the various use cases it will serve. In addition, 6G will have various candidate technological enablers, making the design space of the system even more complex. Furthermore, due to the subjective nature of sustainability indicators, especially social sustainability, the literature still lacks clear methods to link them with technical enablers and 6G system design. Hence, in this article a novel method for 6G end-to-end (E2E) system design based on Knowledge graphs (KG) has been introduced. It considers as its input: the use case KPIs, use case sustainability requirements expressed as Key Values (KV) and KV Indicators (KVIs), the ability of the technological enablers to satisfy these KPIs and KVIs, the 6G system design principles defined in Hexa-X-II project, the maturity of a technological enabler and the dependencies between the various enablers. The KG method also introduces a novel approach for determining the key values addressed by a technological enabler. The effectiveness of the KG method was demonstrated by its application in designing the 6G E2E system for the cooperating mobile robot use case defined in the Hexa-X-II project, where 82 enablers were selected. Lastly, results from proof-of-concept demonstrations for a subset of the selected enablers have also been provided, which reinforce the efficacy of the KG method for designing a sustainable 6G system.

As bandwidth demands continue to rise, wavelength-level granularity in wavelength division multiplexing (WDM)-based optical networks becomes a limiting factor, as scaling such networks places increasing load on the WDM nodes. This motivates a shift toward coarser switching granularities. Node architectures will thus evolve from wavelength switching to waveband-selective switching and eventually to fiber cross-connects as capacity requirements grow. Multi-granular optical node (MG-ON) architectures support this transition by integrating wavelength, waveband, and spatial switching. However, during dynamic routing and resource assignment, MG-ON architectures may suffer from inefficient utilization of wavelength, waveband, and spatial resources. This can lead to increased connection request blocking. To address this, we propose a dynamic routing and resource assignment algorithm combined with an augmented optical grooming strategy for MG-ON networks. We evaluate the proposed approach in terms of connection accommodation, switch count, and per-switch port requirements across multiple network configurations. Its performance is compared with baseline WDM networks and existing MG-ON grooming strategies.

The Sixth-Generation (6G) networks are expected to support a multitude of vertical services, each with distinct intent requirements. Managing such diverse demands requires intelligent automation and dynamic resource allocation that aligns service objectives with limited network resources. This paper presents an Intent-Based Network (IBN) optimization framework to automate resource management and resolve conflicting service objectives. The Multi-Objective IBN Slicing (M2O-IBNS) system translates high-level service intents into concrete network configuration targets and jointly maximizes network throughput while minimizing both Energy Consumption (EC) and the costs associated with Slice Creation (SC). It proactively detects and resolves conflicts among slices by dynamically adjusting their Service Level Agreement (SLA) thresholds based on predefined priorities. Our numerical results demonstrate the efficacy of M2O-IBNS by consistently achieving solutions within a tight 1% optimality gap from the theoretical upper bound, and significantly outperforming State-of-the-Art (SoA) approaches by increasing throughput by up to 24.8%. Furthermore, our analysis reveals a critical trade-off: prioritizing the SLA of a single high-priority slice can secure its performance objectives, but at the cost of a significant reduction in overall network performance. For instance, imposing a strict SLA for one slice led to a 65% decrease in the cumulative throughput of all other slices, although it also reduced EC by 30% and SC costs by 77%. These findings demonstrate that our intent-driven optimization provides a powerful mechanism for Mobile Network Operators (MNOs) to strategically manage network resources, prioritize critical services, and quantitatively balance performance trade-offs across the entire network.

The Sixth-Generation (6G) mobile networks aim to automate network resource allocation and support both new and existing vertical services, each with diverse Quality of Service (QoS) intent requirements. Digital Service Providers (DSPs) must consider specific intent expectations, and targets set by different services, and re-configure and prioritize the most critical intents when resources are insufficient. This paper presents an optimization model for a flexible network paradigm using an Intent-Based Network Slicing (IBNS) framework that can manage the complexity of QoS intents and identify slice intent conflicts through closed-loop evaluation and monitoring. It dynamically adjusts the slice configurations to handle and mitigate detected conflicts by executing the agreed-upon Service Level Agreement (SLA) objectives (%) for higher-priority slices to ensure that critical intents are addressed. According to the results, this approach successfully meets the SLA target we set for slice but it negatively impacts the performance of other slices and degrades their slice capacity.

This paper presents a security and trust solution for 6G transport networks, focusing on the integration of Distributed Ledger Technology (DLT), Closed-Loop (CL) automation, and trust-based security management across multi-domain, multi-provider environments. The proposed solution is designed to enhance the security of End-to-End (E2E) services by enabling operators to define security and trust requirements while allowing providers to fulfilconnectivity services needs dynamically. Key elements of the solution include blockchain-based smart contracts to manage operator-transport provider agreements and Level-of-Trust (LoT) metrics for continuous trust evaluation. The paper highlights the role of security service level agreements (SSLAs) and trust-aware SLAs (TSLAs) in ensuring the integrity of service deployment and operations. Additionally, the integration of real-time monitoring and automated mitigation actions via CLs ensures that the system adapts to threats dynamically, maintaining continuous service security. The use of Artificial Intelligence -driven analytics for threat detection and mitigation further supports the robust security framework proposed for next-generation 6G systems. A multi-stakeholder scenario based on the use of different optical and packet-based transport domains is used in the experimental test case to validate the system’s effectiveness in dynamically reconfiguring security resources and adapting to evolving threats, showcasing its potential to meet the high-security demands of 6G networks. The solution ensures uninterrupted service and robust protection in multi-provider environments.

This work advances a 6G-ready, micro-granular SDN fabric that unifies high-performance edge data planes with intent-driven, multi-domain orchestration and cloud offloading. First, edge and cell-site whiteboxes are upgraded with Smart Network Interface Cards and embedded AI accelerators, enabling line-rate processing of data flows and on-box learning/inference directly in the data plane. This pushes functions such as traffic classification, telemetry, and anomaly mitigation to the point of ingress, reducing latency and backhaul load. Second, an SDN controller, i.e., ETSI TeraFlowSDN, is extended to deliver multi-domain SDN orchestration with native lifecycle management (LCM) for whitebox Network Operating Systems—covering onboarding, configuration-drift control, rolling upgrades/rollbacks, and policy-guarded compliance—so operators can reliably manage heterogeneous edge fleets at scale. Third, the SDN controller incorporates a new NFV-O client that seamlessly offloads network services—such as ML pipelines or NOS components—to telco clouds via an NFV orchestrator (e.g., ETSI Open Source MANO), enabling elastic placement and scale-out across the edge–cloud continuum. Together, these contributions deliver an open, programmable platform that couples in-situ acceleration with closed-loop, intent-based orchestration and elastic cloud resources, targeting demonstrable gains in end-to-end latency, throughput, operational agility, and energy efficiency for emerging 6G services.