Alfonso Sanchez-Macian

As optical networks evolve toward dynamic, multi-band (C + L) architectures, efficient and QoT-aware resource management becomes essential to ensure scalable and low-service downtime operation. This paper introduces a novel, to our knowledge, unified hybrid grooming framework that addresses the unique challenges of traffic grooming in dynamic multi-band elastic optical networks (MB-EONs). Motivated by the need for cost-effective and adaptive high-capacity infrastructures, we propose a policy-based framework incorporating three heuristic algorithms tailored to distinct optimization goals. The unique challenges of multi-band optical networks, such as the non-uniform QoT performance caused by inter-channel stimulated Raman scattering (ISRS) are explicitly considered in our design, as they directly impact grooming efficiency, spectrum utilization, and achievable modulation formats. The algorithms include (i) Min–Max Channel, which minimizes spectrum fragmentation and reduces the partial bit rate blocking probability by up to 35%; (ii) Max Grooming Capacity, which improves line card interface (LCI) reuse and reduces deployment by 20%; and (iii) Time Aware, which minimizes reconfiguration counts by up to 80%, significantly lowering control overhead and service downtime. Unlike prior works limited to static or single-band scenarios, our framework is the first, to our knowledge, to dynamically integrate routing, band selection, modulation format, grooming, and spectrum assignment (RBMGSA) in a QoT-aware manner. Simulation results over the NSFNET, Japan, and Spain topologies under dynamic traffic conditions demonstrate that our approach supports flexible trade-offs among performance, cost, and reconfiguration complexity. Notably, the reconfigurable variants of our algorithms consistently outperform non-reconfigurable approaches by enhancing resource utilization and reducing blocking. The proposed system also supports partial grooming, enabling improved service accommodation and laying the groundwork for scalable and efficient operation in future multi-band optical networks.

Model networks and their underlying topologies have been used as a reference for techno-economic studies for several decades. Existing reference topologies for optical networks may cover different network segments such as backbone, metro core, metro aggregation, access, and/or data center. While telecommunication operators work on the optimization of their own existing deployed optical networks, the availability of different topologies is useful for researchers and technology developers to test their solutions in a variety of scenarios and validate the performance in terms of energy efficiency or cost reduction. This paper presents an open-source tool, MoleNetwork, to generate graphs (backbone, metro core, and metro aggregation) inspired by real network topologies of telecommunication operators that can be used as benchmarks for techno-economic studies. A new topology, to our knowledge, Italy2k, is generated based on the structure of a real operator’s network. Then, the tool is tested by validating that the expected operator parameters are matched in the generated topology and by using the topology to forecast technical demands in a 10-year period in one of its metro regions (core and aggregation networks).

This article presents an open‐source network simulator and digital twin focused on the analysis of latency in Metropolitan Area Networks (MAN). Our tool can estimate delay percentiles between pairs of nodes, aiming to see if the MAN can support emerging services and applications with strict latency requirements. We show that probability bounds like Vysochanskij–Petunin (VP) inequality can be used to accurately estimate latency percentiles between pairs of nodes with minimal computational effort. Theoretical results are validated with extensive simulations leveraging the simmer package, an open‐source Discrete Event Simulator (DES) written in R, along with igraph for visualization of networks and shortest path calculations. Two versions of the simulator are provided as open‐source on GitHub for the research community to use and build upon: One for local PC and a second one optimized to be executed in the cloud with multiple cores and massive memory.

Both multi-band and space division multiplexing (SDM) independently represent cost-effective approaches for next-generation optical backbone networks, particularly as data exchange between core data centers reaches the petabit-per-second scale. This paper focuses on different strategies for implementing band and SDM elastic optical network (BSDM EON) technology and analyzes the total network capacity of three sizes of backbone metro-core networks: ultra-long-, long-, and medium-distance networks related to the United States, Japan, and Spain, respectively. Two BSDM strategies are considered, namely, multi-core fibers (MCFs) and BSDM based on standard single-mode fiber (SSMF) bundles of multi-fiber pairs (BuMFPs). For MCF-based BSDM, we evaluated the performance of four manufactured trench-assisted weakly coupled (TAWC) MCFs with 4, 7, 13, and 19 cores. Simulation results reveal that, in the regime of ultra-low (UL) loss and inter-core crosstalk (ICXT), MCF-based throughput can be up to 14% higher than SSMF BuMFP-based BSDM when the core pitch exceeds 43 µm and the loss coefficient is lower than that of standard single-mode fibers. However, increasing the number of cores with (non-)standard cladding diameters, UL loss, and ICXT coefficient is not beneficial. As core counts increase up to 13 for non-standard cladding diameters (<230µm), the core pitch and loss coefficient also increase, leading to degraded performance of MCF-based BSDM compared to SSMF BuMFP-based BSDM. The results indicate that, in scenarios with 19 MFPs, SSFM BuMFP-based BSDM outperforms 19-core MCF-based scenarios, increasing the throughput by 55% to 73%, from medium-backbone networks to ultra-long ones.

In this paper, we introduce TEFNET24, a reference multi-layer hierarchical network topology that spans from access to core networks, specifically designed to meet the demands of beyond 5G and prepared for next-generation 6G communication systems. This topology, inspired by the actual network deployments of Telefónica in medium-sized countries (or large federal states) in Europe and America, integrates both IP and optical (DWDM) layers to provide a comprehensive framework for network design, optimization, and analysis. Our primary contribution is the development of an open-source benchmarking network, accessible to both researchers and industry professionals. This resource aims to facilitate the study and advancement of integrated IP and optical networks, allowing researchers to address key challenges such as traffic aggregation, latency reduction, cost efficiency, and support for advanced applications. We provide guidelines for utilizing this benchmark network, enabling users to evaluate and enhance their solutions for AI-driven network management, ultra-reliable low-latency communication, enhanced mobile broadband, and massive machine-type communication. By sharing this detailed and practical benchmarking network, we seek to foster innovation and collaboration within the optical network community, driving forward the capabilities and performance of future communication networks. A dataset with TEFNET24 details is provided.

Estimating the frequency of elements in a data stream and identifying the elements that appear many times (also known as heavy hitters) are needed in many applications such as traffic monitoring in networks or popularity estimate in web and social networks. The Count-Min Sketch (CMS) is probably one of the most widely used algorithms for frequency estimate. The CMS uses a sub-linear space to provide queries for data streams and retrieve an approximate value for the frequency of events. It has been used in many different applications and scenarios, making its security and privacy a matter of interest. This paper considers the privacy of the CMS and presents an algorithm to extract the most frequent elements (also known as top-K) and their estimate from a CMS. This is possible for universes of a limited size; when the attacker has access to the sketch, its hash functions and the counters at a specific point of time. The algorithm is tested using CAIDA traces showing that it is able to retrieve the group of top-K elements with an acceptable percentage of false positives and negatives. The results improve with the size of the sketch and for smaller values of K, indicating that in some practical settings an attacker can extract substantial information about the top-K elements from the sketch. The code used in the simulation is provided in a public open-source repository to facilitate reproducing our results and extending the ideas presented in this paper.

The relentless demand for high-bandwidth services and applications in the beyond-5G/6G era necessitates optical networks to provide ample spectral resources to accommodate the increasing traffic loads. This requirement is especially pronounced in metro and regional segments, where a projected traffic compound annual growth rate (CAGR) of over 40%, driven by content delivery network (CDN) traffic concentrated near the end users, threatens to push the fiber capacity to its limits on a number of heavily utilized links in the short to medium term. This limitation cannot be circumvented despite the utilization of spectrally efficient modulation formats designed for short-distance transmission. Thus, it is imperative to explore migration strategies to solutions that allow the expansion of spectral resources beyond the current usage of the extended C-band (4.8 THz). In this article, we present a comprehensive evaluation of multi-homed edge-to-core routing, modulation-level selection, and spectrum assignment simulations conducted over reference metropolitan area networks (MANs) by leveraging on a novel network planner called 6D-MAN, which we have developed to adapt to heterogeneous multi-layer networks based on multi-band and multi-fiber transmission. Our simulations consider coherent transmission with flexible modulation format transponders operating at capacities ranging from 100 to 400 Gbps on the 50 GHz grid and explore link-by-link migration strategies restricted to the C+L-band, ensuring optimal performance in terms of the generalized signal-to-noise ratio (GSNR). The obtained results demonstrate that deploying L-band equipment on a selected number of links effectively extends the lifespan of existing networks, enabling congestion-free operation with minimal intervention. In their entirety, our findings underscore the importance of contemplating alternative spectral resources beyond the conventional C-band. They unequivocally accentuate the potential of L-band equipment strategic deployment to tackle capacity constraints in MANs, resulting in a 60% reduction in fiber length and a remarkable 45% decrease in new fiber-pair link deployment needs. The profound implications of efficient fiber capacity utilization manifest themselves in substantial OPEX and optical total cost of ownership savings, amounting to approximately 71% and 17%–27%, respectively, over a 10-year period. This research provides valuable insights for MAN operators seeking sustainable strategies to support the growing demands of future beyond-5G/6G services.

Approximate membership filters are increasingly used in many computing and networking applications and new filter designs are being continuously presented to improve one or more performance metrics. Therefore, understanding their security and privacy is an important issue. Previous works have considered attackers that only have access to an individual filter in isolation. For applications that generate many related filters, such as a filter for a deny list that evolves over time, that analysis is insufficient. This paper considers an attacker with access to several versions of a filter that share most of the same input elements. We find that for typical implementations of Bloom, cuckoo, and quotient filters, the attacker gains little or no advantage with access to multiple versions of a filter. However, typical xor filters do reveal more information about their input elements by querying multiple versions of a filter, and we propose techniques to enhance the privacy of xor filters and others.

Counting Bloom Filters (CBFs) are approximate membership checking data structures, and it is normally believed that at most an approximate reconstruction of the underlying set can be derived when interacting with a CBF. This paper decisively refutes this assumption. In a recent paper, we considered the privacy of CBFs when the attacker has access to the implementation details and thus, it sees the filter as a white-box. In that setting, we showed that the attacker may be able to extract the elements stored in the filter when the number of false positives over the entire universe is not significantly larger than the number of elements stored in the filter. In this work, we consider a black-box attacker that can only perform user interactions on the CBF to insert, remove and query elements with no knowledge of the filter implementation details. We show that even in this case, an attacker may be able to extract information from the filter at the cost of using more complex and time-consuming attack algorithms. The proposed algorithms have been implemented and compared with the white-box attack, showing that in most cases, almost the same information can be extracted from the filter.

Approximate membership check filters are increasingly used to speed up data processing in many applications. Also, privacy is becoming a key design objective for many systems and thus, the privacy of filters needs to be carefully considered. Previous works have shown that an attacker that knows the implementation details of the filter and has access to its content, may be able to extract some information about the elements stored in the filter. This attack is, however, specific to Bloom filters and requires that the universe of elements must be small. In this article, we show that in many practical settings, an attacker that has only a black-box access to the filter, can extract information about the elements stored in the filter regardless of the specific filter type and the universe size. This is possible based on the key observation that in many applications, the elements stored in the filter are not randomly chosen, but they are concentrated in one or more parts of the universe of elements. To identify these parts, the positive probability can be measured on different parts of the universe; the parts having significantly larger values than the average positive probability for the filter are the ones on which the filter elements are concentrated. This approach is formalized and applied to several case studies showing the process by which the attacker can get additional information about the elements stored for the filters in a wide range of scenarios.