2023 19th International Conference on the Design of Reliable Communication Networks (DRCN),

Producción CientíficaLink failures have a significant negative impact on the availability of a network and should therefore be resolved as soon as possible. Because of the slow convergence time of routing protocols upon detection of a link failure, several IP Fast ReRoute (FRR) mechanisms have been developed to overcome this problem. Recently, segment routing, which is a flexible and scalable way of doing source routing, enabled a new FRR mechanism called Topology Independent Loop-Free Alternate (TI-LFA). As the name suggests, the key feature of TI-LFA is that it guarantees a loop-free detour against any link failure in any network topology. However, typically fast responses to failures only aim to restore the loop-free connection between the affected routers and do not consider the resulting delay or impact on network congestion. This paper presents an initial study on the selected TI-LFA backup paths and their effect on the overall network performance. By means of simulation, we evaluate how efficient TI-LFA reroutes traffic for a number of traffic engineering approaches. Our results quantify the impact of different traffic engineering approaches and network loads on the performance of TI-LFA. This suggests potential directions for improving the effectiveness of TI-LFA protection in segment routing.EU H2020 MSCA ITN-ETN IoTalentum (grant no. 953442)EU H2020-ICT-52-2020 TeraFlow Project (grant 101015857)Ministerio de Ciencia e Innovación y Agencia Estatal de Investigación (Proyecto PID2020-112675RB-C42 financiado por MCIN/AEI/10.13039/501100011033

Routing, Modulation and Spectrum Assignment Algorithm Using Multi-Path Routing and Best-Fit

Producción CientíficaElastic Optical Networks (EONs) are a promising optical technology to deal with the ever-increasing traffic and the vast number of connected devices of the next generation of the Internet, associated to paradigms like the Internet of Things (IoT), the Tactile Internet or the Industry 4.0, to name just a few. In this kind of optical network, each optical circuit or lightpath is provisioned by means of superchannels of variable bandwidth. In this manner, only the necessary bandwidth to accommodate the demand is allocated, improving the spectrum usage. When establishing a connection, the EON control layer determines the modulation format to be used and allocates a portion of the spectrum in a sequence of fibers from the source to the destination node providing the user-demanded bandwidth. This is known as the routing, modulation level and spectrum assignment (RMSA) problem. In this work, we firstly review the most important contributions in that area, and then, we propose a novel RMSA algorithm, multi-path best-fit (MP-BF), which uses a split spectrum multi-path strategy together with a spectrum assignment technique (best-fit), and which jointly exploit the flexibility of EONs. A simulation study has been conducted comparing the performance of EONs when using MP-BF with other proposals from the literature. The results of this study show that, by using MP-BF, the network can increase its performance in terms of lightpath request blocking ratio and supported traffic load, without affecting the energy per bit or the computation time required to find a solution

Hybrid RSS-RTT Localization Scheme for Indoor Wireless Networks

[EN]Nowadays, a variety of information related to the distance between two wireless devices can be easily obtained. This paper presents a hybrid localization scheme that combines received signal strength (RSS) and round-trip time (RTT) information with the aim of improving the previous localization schemes. The hybrid localization scheme is based on an RSS ranging technique that uses RTT ranging estimates as constraints among other heuristic constraints. Once distances have been well estimated, the position of the mobile station (MS) to be located is estimated using a new robust least-squared multilateration (RLSM) technique that combines the RSS and RTT ranging estimates mitigating the negative effect of outliers. The hybrid localization scheme coupled with simulations and measurements demonstrates that it outperforms the conventional RSS-based and RTT-based localization schemes, without using either a tracking technique or a previous calibration stage of the environment.Dirección General de Telecomunicaciones de la Consejería de Fomento de Castilla y Leó

Artificial intelligence (AI) methods in optical networks: A comprehensive survey

Producción CientíficaArtificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.Ministerio de Economía, Industria y Competitividad (Project EC2014-53071-C3-2-P, TEC2015-71932-REDT

International Conference on Broadband Communications, Networks and Systems

Producción CientíficaNetwork Function Virtualization (NFV) is considered to be one of the enabling technologies for 5G. NFV poses several challenges, like deciding the virtual network function (VNF) placement and chaining, and adding backup resources to guarantee the survivability of service chains. In this paper, we propose a genetic algorithm that jointly solves the VNF-placement, chaining and virtual topology design problem in WDM metro ring network, with the additional capacity of providing node protection. The simulation results show how important is to solve all of these subproblems jointly, as well as the benefits of using shared VNF and network resources between backup instances in order to reduce both the service blocking ratio and the number of active CPUs.Ministerio de Economía, Industria y Competitividad (grant TEC2017-84423-C3-1-P)Ministerio de Industria, Comercio y Turismo (grant BES 2015-074514)INTERREG V-A España-Portugal (POCTEP) (grant 0677_DISRUPTIVE_2_E)

Fair bandwidth allocation algorithm for PONS based on network utility maximization

Network utility maximization (NUM) models have been successfully applied to address multiple resource- allocation problems in communication networks. This paper explores, for the first time to our knowledge, their application to modeling the bandwidth-allocation problem in passive optical networks (PONs) and long-reach PONs. Using the NUM model, we propose the FEx-DBA (fair excess-dynamic bandwidth allocation) algorithm, a new DBA scheme to allow a fair and efficient allocation of the upstream channel capacity. The NUM framework provides the mathematical support to formally define the fairness concept in the resource allocation and the guidelines to devise FEx-DBA. A simulation study is conducted, whereby FEx-DBA is compared to a state-of-the-art proposal. We show that FEx-DBA (i) provides bandwidth guarantees to the users according to the service level agreement (SLA) contracted and fairly distributes the excess bandwidths among them; (ii) has a stable response and fast convergence when traffic or SLAs change, avoiding the oscillations appearing in other proposals; (iii) improves average delay and jitter measures; and (iv) only depends on a reduced set of parameters, which can be easily tuned.This work has been funded by Spanish Ministry of Science and Innovation (TEC2014-53071-C3-2-P and TEC2015-71932-REDT)

A testbed and a simulation laboratory for training engineering students in optical access network technologies

Producción CientíficaEngineering profiles focused on next-generation optical networks are gaining immense importance due to new emerging services and the amount of data expected in future network scenarios. In fact, not only are optical access networks leading to a major revolution in the network industry, but passive optical networks are the most widely deployed access networks worldwide today. This should be a strong incentive for universities to train their students in these innovative and recent technologies. In this vein, we propose the deployment of an optical communication laboratory with on-site experimental sessions in which students work with commercial equipment and realistic working environments. These working environments are necessary to train professionals in the area of optical networks. However, due to the high cost of the optical communications equipment, it is not possible to have a working place for each group and we combine these experimental sessions with some simulation sessions to complete the training. We present the design of this lab and a qualitative and quantitative study aimed at analyzing students’ experiences, the skills they have acquired, and the potential impact on their future careers. This study shows that students have a very positive perception of the lab, emphasizing that working with real equipment helps them improve technical skills and assimilate theoretical knowledge. They also point out they would like a higher number of subjects in their degrees to employ this type of lab. Finally, students perceive these sessions as very useful for their professional future.Unión Europea a través del programa INTERREG V-A España-Portugal (project 0677_DISRUPTIVE_2_E)Junta de Castilla y León (grant VA085G19)Ministerio de Ciencia, Innovación y Universidades (grants TEC2017-84423-C3-1-P and RED2018-102585-T

2020 22nd International Conference on Transparent Optical Networks (ICTON)

Producción CientíficaNetwork Function Virtualization (NFV) is a promising networking paradigm that will ease the network manageability and increase its flexibility, while reducing costs. In this paradigm, operators must solve the Virtual Network Function (VNF) placement and chaining problems. It is also important to provide backup resources to ensure the survivability of the offered services when a node failure happens. In this paper, we compare two different protection approaches to ensure the service resilience: individual VNF protection and end-to-end protection. Results show the benefits in terms of use of computing resources and energy consumption of protecting each VNF individually, compared to the end-to-end protection approach.Ministerio de Economía, Industria y Competitividad (grant TEC2017-84423-C3-1-P)Ministerio de Industria, Comercio y Turismo (fellowship BES-2015-074514)Research network Go2Edge (grant RED2018-102585-T)Interreg V-A Spain-Portugal (POCTEP) programme 2014- 202

A Framework for Next Generation Cloud-Native SDN Cognitive Resource Orchestrator for IoTs (NG2CRO)

Producción CientíficaSDN (Software Define Networking) and NFV (Network Function Virtualization) are the key enablers for 5G systems and also open many doors in the cloud-native application. Besides, it invites new challenges to the efficiency and scalability of resource management. This work aims to provide a cognitive framework for 5G resource and service orchestration in a cloud-native SDN environment. The proposed NG2CRO framework resource orchestrator is designed to adapt the network’s self-learning capabilities and dynamicity while taken on to account the network’s Markovian properties and diverse service requirements. We consider incorporating AI (Artificial Intelligence) techniques specifically RL (Reinforcement Learning) methodologies because literature has shown that these techniques can efficiently address and comply with the current dynamic behaviors and heterogeneity of 5G services and applications. In conclusion, both benefits and liabilities are discussed of incorporating AI specifically RL into resource orchestration practices that provide us with future research challenges.EU H2020 MSCA ITN-ETN IoTalentum (grant no. 953442)Consejería de Educación de la Junta de Castilla y León y FEDER (VA231P20)Ministerio de Ciencia e Innovación y Agencia Estatal de Investigación (Proyecto PID2020-112675RB-C42 financiado por MCIN/AEI/10.13039/501100011033

III Workshop on disruptive information and communication technologies for innovation and digital transformation

Producción CientíficaCon la aparición de tecnologías disruptivas como Internet de las Cosas (IoT), Industria 4.0 o Realidad Virtual (VR), entre otras, cada vez hay más servicios y dispositivos con diferentes características que se interconectan mediante redes de comunicaciones y necesitan capacidades de computación y almacenamiento con las que, en principio, no cuentan. Para superar este problema se propuso la solución de computación en la nube (cloud computing), que consiste básicamente en confiar las tareas más pesadas a un servidor central con alta potencia computacional. A primera vista este enfoque resuelve el problema, pero, como generalmente estos servidores centrales (data centers) se encuentran lejos de los dispositivos finales, aparecen nuevos problemas, especialmente con respecto al aumento de la latencia. La siguiente propuesta es el MEC (Multi-access Edge Computing, o computación de acceso múltiple en el borde), que es similar a la computación en la nube, pero se basa en servidores más cercanos a los usuarios, esto es, "en el borde" de la red de acceso, en lugar de servidores lejanos "en la nube". Este artículo ofrece una revisión de las principales características, de MEC, haciendo énfasis en su aplicación en escenarios como muchas regiones hispano-portuguesas, con baja densidad de población, grandes distancias entre ciudades o pueblos, y con un importante porcentaje de entornos rurales.Fondo Europeo de Desarrollo Regional FEDER a través del proyecto DISRUPTIVE del Programa Interreg V-A España-Portugal (POCTEP) 2014-2020Ministerio de Ciencia, Innovación y Universidades (grants (ONOFRE-2: TEC2017-84423-C3-1- P and Go2Edge: RED2018-102585-T)Junta de Castilla y León - Fondo Europeo de Desarrollo Regional (project VA231P20