Posts by Collection

ENTOMATIC: bioacoustic identification of the olive fruit fly

Published: September 01, 2015

About: ENTOMATIC addresses a major problem faced by EU Associations of Olive growing SMEs: the Olive fruit fly (Bactrocera oleae). This insect pest causes yearly economical losses estimated to be almost €600/ha. ENTOMATIC aims to develop a novel stand-alone field monitoring system comprising: a fully autonomous trap with integrated insect bioacoustic recognition embedded in a wireless sensor network and supported by a spatial decision support system.

Introducing Arduino and the IoT to Kids and Teenagers

Published: July 15, 2017

This project aims to disseminate and motivate the use of new technologies among young people. To that purpose, several activities have been so far held in collaboration with the UPF and Ajuntament de Barcelona.

Komondor: an IEEE 802.11ax simulator

Published: January 01, 2018

Komondor is an open-source simulation tool that aims to reproduce novel techniques to be included in next-generation WLANs. Particular emphasis is done to the IEEE 802.11ax amendment, and the inclusion of intelligent agents is one of the main novelties of the project.

GOAT: A Tool for Planning Wireless Sensor Networks

Published in International Workshop on Multiple Access Communications (MACOM), 2015

Abstract: This paper presents GOAT, a software tool that has been developed to study the effect of different Medium Access Control (MAC) and routing protocols on the energy consumption in Wireless Sensor Networks (WSNs). GOAT is a graphical network analysis tool that allows designing WSNs, calculating the energy consumption and overall lifetime in thoroughly configurable WSN scenarios. The aim of the GOAT tool is to obtain a knowledge of the behaviour of WSNs in terms of nodes connectivity and energy consumption prior to the WSN deployment in a real environment.

Recommended citation: Barrachina, S., Adame, T., Bel, A., & Bellalta, B. (2015, September). GOAT: A Tool for Planning Wireless Sensor Networks. In International Workshop on Multiple Access Communications (pp. 147-158). Springer, Cham. https://link.springer.com/chapter/10.1007/978-3-319-23440-3_12

Multi-hop communication in the uplink for LPWANs

Published in Computer Networks (Elsevier), 2017

Abstract: Low-Power Wide Area Networks (LPWANs) have arisen as a promising communication technology for supporting Internet of Things (IoT) services due to their low power operation, wide coverage range, low cost and scalability. However, most LPWAN solutions like SIGFOX™or LoRaWAN™rely on star topology networks, where stations (STAs) transmit directly to the gateway (GW), which often leads to rapid battery depletion in STAs located far from it. In this work, we analyze the impact on LPWANs energy consumption of multi-hop communication in the uplink, allowing STAs to transmit data packets in lower power levels and higher data rates to closer parent STAs, reducing their energy consumption consequently. To that aim, we introduce the Distance-Ring Exponential Stations Generator (DRESG) framework,1 designed to evaluate the performance of the so-called optimal-hop routing model, which establishes optimal routing connections in terms of energy efficiency, aiming to balance the consumption among all the STAs in the network. Results show that enabling such multi-hop connections entails higher network lifetimes, reducing significantly the bottleneck consumption in LPWANs with up to thousands of STAs. These results lead to foresee multi-hop communication in the uplink as a promising routing alternative for extending the lifetime of LPWAN deployments.

Recommended citation: Barrachina-Muñoz, S., Bellalta, B., Adame, T., & Bel, A. (2017). Multi-hop communication in the uplink for LPWANs. Computer Networks, 123, 153-168. https://www.sciencedirect.com/science/article/pii/S1389128617302207

Learning optimal routing for the uplink in LPWANs using similarity-enhanced e-greedy

Published in IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 2017

Abstract: Despite being a relatively new communication technology, Low-Power Wide Area Networks (LPWANs) have shown their suitability to empower a major part of Internet of Things applications. Nonetheless, most LPWAN solutions are built on star topology (or single-hop) networks, often causing lifetime shortening in stations located far from the gateway. In this respect, recent studies show that multi-hop routing for uplink communications can reduce LPWANs’ energy consumption significantly. However, it is a troublesome task to identify such energetically optimal routing through trial-and-error brute-force approaches because of time and, especially, energy consumption constraints. In this work we show the benefits of facing this exploration/exploitation problem by running centralized variations of the multi-arm bandit’s e-greedy, a well-known online decision-making method that combines best known action selection and knowledge expansion. Important energy savings are achieved when proper randomness parameters are set, which are often improved when conveniently applying similarity, a concept introduced in this work that allows harnessing the gathered knowledge by sporadically selecting unexplored routing combinations akin to the best known one.

Recommended citation: Barrachina-Muñoz, S., & Bellalta, B. (2017, October). Learning optimal routing for the uplink in LPWANs using similarity-enhanced e-greedy. In 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) (pp. 1-5). IEEE. https://ieeexplore.ieee.org/abstract/document/8292373/

Collaborative Spatial Reuse in Wireless Networks via Selfish Multi-Armed Bandits

Published in Ad-hoc Networks (Elsevier), 2017

Abstract: Next-generation wireless deployments are characterized by being dense and uncoordinated, which often leads to inefficient use of resources and poor performance. To solve this, we envision the utilization of completely decentralized mechanisms that enhance Spatial Reuse (SR). In particular, we concentrate in Reinforcement Learning (RL), and more specifically, in Multi-Armed Bandits (MABs), to allow networks to modify both their transmission power and channel based on their experienced throughput. In this work, we study the exploration-exploitation trade-off by means of the ε-greedy, EXP3, UCB and Thompson sampling action-selection strategies. Our results show that optimal proportional fairness can be achieved, even if no information about neighboring networks is available to the learners and WNs operate selfishly. However, there is high temporal variability in the throughput experienced by the individual networks, specially for ε-greedy and EXP3. We identify the cause of this variability to be the adversarial setting of our setup in which the set of most played actions provide intermittent good/poor performance depending on the neighboring decisions. We also show that this variability is reduced using UCB and Thompson sampling, which are parameter-free policies that perform exploration according to the reward distribution of each action.

Recommended citation: Wilhelmi, F., Cano, C., Neu, G., Bellalta, B., Jonsson, A., & Barrachina-Muñoz, S. (2019). Collaborative Spatial Reuse in Wireless Networks via Selfish Multi-Armed Bandits. Ad Hoc Networks 88 (2019): 129-141. https://www.sciencedirect.com/science/article/pii/S1570870518302646?casa_token=_3NaFYTPWgoAAAAA:7Z0DkV6IOJ3ITNi1uOoarip1kjU07-DKEdBMaYqoGHhDrqRoGLHQjHAOeaj9ETVoXNYrtXUx0w

HARE: Supporting efficient uplink multi-hop communications in self-organizing LPWANs

Published in Unknown Venue, 2018

Abstract: The emergence of low-power wide area networks (LPWANs) as a new agent in the Internet of Things (IoT) will result in the incorporation into the digital world of low-automated processes from a wide variety of sectors. The single-hop conception of typical LPWAN deployments, though simple and robust, overlooks the self-organization capabilities of network devices, suffers from lack of scalability in crowded scenarios, and pays little attention to energy consumption. Aimed to take the most out of devices’ capabilities, the HARE protocol stack is proposed in this paper as a new LPWAN technology flexible enough to adopt uplink multi-hop communications when proving energetically more efficient. In this way, results from a real testbed show energy savings of up to 15% when using a multi-hop approach while keeping the same network reliability. System’s self-organizing capability and resilience have been also validated after performing numerous iterations of the association mechanism and deliberately switching off network devices.

Recommended citation: Toni Adame Vazquez and Sergio Barrachina-Muñoz and Boris Bellalta and Albert Bel (2018). HARE: Supporting efficient uplink multi-hop communications in self-organizing LPWANs. Unknown Venue. https://www.mdpi.com/1424-8220/18/1/115

HARE: Supporting efficient uplink multi-hop communications in self-organizing LPWANs

Published in Sensors, 2018

Abstract: The emergence of low-power wide area networks (LPWANs) as a new agent in the Internet of Things (IoT) will result in the incorporation into the digital world of low-automated processes from a wide variety of sectors. The single-hop conception of typical LPWAN deployments, though simple and robust, overlooks the self-organization capabilities of network devices, suffers from lack of scalability in crowded scenarios, and pays little attention to energy consumption. Aimed to take the most out of devices’ capabilities, the HARE protocol stack is proposed in this paper as a new LPWAN technology flexible enough to adopt uplink multi-hop communications when proving energetically more efficient. In this way, results from a real testbed show energy savings of up to 15% when using a multi-hop approach while keeping the same network reliability. System’s self-organizing capability and resilience have been also validated after performing numerous iterations of the association mechanism and deliberately switching off network devices.

Recommended citation: Adame Vázquez, T., Barrachina-Muñoz, S., Bellalta, B., & Bel, A. (2018). HARE: Supporting efficient uplink multi-hop communications in self-organizing LPWANs. Sensors, 18(1), 115. https://www.mdpi.com/1424-8220/18/1/115

Potential and Pitfalls of Multi-Armed Bandits for Decentralized Spatial Reuse in WLANs

Published in Journal of Network and Computer Applications (JNCA), 2018

Abstract: Spatial Reuse (SR) has recently gained attention for performance maximization in IEEE 802.11 Wireless Local Area Networks (WLANs). Decentralized mechanisms are expected to be key in the development of SR solutions for next-generation WLANs, since many deployments are characterized by being uncoordinated by nature. However, the potential of decentralized mechanisms is limited by the significant lack of knowledge with respect to the overall wireless environment. To shed some light on this subject, we show the main considerations and possibilities of applying online learning to address the SR problem in uncoordinated WLANs. In particular, we provide a solution based on Multi-Armed Bandits (MABs) whereby independent WLANs dynamically adjust their frequency channel, transmit power and sensitivity threshold. To that purpose, we provide two different strategies, which refer to selfish and environment-aware learning. While the former stands for pure individual behavior, the second one aims to consider the performance experienced by surrounding networks, thus taking into account the impact of individual actions on the environment. Through these two strategies we delve into practical issues of applying MABs in wireless networks, such as convergence guarantees or adversarial effects. Our simulation results illustrate the potential of the proposed solutions for enabling SR in future WLANs, showing that substantial improvements on network performance can be achieved regarding throughput and fairness.

Recommended citation: Wilhelmi, F., Barrachina-Muñoz, S., Bellalta, B., Cano, C., Jonsson, A., & Neu, G. (2019). Potential and pitfalls of multi-armed bandits for decentralized spatial reuse in WLANs. Journal of Network and Computer Applications, 127, 26-42. https://www.sciencedirect.com/science/article/pii/S1084804518303655

Collaborative spatial reuse in wireless networks via selfish multi-armed bandits

Published in Unknown Venue, 2019

Abstract: Next-generation wireless deployments are characterized by being dense and uncoordinated, which often leads to inefficient use of resources and poor performance. To solve this, we envision the utilization of completely decentralized mechanisms to enable Spatial Reuse (SR). In particular, we focus on dynamic channel selection and Transmission Power Control (TPC). We rely on Reinforcement Learning (RL), and more specifically on Multi-Armed Bandits (MABs), to allow networks to learn their best configuration. In this work, we study the exploration-exploitation trade-off by means of the ε-greedy, EXP3, UCB and Thompson sampling action-selection, and compare their performance. In addition, we study the implications of selecting actions simultaneously in an adversarial setting (i.e., concurrently), and compare it with a sequential approach. Our results show that optimal proportional fairness can be achieved …

Recommended citation: Francesc Wilhelmi and Cristina Cano and Gergely Neu and Boris Bellalta and Anders Jonsson and Sergio Barrachina-Muñoz (2019). Collaborative spatial reuse in wireless networks via selfish multi-armed bandits. Unknown Venue. https://www.sciencedirect.com/science/article/pii/S1570870518302646

Combining software defined networks and machine learning to enable self organizing wlans

Published in Unknown Venue, 2019

Abstract: Next generation of wireless local area networks (WLANs) will operate in dense, chaotic and highly dynamic scenarios that in a significant number of cases may result in a low user experience due to uncontrolled high interference levels. Flexible network architectures, such as the software-defined networking (SDN) paradigm, will provide WLANs with new capabilities to deal with users’ demands, while achieving greater levels of efficiency and flexibility in those complex scenarios. On top of SDN, the use of machine learning (ML) techniques may improve network resource usage and management by identifying feasible configurations through learning. ML techniques can drive WLANs to reach optimal working points by means of parameter adjustment, in order to cope with different network requirements and policies, as well as with the dynamic conditions. In this paper we overview the work done in SDN for WLANs, as …

Recommended citation: Álvaro López-Raventós and Francesc Wilhelmi and Sergio Barrachina-Muñoz and Boris Bellalta (2019). Combining software defined networks and machine learning to enable self organizing wlans. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/8923569/

On the performance of the spatial reuse operation in IEEE 802.11 ax WLANs

Published in Unknown Venue, 2019

Abstract: The Spatial Reuse (SR) operation included in the IEEE 802.11ax-2020 (11ax) amendment aims at increasing the number of parallel transmissions in an Overlapping Basic Service Set (OBSS). However, many unknowns exist about the performance gains that can be achieved through SR. In this paper, we provide a brief introduction to the SR operation described in the IEEE 802.11ax (draft D4.0). Then, a simulation-based implementation is provided in order to explore the performance gains of the SR operation. Our results show the potential of using SR in different scenarios covering multiple network densities and traffic loads. In particular, we observe significant improvements on the channel utilization when applying SR with respect to the default configuration, thus allowing to increase the throughput and reduce the delay. Interestingly, the highest improvements provided by the SR operation are observed in the …

Recommended citation: Francesc Wilhelmi and Sergio Barrachina-Muñoz and Boris Bellalta (2019). On the performance of the spatial reuse operation in IEEE 802.11 ax WLANs. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/8931315/

Potential and pitfalls of multi-armed bandits for decentralized spatial reuse in WLANs

Published in Unknown Venue, 2019

Abstract: Spatial Reuse (SR) has recently gained attention to maximize the performance of IEEE 802.11 Wireless Local Area Networks (WLANs). Decentralized mechanisms are expected to be key in the development of SR solutions for next-generation WLANs, since many deployments are characterized by being uncoordinated by nature. However, the potential of decentralized mechanisms is limited by the significant lack of knowledge with respect to the overall wireless environment. To shed some light on this subject, we show the main considerations and possibilities of applying online learning to address the SR problem in uncoordinated WLANs. In particular, we provide a solution based on Multi-Armed Bandits (MABs) whereby independent WLANs dynamically adjust their frequency channel, transmit power and sensitivity threshold. To that purpose, we provide two different strategies, which refer to selfish and …

Recommended citation: Francesc Wilhelmi and Sergio Barrachina-Munoz and Boris Bellalta and Cristina Cano and Anders Jonsson and Gergely Neu (2019). Potential and pitfalls of multi-armed bandits for decentralized spatial reuse in WLANs. Unknown Venue. https://www.sciencedirect.com/science/article/pii/S1084804518303655

Dynamic Channel Bonding in Spatially Distributed High-Density WLANs

Published in IEEE Transactions on Mobile Computing, 2019

Abstract: In this paper, we discuss the effects on throughput and fairness of dynamic channel bonding (DCB) in spatially distributed high-density wireless local area networks (WLANs). First, we present an analytical framework based on continuous-time Markov networks (CTMNs) for depicting the behavior of different DCB policies in spatially distributed scenarios, where nodes are not required to be within the carrier sense range of each other. Then, we assess the performance of DCB in high-density IEEE 802.11ac/ax WLANs by means of simulations. We show that there may be critical interrelations among nodes in the spatial domain-even if they are located outside the carrier sense range of each other-in a chain reaction manner. Results also reveal that, while always selecting the widest available channel normally maximizes the individual long-term throughput, it often generates unfair situations where other WLANs starve. Moreover, we show that there are scenarios where DCB with stochastic channel width selection improves the latter approach both in terms of individual throughput and fairness. It follows that there is not a unique optimal DCB policy for every case. Instead, smarter bandwidth adaptation is required in the challenging scenarios of next-generation WLANs.

Recommended citation: Barrachina-Muñoz, S., Wilhelmi, F., & Bellalta, B. (2019). Dynamic channel bonding in spatially distributed high-density WLANs. IEEE Transactions on Mobile Computing, 19(4), 821-835. https://ieeexplore.ieee.org/abstract/document/8642923

Towards Energy Efficient LPWANs through Learning-based Multi-hop Routing

Published in IEEE 5th World Forum on Internet of Things (WF-IoT), 2019

Abstract: Low-power wide area networks (LPWANs) have been identified as one of the top emerging wireless technologies due to their autonomy and wide range of applications. Yet, the limited energy resources of battery-powered sensor nodes is a top constraint, especially in single-hop topologies, where nodes located far from the base station must conduct uplink (UL) communications in high power levels. On this point, multi-hop routings in the UL are starting to gain attention due to their capability of reducing energy consumption by enabling transmissions to closer hops. Nonetheless, a priori identifying energy efficient multi-hop routings is not trivial due to the unpredictable factors affecting the communication links in large LPWAN areas. In this paper, we propose epsilon multi-hop (EMH), a simple reinforcement learning (RL) algorithm based on epsilon-greedy to enable reliable and low consumption LPWAN multi-hop topologies. Results from a real testbed show that multi-hop topologies based on EMH achieve significant energy savings with respect to the default single-hop approach, which are accentuated as the network operation progresses.

Recommended citation: Barrachina-Muñoz, S., Adame, T., Bel, A., & Bellalta, B. (2019, April). Towards energy efficient LPWANs through learning-based multi-hop routing. In 2019 IEEE 5th World Forum on Internet of Things (WF-IoT) (pp. 644-649). IEEE. https://ieeexplore.ieee.org/abstract/document/8767193/

Combining Software Defined Networks and Machine Learning to enable Self Organizing WLANs

Published in 2019 International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), 2019

Abstract: Next generation of wireless local area networks (WLANs) will operate in dense, chaotic and highly dynamic scenarios that in a significant number of cases may result in a low user experience due to uncontrolled high interference levels. Flexible network architectures, such as the software-defined networking (SDN) paradigm, will provide WLANs with new capabilities to deal with users’ demands, while achieving greater levels of efficiency and flexibility in those complex scenarios. On top of SDN, the use of machine learning (ML) techniques may improve network resource usage and management by identifying feasible configurations through learning. ML techniques can drive WLANs to reach optimal working points by means of parameter adjustment, in order to cope with different network requirements and policies, as well as with the dynamic conditions. In this paper we overview the work done in SDN for WLANs, as well as the pioneering works considering ML for WLAN optimization. Finally, in order to demonstrate the potential of ML techniques in combination with SDN to improve the network operation, we evaluate different use cases for intelligent-based spatial reuse and dynamic channel bonding operation in WLANs using Multi-Armed Bandits.

Recommended citation: López-Raventós, Á., Wilhelmi, F., Barrachina--Muñoz, S., & Bellalta, B. (2019). Combining Software Defined Networks and Machine Learning to enable Self Organizing WLANs. In 2019 International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) (pp. 1-8). IEEE. https://ieeexplore.ieee.org/abstract/document/8923569/

To overlap or not to overlap: Enabling channel bonding in high-density WLANs

Published in Computer Networks (Elsevier), 2019

Abstract: Wireless local area networks (WLANs) are the most popular kind of wireless Internet connection because of their simplicity of deployment and operation. As a result, the number of devices accessing the Internet through WLANs such as laptops, smartphones, or wearables, is increasing drastically at the same time that applications’ throughput requirements do. To cope with these challenges, channel bonding (CB) techniques are used for enabling higher data rates by transmitting in wider channels, thus increasing spectrum efficiency. However, important issues like higher potential co-channel and adjacent channel interference arise when bonding channels. This may harm the performance of the carrier sense multiple access (CSMA) protocol because of recurrent backoff freezing while making nodes more sensitive to hidden node effects. In this paper, we address the following point at issue: is it convenient for high-density (HD) WLANs to use wider channels and potentially overlap in the spectrum? First, we highlight key aspects of DCB in toy scenarios through a continuous time Markov network (CTMN) model. Then, by means of extensive simulations covering a wide range of traffic loads and access point (AP) densities, we show that dynamic channel bonding (DCB) - which adapts the channel bandwidth on a per-packet transmission - significantly outperforms traditional single-channel on average. Nevertheless, results also corroborate that DCB is more prone to generate unfair situations where WLANs may starve. Contrary to most of the current thoughts pushing towards non-overlapping channels in HD deployments, we highlight the benefits of allocating channels as wider as possible to WLANs altogether with implementing adaptive access policies to cope with the unfairness situations that may appear.

Recommended citation: Barrachina-Muñoz, S., Wilhelmi, F., & Bellalta, B. (2019). To overlap or not to overlap: Enabling channel bonding in high-density WLANs. Computer Networks, 152, 40-53. https://www.sciencedirect.com/science/article/abs/pii/S1389128618309745

Komondor: a Wireless Network Simulator for Next-Generation High-Density WLANs

Published in Wireless Days, 2019

Abstract: Komondor is a wireless network simulator for next-generation wireless local area networks (WLANs). The simulator has been conceived as an accessible (ready-to-use) open source tool for research on wireless networks and academia. An important advantage of Komondor over other well-known wireless simulators lies in its high event processing rate, which is furnished by the simplification of the core operation. This allows outperforming the execution time of other simulators like ns-3, thus supporting large-scale scenarios with a huge number of nodes. In this paper, we provide insights into the Komondor simulator and overview its main features, development stages and use cases. The operation of Komondor is validated in a variety of scenarios against different tools: the ns-3 simulator and two analytical tools based on Continuous Time Markov Networks (CTMNs) and the Bianchi’s DCF model. Results show that Komondor captures the IEEE 802.11 operation very similarly to ns-3. Finally, we discuss the potential of Komondor for simulating complex environments – even with machine learning support – in next-generation WLANs by easily developing new user-defined modules of code.

Recommended citation: Barrachina-Muñoz, S., Wilhelmi, F., Selinis, I., & Bellalta, B. (2019, April). Komondor: a Wireless Network Simulator for Next-Generation High-Density WLANs. In 2019 Wireless Days (WD) (pp. 1-8). IEEE. https://ieeexplore.ieee.org/abstract/document/8734225

Online Primary Channel Selection for Dynamic Channel Bonding in High-Density WLANs

Published in Wireless Days, 2019

Abstract: In order to dynamically adapt the transmission bandwidth in wireless local area networks (WLANs), dynamic channel bonding (DCB) was introduced in IEEE 802.11n. It has been extended since then, and it is expected to be a key element in IEEE 802.11ax and future amendments such as IEEE 802.11be. While DCB is proven to be a compelling mechanism by itself, its performance is deeply tied to the primary channel selection, especially in high-density (HD) deployments, where multiple nodes contend for the spectrum. Traditionally, this primary channel selection relied on picking the most free one without any further consideration. In this letter, in contrast, we propose dynamic-wise (DyWi), a light-weight, decentralized, online primary channel selection algorithm for DCB that improves the expected WLAN throughput by considering not only the occupancy of the target primary channel but also the activity of the secondary channels. Even when assuming important delays due to primary channel switching, simulation results show a significant improvement both in terms of average delay and throughput.

Recommended citation: Barrachina-Muñoz, S., Wilhelmi, F., & Bellalta, B. (2019). Online Primary Channel Selection for Dynamic Channel Bonding in High-Density WLANs. IEEE Wireless Communications Letters, 9(2), 258-262. https://ieeexplore.ieee.org/abstract/document/8894073

On the Performance of the Spatial Reuse Operation in IEEE 802.11 ax WLANs

Published in IEEE Conference on Standards for Communications and Networking (CSCN), 2019

Abstract: The Spatial Reuse (SR) operation included in the IEEE 802.11ax-2020 (11ax) amendment aims at increasing the number of parallel transmissions in an Overlapping Basic Service Set (OBSS). However, many unknowns exist about the performance gains that can be achieved through SR. In this paper, we provide a brief introduction to the SR operation described in the IEEE 802.11ax (draft D4.0). Then, a simulation-based implementation is provided in order to explore the performance gains of the SR operation. Our results show the potential of using SR in different scenarios covering multiple network densities and traffic loads. In particular, we observe significant performance gains when a WLAN applies SR with respect to the default configuration. Interestingly, the highest improvements are observed in the most pessimistic situations in terms of network density and traffic load.

Recommended citation: Wilhelmi, F., Barrachina-Muñoz, S., & Bellalta, B. (2019, October). On the Performance of the Spatial Reuse Operation in IEEE 802.11 ax WLANs. In 2019 IEEE Conference on Standards for Communications and Networking (CSCN) (pp. 1-6). IEEE. https://ieeexplore.ieee.org/abstract/document/8931315/

A flexible machine-learning-aware architecture for future WLANs

Published in Unknown Venue, 2020

Abstract: Lots of hopes have been placed on machine learning (ML) as a key enabler of future wireless networks. By taking advantage of large volumes of data, ML is expected to deal with the ever-increasing complexity of networking problems. Unfortunately, current networks are not yet prepared to support the ensuing requirements of ML-based applications in terms of data collection, processing, and output distribution. This article points out the architectural requirements that are needed to pervasively include ML as part of future wireless networks operation. Specifically, we look into wireless local area networks (WLANs), which, due to their nature, can be found in multiple forms, ranging from cloud-based to edge-computing-like deployments. In particular, we propose to adopt the International Telecommunication Union (ITU) unified architecture for 5G and beyond. Based on ITU’s architecture, we provide insights on the main …

Recommended citation: Francesc Wilhelmi and Sergio Barrachina-Munoz and Boris Bellalta and Cristina Cano and Anders Jonsson and Vishnu Ram (2020). A flexible machine-learning-aware architecture for future WLANs. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/9040258/

A Flexible Machine Learning-Aware Architecture for Future WLANs

Published in IEEE Communications Magazine, 2020

Abstract: Lots of hopes have been placed in Machine Learning (ML) as a key enabler of future wireless networks. By taking advantage of the large volumes of data generated by networks, ML is expected to deal with the ever-increasing complexity of networking problems. Unfortunately, current networking systems are not yet prepared for supporting the ensuing requirements of ML-based applications, especially for enabling procedures related to data collection, processing, and output distribution. This article points out the architectural requirements that are needed to pervasively include ML as part of future wireless networks operation. To this aim, we propose to adopt the International Telecommunications Union (ITU) unified architecture for 5G and beyond. Specifically, we look into Wireless Local Area Networks (WLANs), which, due to their nature, can be found in multiple forms, ranging from cloud-based to edge-computing-like deployments. Based on the ITU’s architecture, we provide insights on the main requirements and the major challenges of introducing ML to the multiple modalities of WLANs.

Recommended citation: Wilhelmi, F., Barrachina-Munoz, S., Bellalta, B., Cano, C., Jonsson, A., & Ram, V. (2020). A Flexible Machine-Learning-Aware Architecture for Future WLANs. IEEE Communications Magazine, 58(3), 25-31. https://ieeexplore.ieee.org/abstract/document/9040258/

Wi-Fi All-Channel Analyzer (Runner up, best paper award)

Published in Proceedings of the 14th International Workshop on Wireless Network Testbeds, Experimental evaluation & Characterization (WINTECH), 2020

Abstract: In this paper, we present WACA, the first system to simultaneously measure the energy in all 24 Wi-Fi channels that allow channel bonding at 5 GHz with microsecond scale granularity. With WACA, we perform a first-of-its-kind measurement campaign in areas including urban hotspots, residential neighborhoods, universities, and a sold-out stadium with 98,000 fans and 12,000 simultaneous Wi-Fi connections. The gathered dataset is a unique asset to find insights otherwise not possible in the context of multi-channel technologies like Wi-Fi. To show its potential, we compare the performance of contiguous and non-contiguous channel bonding using a trace-driven framework. We show that while non-contiguous outperforms contiguous channel bonding’s throughput, occasionally bigger by a factor of 5, their average throughputs are similar.

Recommended citation: Barrachina-Muñoz, S., Bellalta, B., & Knightly, E. (2020, September). Wi-Fi All-Channel Analyzer. In Proceedings of the 14th International Workshop on Wireless Network Testbeds, Experimental evaluation & Characterization (pp. 72-79).

Responsive spectrum management for wireless local area networks: from heuristic-based policies to model-free reinforcement learning

Published in Unknown Venue, 2021

Abstract: In this thesis, we focus on the so-called spectrum management’s joint problem: efficient allocation of primary and secondary channels in channel bonding wireless local area networks (WLANs). From IEEE 802.11 n to more recent standards like 802.11 ax and 802.11 be, bonding channels together is permitted to increase transmissions’ bandwidth. While such an increase favors the potential network capacity and the activation of higher transmission rates, it comes at the price of reduced power per Hertz and accentuated issues on contention and interference with neighboring nodes. So, if WLANs were per se complex deployments, they are becoming even more complicated due to the increasing node density and the new technical features required by novel highly bandwidth-demanding applications. This dissertation provides an in-depth study of channel allocation and channel bonding in WLANs and discusses the suitability of solutions ranging from heuristic-based to reinforcement learning (RL)-based.

Recommended citation: Sergio Barrachina Muñoz (2021). Responsive spectrum management for wireless local area networks: from heuristic-based policies to model-free reinforcement learning. Unknown Venue. https://dialnet.unirioja.es/servlet/tesis?codigo=292244

Spatial reuse in IEEE 802.11 ax WLANs

Published in Unknown Venue, 2021

Abstract: Dealing with massively crowded scenarios is one of the most ambitious goals of next-generation wireless networks. With this goal in mind, the IEEE 802.11ax amendment includes, among other techniques, the Spatial Reuse (SR) operation. The SR operation encompasses a set of unprecedented techniques that are expected to significantly boost Wireless Local Area Networks (WLANs) performance in dense environments. In particular, the main objective of the SR operation is to maximize the utilization of the medium by increasing the number of parallel transmissions. Nevertheless, due to the novelty of the operation, its performance gains remain largely unknown. In this paper, we first provide a gentle tutorial of the SR operation included in the IEEE 802.11ax. Then, we analytically model SR and delve into the new kinds of MAC-level interactions among network devices. Finally, we provide a simulation-driven …

Recommended citation: Francesc Wilhelmi and Sergio Barrachina-Muñoz and Cristina Cano and Ioannis Selinis and Boris Bellalta (2021). Spatial reuse in IEEE 802.11 ax WLANs. Unknown Venue. https://www.sciencedirect.com/science/article/pii/S0140366421000499

Spatial Reuse in IEEE 802.11ax WLANs

Published in Computer Communications, 2021

Abstract: Dealing with massively crowded scenarios is one of the most ambitious goals of next-generation wireless networks. With this goal in mind, the IEEE 802.11ax amendment includes, among other techniques, the Spatial Reuse (SR) operation. The SR operation encompasses a set of unprecedented techniques that are expected to significantly boost Wireless Local Area Networks (WLANs) performance in dense environments. In particular, the main objective of the SR operation is to maximize the utilization of the medium by increasing the number of parallel transmissions. Nevertheless, due to the novelty of the operation, its performance gains remain largely unknown. In this paper, we first provide a gentle tutorial of the SR operation included in the IEEE 802.11ax. Then, we analytically model SR and delve into the new kinds of MAC-level interactions among network devices. Finally, we provide a simulation-driven analysis to showcase the potential of SR in various deployments, comprising different network densities and traffic loads. Our results show that the SR operation can significantly improve the medium utilization, especially in scenarios under high interference conditions. Moreover, our results demonstrate the non-intrusive design characteristic of SR, which allows enhancing the number of simultaneous transmissions with a low impact on the environment. We conclude the paper by giving some thoughts on the main challenges and limitations of the IEEE 802.11ax SR operation, including research gaps and future directions.

Recommended citation: Wilhelmi, F., Barrachina-Muñoz, S., Cano, C., Selinis, I., & Bellalta, B. (2021). Spatial Reuse in IEEE 802.11ax WLANs. Computer Communications 170, 65-83. https://arxiv.org/abs/1907.04141

Multi-Armed Bandits for Spectrum Allocation in Multi-Agent Channel Bonding WLANs

Published in IEEE/ACM Transactions on Networking, 2021

Abstract: While dynamic channel bonding (DCB) is proven to boost the capacity of wireless local area networks (WLANs) by adapting the bandwidth on a per-frame basis, its performance is tied to the primary and secondary channel selection. Unfortunately, in uncoordinated high-density deployments where multiple basic service sets (BSSs) may potentially overlap, hand-crafted spectrum management techniques perform poorly given the complex hidden/exposed nodes interactions. To cope with such challenging Wi-Fi environments, in this paper, we first identify machine learning (ML) approaches applicable to the problem at hand and justify why model-free RL suits it the most. We then design a complete RL framework and call into question whether the use of complex RL algorithms helps the quest for rapid learning in realistic scenarios. Through extensive simulations, we derive that stateless RL in the form of lightweight multi-armed-bandits (MABs) is an efficient solution for rapid adaptation avoiding the definition of broad and/or meaningless states. In contrast to most current trends, we envision lightweight MABs as an appropriate alternative to the cumbersome and slowly convergent methods such as Q-learning, and especially, deep reinforcement learning.

Recommended citation: Barrachina-Muñoz, S., Chiumento, A., & Bellalta, B. (2021). Multi-Armed Bandits for Spectrum Allocation in Multi-Agent Channel Bonding WLANs.IEEE Access..

Wi-Fi Channel Bonding: An All-Channel System and Experimental Study From Urban Hotspots to a Sold-Out Stadium

Published in IEEE/ACM Transactions on Networking, 2021

Abstract: In this paper, we present WACA, the first system to simultaneously measure all 24 Wi-Fi channels that allow channel bonding at 5 GHz with microsecond scale granularity. With WACA, we perform a first-of-its-kind measurement study in areas including urban hotspots, residential neighborhoods, universities, and even a game in Futbol Club Barcelona’s Camp Nou, a sold-out stadium with 98,000 fans and 12,000 simultaneous Wi-Fi connections. We study channel bonding in this environment, and our experimental findings reveal the underpinning factors controlling throughput gain, including channel bonding policy and spectrum occupancy statistics. We then show the significance of the gathered dataset for finding insights, which would not be possible otherwise, given that simple channel occupancy models severely underestimate the available gains. Likewise, we characterize the risks of channel bonding due to other BSS’s, including their missed transmission opportunities and potential collisions due to imperfect sensing of bonded transmissions. We explore 802.11ax which imposes constraints on bonded channels to avoid fragmentation and defines different modes that can trade implementation complexity for throughput. Lastly, we show that the stadium, while seemingly too highly occupied for channel bonding gains, has transient gaps yielding impressive gains.

Recommended citation: Barrachina-Muñoz, S., Bellalta, B., & Knightly, E. (2020, September). Wi-Fi All-Channel Analyzer. IEEE/ACM Transactions on Networking.

Stateless Reinforcement Learning for Multi-Agent Systems: the Case of Spectrum Allocation in Dynamic Channel Bonding WLANs

Published in IEEE 2021 Wireless Days (WD), 2021

Abstract: Spectrum allocation in the form of primary channel and bandwidth selection is a key factor for dynamic channel bonding (DCB) wireless local area networks (WLANs). To cope with varying environments, where networks change their configurations on their own, the wireless community is looking towards solutions aided by machine learning (ML), and especially reinforcement learning (RL) given its trial-and-error approach. However, strong assumptions are normally made to let complex RL models converge to near-optimal solutions. Our goal with this paper is two-fold: justify in a comprehensible way why RL should be the approach for wireless networks problems like decentralized spectrum allocation, and call into question whether the use of complex RL algorithms helps the quest of rapid learning in realistic scenarios. We derive that stateless RL in the form of lightweight multi-armed-bandits (MABs) is an efficient solution for rapid adaptation avoiding the definition of extensive or meaningless RL states.

Recommended citation: Barrachina-Muñoz, S., Chiumento, A., & Bellalta, B. (2021). Stateless Reinforcement Learning for Multi-Agent Systems: the Case of Spectrum Allocation in Dynamic Channel Bonding WLANs. IEEE 2021 Wireless Days (WD).

Cloud-native 5G experimental platform with over-the-air transmissions and end-to-end monitoring

Published in Unknown Venue, 2022

Abstract: 5G represents a revolutionary shift with respect to previous generations given its design centered on network softwarization. Within such a change of paradigm, cloud-native solutions are widely regarded as the future of vertical application development because of their enhanced flexibility and adaptability to complex and dynamic scenarios. In this context, we present an experimental framework with over-the-air transmissions that tackles two critical aspects for enhancing the lifecycle management of 5G and beyond networks: cloud-native deployments of 5G core network functions (NFs) and end-to-end monitoring. First, we deploy Open5GS and Prometheus-based monitoring as containerized network functions (CNFs) in a Kubernetes cluster spanning a multi-tier network with a multi-access edge computing (MEC) host. We then demonstrate the end-to-end monitoring system by showcasing via Grafana dashboards …

Recommended citation: Sergio Barrachina-Muñoz and Miquel Payaró and Josep Mangues-Bafalluy (2022). Cloud-native 5G experimental platform with over-the-air transmissions and end-to-end monitoring. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/9908028/

End-to-End Latency Analysis and Optimal Block Size of Proof-of-Work Blockchain Applications

Published in Unknown Venue, 2022

Abstract: Due to the increasing interest in blockchain technology for fostering secure, auditable, decentralized applications, a set of challenges associated with this technology need to be addressed. In this letter, we focus on the delay associated with Proof-of-Work (PoW)-based blockchains, whereby participants validate the new information to be appended to a distributed ledger via consensus to confirm transactions. We propose a novel end-to-end latency model based on batch-service queuing theory that characterizes timers and forks for the first time. Furthermore, we derive an estimation of the optimal block size analytically. Endorsed by analytical and simulation results, we show that the optimal block size approximation is a consistent method that leads to close-to-optimal performance by significantly reducing the overheads associated with blockchain applications.

Recommended citation: Francesc Wilhelmi and Sergio Barrachina-Muñoz and Paolo Dini (2022). End-to-End Latency Analysis and Optimal Block Size of Proof-of-Work Blockchain Applications. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/9843985/

Experimentation Scenarios for Machine Learning-Based Resource Management

Published in Unknown Venue, 2022

Abstract: 5G changes the landscape of mobile networks profoundly, with an evolved architecture supporting unprecedented capacity, spectral efficiency, and increased flexibility. The MARSAL project targets the development and evaluation of a complete framework for the management and orchestration of network resources in 5G and beyond by utilizing a converged optical-wireless network infrastructure in the access and fronthaul/midhaul segments. In this paper, we present a conceptual view of the MARSAL architecture, as well as a wide range of experimentation scenarios.

Recommended citation: Alexandros Kostopoulos and Ioannis P. Chochliouros and John Vardakas and Miquel Payaró and Sergio Barrachina and Md Arifur Rahman and Evgenii Vinogradov and Philippe Chanclou and Roberto Gonzalez and Charalambos Klitis and Sabrina De Capitani di Vimercati and Polyzois Soumplis and Emmanuel Varvarigos and Dimitrios Kritharidis and Kostas Chartsias (2022). Experimentation Scenarios for Machine Learning-Based Resource Management. Unknown Venue. https://link.springer.com/chapter/10.1007/978-3-031-08341-9_11

Intent-based orchestration for application relocation in a 5G cloud-native platform

Published in Unknown Venue, 2022

Abstract: The need of mobile network operators for cost-effectiveness is driving 5G and beyond networks towards highly flexible and agile deployments to adapt to dynamic and resource-constrained scenarios while meeting a myriad of user network stakeholders’ requirements. In this setting, we consider that zero-touch orchestration schemes based on cloud-native deployments equipped with end-to-end monitoring capabilities provide the necessary technology mix to be a solution candidate. This demonstration, built on top of an end-to-end cloud-native 5G experimental platform with over- the-air transmissions, shows how dynamic orchestration can relocate container-based end-user applications to fulfil intent-based requirements. Accordingly, we provide an experimental validation to showcase how the platform enables the desired flexible and agile 5G deployments.

Recommended citation: Sergio Barrachina-Muñoz and Jorge Baranda and Miquel Payaró and Josep Mangues-Bafalluy (2022). Intent-based orchestration for application relocation in a 5G cloud-native platform. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/9974703/

Mobile Edge Vertical Applications Using ETSI MEC APIs and Sandbox

Published in Unknown Venue, 2022

Abstract: MEC Sandbox is an excellent tool that simulates wireless networks and deploys ETSI Multi-access Edge Computing (MEC) APIs on top of the simulated wireless network. In this demo, we consume these APIs using a decision engine (DE) to scale a video-on-demand (VoD) application located on the network edge.Specifically, the developed DE uses the ETSI MEC Location API and retrieves the number of users in a given zone. The DE then takes actions at the microservice scaling level and executes them through a custom-made Kubernetes-based OpenAPI.

Recommended citation: Rasoul Nikbakht and Michail Dalgitsis and Sergio Barrachina-Muñoz and Sarang Kahvazadeh (2022). Mobile Edge Vertical Applications Using ETSI MEC APIs and Sandbox. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10051036/

End-to-End Latency Analysis and Optimal Block Size of Proof-of-Work Blockchain Applications

Published in arxiv, 2022

Abstract: Due to the increasing interest in blockchain technology for fostering secure, auditable, decentralized applications, a set of challenges associated with this technology need to be addressed. In this letter, we focus on the delay associated with Proof-of-Work (PoW)-based blockchain networks, whereby participants validate the new information to be appended to a distributed ledger via consensus to confirm transactions. We propose a novel end-to-end latency model based on batch-service queuing theory that characterizes timers and forks for the first time. Furthermore, we derive an estimation of optimum block size analytically. Endorsed by simulation results, we show that the optimal block size approximation is a consistent method that leads to close-to-optimal performance by significantly reducing the overheads associated with blockchain applications.

Recommended citation: Wilhelmi, F., Barrachina-Muñoz, S., & Dini, P. (2022). End-to-End Latency Analysis and Optimal Block Size of Proof-of-Work Blockchain Applications. arXiv preprint arXiv:2202.01497. https://arxiv.org/pdf/2202.01497.pdf

Towards Sustainable and Trustworthy 6G: Challenges, Enablers, and Architectural Design

Published in Unknown Venue, 2023

Abstract: While the 5th Generation (5G) system is being widely deployed across the globe, the information and communication technology (ICT) industry, research, standardization and consensus building for the 6th generation (6G) are already well underway with high expectations towards the merger of digital, physical, and human worlds. The main goal of this book is to introduce the upcoming 6G technologies and outline the foreseen challenges, enablers, and architectural design trends that will be instrumental in realizing a Sustainable and Trustworthy 6G system in the coming years. The envisioned 6G system promises to offer a more advanced and comprehensive user experience not only by achieving higher speeds, larger capacity, and lower latency, but also much more improved reliability, greater energy efficiency, and an enhanced security and privacy-preserving framework while natively integrating intelligence end-to-end (E2E). Achieving these goals will require innovative technological solutions and a holistic system design that considers the needs of various stakeholders and future 6G use cases. Capitalizing on the European 5G Public-Private-Partnership (5G PPP) Phase 3 projects working on 5G & Beyond and 6G research in recent years, and the join efforts between the Architecture Working Group (WG) and the 6G flagship Hexa-X project, this book delves into the critical challenges and enablers of the 6G system, including new network architectures and novel enhancements as well as the role of regulators, network operators, industry players, application developers, and end-users. Accordingly, this book provides a comprehensive …

Recommended citation: Ömer Bulakçı and Xi Li and Marco Gramaglia and Anastasius Gavras and Mikko Uusitalo and Patrik Rugeland and Mauro Boldi and et. al. (2023). Towards Sustainable and Trustworthy 6G: Challenges, Enablers, and Architectural Design. Unknown Venue. https://library.oapen.org/handle/20.500.12657/87169

A marketplace solution for distributed network management and orchestration of slices

Published in Unknown Venue, 2023

Abstract: The H2020 Distributed management of Network Slices in beyond 5G(MonB5G) project aims to provide zero-touch management and orchestration to support network slicing at scale to reduce the management burden on mobile operators by leveraging distribution of operations along with advanced data-driven Artificial Intelligence (AI)-based mechanisms. However, while this approach shows promise and large companies with abundant data and ML expertise are developing powerful MLdriven services, a critical aspect that remains to be analyzed is its business case. The vast majority of potentially valuable ML services, such as predictive maintenance, Quality of Service (QoS) optimization, network security enhancements, remain stuck at the idea or prototype stage. This paper delves into an analysis of how the MonB5G solutions in particular the tuples (Monitoring System (MS), Analytics Engine (AE), Decision …

Recommended citation: Engin Zeydan and Luis Blanco and Sergio Barrachina-Muñoz and Farhad Rezazadeh and Luca Vettori and Josep Mangues (2023). A marketplace solution for distributed network management and orchestration of slices. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10327832/

A Multi-Agent Deep Reinforcement Learning Approach for RAN Resource Allocation in O-RAN

Published in Unknown Venue, 2023

Abstract: Artificial intelligence (AI) and Machine Learning (ML) are considered as key enablers for realizing the full potential of fifth-generation (5G) and beyond mobile networks, particularly in the context of resource management and orchestration. In this demonstration, we consider a fully-fledged 5G mobile network and develop a multi-agent deep reinforcement learning (DRL) framework for RAN resource allocation. By leveraging local monitoring information generated by a shared gNodeB instance (gNB), each DRL agent aims to optimally allocate radio resources concerning service-specific traffic demands belonging to heterogeneous running services. We perform experiments on the deployed testbed in real-time, showing that DRL-based agents can allocate radio resources fairly while improving the overall efficiency of resource utilization and minimizing the risk of over provisioning.

Recommended citation: Farhad Rezazadeh and Lanfranco Zanzi and Francesco Devoti and Sergio Barrachina-Muñoz and Engin Zeydan and Xavier Costa-Pérez and Josep Mangues-Bafalluy (2023). A Multi-Agent Deep Reinforcement Learning Approach for RAN Resource Allocation in O-RAN. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10226154/

AI-Driven Framework for Scalable Management of Network Slices

Published in Unknown Venue, 2023

Abstract: This article describes a scalable solution for orchestrating and managing a massive number of network slices that leverages Artificial Intelligence (AI) techniques to design robust and sustainable networks. To achieve this goal, the proposed approach decomposes the management and orchestration (M&O) plane using separation of concerns and uses AI techniques to automate M&O operations. The M&O automation is achieved through the use of multiple, distributed and AI-driven control loops. The control loops have different goals and may work on the node level, slice level, inter-slice level or orchestration domain level. We also present a case study of using the proposed distributed intelligent components to scale, optimize and improve the network infrastructure. Finally, we briefly describe some challenges and future directions for scalable M&O on the road to 6G.

Recommended citation: Luis Blanco and Sławomir Kukliński and Engin Zeydan and Farhad Rezazadeh and Ashima Chawla and Lanfranco Zanzi and Francesco Devoti and Robert Kolakowski and Vasiliki Vlahodimitropoulou and Ioannis Chochliouros and Anne-Marie Bosneag and Sihem Cherrared and Luis A. Garrido and Sergio Barrachina-Muñoz and Josep Mangues (2023). AI-Driven Framework for Scalable Management of Network Slices. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10328194/

Cloud Native Federated Learning for Streaming: An Experimental Demonstrator

Published in Unknown Venue, 2023

Abstract: This paper demonstrates an implementation of Federated Learning (FL) for streaming applications using cloud-native technology. Compared to a centralized management, by adopting a decentralized approach, the FL method improves convergence time, reduces communication overhead, and increases network energy efficiency. The cloud-native FL architecture presented comprises three sites, each with its own Kubernetes (K8s) cluster. The edge sites run FL Analytical Engines (AEs)/clients for local training and updates, and the central site runs the aggregation server for FL training. Some other relevant workloads deployed at the clusters are the video streaming server, the orchestrator, and monitoring components. As for the RAN, we showcase a multi-gNB setup from which we obtain monitoring data via custom sampling functions. Following the description of the testbed infrastructure and setup, this …

Recommended citation: Sergio Barrachina-Muñoz and Engin Zeydan and Luis Blanco and Luca Vettori and Farhad Rezazadeh and Josep Mangues-Bafalluy (2023). Cloud Native Federated Learning for Streaming: An Experimental Demonstrator. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10147920/

Deploying cloud-native experimental platforms for zero-touch management 5G and beyond networks

Published in Unknown Venue, 2023

Abstract: An experimental framework for managing 5G and beyond networks through cloud‐native deployments and end‐to‐end monitoring is presented. The framework uses containerised network functions in a Kubernetes cluster across a multi‐domain network spanning cloud and edge hosts. End‐to‐end monitoring is demonstrated through Grafana dashboards that showcase both infrastructure resources and radio metrics in two scenarios involving UPF re‐selection and user mobility. As a third scenario, the authors demonstrate how a decision engine interacts with the experimental platform to perform zero‐touch containerised application relocation, highlighting the potential for enabling dynamic and intelligent management of 5G networks and beyond.

Recommended citation: Sergio Barrachina-Muñoz and Rasoul Nikbakht and Jorge Baranda and Miquel Payaró and Josep Mangues‐Bafalluy and Panagiotis Kokkinos and Polyzois Soumplis and Aristotelis Kretsis and Emmanouel Varvarigos (2023). Deploying cloud-native experimental platforms for zero-touch management 5G and beyond networks. Unknown Venue. https://ietresearch.onlinelibrary.wiley.com/doi/abs/10.1049/ntw2.12095

Disaggregating a 5G Non-Public Network via On-demand Cloud-Native UPF Deployments

Published in Unknown Venue, 2023

Abstract: Effective and real-time management of data planes becomes of paramount importance to support the ever-increasing challenging use cases and scenarios foreseen in 5G and beyond. In this demonstration, we present a comprehensive showcase of a cloud-native open-source 5G core deployment, realised as a disaggregated non-public network (NPN) spanning multiple locations. Ranging from cloud to edge points of presence, the demonstration establishes an end-to-end experimental platform with over-the-air transmission capabilities, specifically highlighting the on-demand creation and deletion of User-Plane Functions (UPFs). This dynamic deployment approach harnesses the advantages offered by edge locations, empowering the mobile network to adapt and scale as per its specific requirements. Furthermore, our demo elucidates how to use Open Source MANO (OSM) for easing the management …

Recommended citation: Jorge Baranda and Sergio Barrachina-Muñoz and Rasoul Nikbakht and Miquel Payaró and Josep Mangues-Bafalluy (2023). Disaggregating a 5G Non-Public Network via On-demand Cloud-Native UPF Deployments. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10327848/

The 6g architecture landscape: European perspective

Published in Unknown Venue, 2023

Abstract: This white paper summarizes the main findings from the European research landscape on the vision of the 6G architecture. Such a design vision is derived from around 45 projects starting from October 2020 in all relevant areas of 5G while paving the way towards 6G, within the 5G Public Private-Partnership (5G PPP) in the scope of the European Framework for Research and Innovation (the list of contributing projects can be obtained from the 5G PPP website at https://5g-ppp. eu/5g-ppp-phase-3-projects/.). At present, the European networking research community has started a new program along with 33 projects on the Smart Networks and Service (SNS) programme that will focus on 5G advanced and 6G. The 5G/B5G Architecture Working Group (WG), as part of the 5G PPP Initiative, is identifying and capturing novel trends and key technological enablers for the realization of the 5G and 6G architecture. The main findings and results of the Architecture WG are now captured in this white paper, which presents a consolidated view from European perspective on the technical directions for the architecture design in the 6G era.

Recommended citation: Agapi Mesodiakaki and Alexandros Kostopoulos and Anastasius Gavras and Arifur Rahman and Bahare Masood Khorsandi and Dimitris Tsolkas and John Cosmas and Marco Gramaglia and Mårten Ericson and Mauro Boldi and Mikko Uusitalo and Mir Ghoraishi and Ömer Bulakci and Patrik Rugeland and Xi Li and Adam Girycki and Adrian Gallego and Ahmad Nimr and Alejandro Ramirez and Alexandre Kazmierowski and Ali Mahbas and Anastassios Nanos and Andreas Gavrielides and Andreas Wolfgang and Andres Garcia-Saavedra and Antonio Cuadra Sánchez and Anttonen Antti and Bastien Béchadergue and Behrooz Makki and Ben Meunier and Bin Han and Carmela Occhipinti and Cédric Morin and César Berlanga De Miguel and Chao Fang and Charalambos Klitis and Charitha Madapatha and Christofer Lindheimer and Christos Tranoris and Christos Verikoukis and Dani Korpi and Dimitrios Fragkos and Dupleich Diego Andres and Ehsan Moeen Taghavi and Emmanouel Varvarigos and Francesco Devoti and Francisco Rodriguez Garcia and Frank HP Fitzek and Furkan Keskin and Geoffrey Eappen and Giacomo Bernini and Giada Landi and Ginés Garcia and Giovanni Nardini and Giuseppe Siracusano and Haeyoung Lee and Håkon Lønsethagen and Hannu Flinck and Hao Guo and Harilaos Koumaras and Hasanin Harkous and Henk Wymeersch and Hui Chen and Ignacio Labrador Pavón and Ioannis Chochliouros and Israel Koffman and Jafar Mohammadi and Janne Tuononen and John Vardakas and Jose Alcaraz-Calero and José Antonio Ordoñez Lucena and José Manuel Palacios Valverde and Kareem Ali and Kim Schindhelm and Kostas Ramantas and Liesbet Van der Perre and Loizos Christofi and Lorenzo Maria Ratto Vaquer and Lucas Scheuvens and Luigi Briguglio and Marco Araújo and Marco Fiore and Marie-Helene Hamon and Marios Sophocleous and Marius Corici and Martti Forsell and Matthias Weh and Mehdi Abad and Merve Saimler and Miltos Filippou and Ming Yin and Miquel Payaró and Mohammad Asif Habibi and Navideh Ghafouri and Ömer Haliloğlu and Pål Frenger and Panagiotis Demestichas and Panagiotis Kokkinos and Panagiotis Vlacheas and Petteri Pöyhönen and Pierangela Samarati and Qi Wang and Raul Barbosa and Renxi Qiu and Riccardo Bassoli and Roberto Gonzalez and Rui Pedro Eliseu and Samia Oukemeni and Sebastian Robitzsch and Sergio Barrachina and Simon Lindberg and Simon Pryor and Sofie Pollin and Sokratis Barmpounakis and Soumplis Polyzois and Stefan Wänstedt and Ta Dang Khoa LE and Tezcan Cogalan and Thomas Luetzenkirchen and Tommy Svensson and Valerio Frascolla and Valerio Prosseda and Vasiliki Lamprousi and Victor Gabillon and Vida Ranjbar and Vijaya Yajnanarayana and Vincenzo Sciancalepore and Xavier Costa and Xun Zhang (2023). The 6g architecture landscape: European perspective. Unknown Venue. https://research-portal.uws.ac.uk/en/publications/the-6g-architecture-landscape-european-perspective

Towards Natively Intelligent Networks

Published in Unknown Venue, 2023

Abstract: Towards Natively Intelligent Networks español English Login español español English Cambiar navegación Cambiar navegación Tipos de Publicaciones bookbook partconference objectdoctoral thesisjournal articlemagazinemaster thesispatenttechnical documentationtechnical report Ver ítem IMDEA Networks Principal Ver ítem IMDEA Networks Principal Ver ítem Towards Natively Intelligent Networks Compartir Ficheros 978-1-63828-239-6.ch5.pdf (31.61Mb) Identificadores URI: https://hdl.handle.net/20.500.12761/1774 ISBN: 978-1-63828-239-6 Metadatos Mostrar el registro completo del ítem Autor(es) Alcaraz-Calero, Jose M.; Antti, Anttonen; Araújo, Marco; Barbosa, Raul; Barmpounakis, Sokratis; Barrachina-Muñoz, Sergio; Bassoli, Riccardo; Bernini, Giacomo; Blanco, Luis; Bosneag, Anne-Marie; Chawla, Ashima; Christofi, Loizos; Dampahalage, Dilin; Demestichas, Panagiotis; Ericson, Marten; Farhadi, Hamed; …

Recommended citation: Jose M Alcaraz-Calero and Anttonen Antti and Marco Araújo and Raul Barbosa and Sokratis Barmpounakis and Sergio Barrachina-Muñoz and Riccardo Bassoli and Giacomo Bernini and Luis Blanco and Anne-Marie Bosneag and Ashima Chawla and Loizos Christofi and Dilin Dampahalage and Panagiotis Demestichas and Marten Ericson and Hamed Farhadi and Marco Fiore and Frank HP Fitzek and Hannu Flinck and Joāo Fonseca and Martti Forsell and Victor Gabillon and Ginés García-Avilés and Andres Garcia-Saavedra and Marco Gramaglia and Bin Han and Mikko Honkala and Alexandre Kazmierowski and Charalambos Klitis and Dani Korpi and Slawomir Kuklinski and Ignacio Labrador Pavón and Vasiliki Lamprousi and Giada Landi and Haeyoung Lee and Xi Li and Josep Mangues-Bafalluy and Bahare Masood Khorsandi and Mattia Merluzzi and Jafar Mohammadi and Cédric Morin and José Antonio Ordoñez Lucena and Petteri Pöyhönen and Nuwanthika Rajapaksha and Premanandana Rajatheva and Farhad Rezazadeh and Roberto Riggio and Lucas Scheuvens and Merve Seimler and Janne Tuononen and Ricard Vilalta and Qi Wang and Stefan Wunderer and Lanfranco Zanzi and Engin Zeydan and Xun Zhang (2023). Towards Natively Intelligent Networks. Unknown Venue. https://dspace.networks.imdea.org/handle/20.500.12761/1774

X-GRL: An empirical assessment of explainable GNN-DRL in B5G/6G networks

Published in Unknown Venue, 2023

Abstract: The rapid development of artificial intelligence (AI) techniques has triggered a revolution in beyond fifth-generation (B5G) and upcoming sixth-generation (6G) mobile networks. Despite these advances, efficient resource allocation in dynamic and complex networks remains a major challenge. This paper presents an experimental implementation of deep reinforcement learning (DRL) enhanced with graph neural networks (GNNs) on a real 5G testbed. The method addresses the explainability of GNNs by evaluating the importance of each edge in determining the model’s output. The custom sampling functions feed the data into the proposed GNN-driven Monte Carlo policy gradient (REINFORCE) agent to optimize the gNodeB (gNB) radio resources according to the specific traffic demands. The demo demonstrates real-time visualization of network parameters and superior performance compared to benchmarks.

Recommended citation: Farhad Rezazadeh and Sergio Barrachina-Muñoz and Engin Zeydan and Houbing Song and KP Subbalakshmi and Josep Mangues-Bafalluy (2023). X-GRL: An empirical assessment of explainable GNN-DRL in B5G/6G networks. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10329778/

5G-GOVSATCOM: 5G EU-GOVSATCOM Non-terrestrial Networks for Humanitarian Connectivity

Published in Unknown Venue, 2024

Abstract: This paper introduces the concept of the project 5G-GOVSATCOM funded by the European Union. 5G non-terrestrial networks (5G-NTN) will soon be able to handle all types of applications and provide service to a massive number of users. In this complex and dynamic network ecosystem, end-to-end adaptation of 5G-NTN to meet the specific requirements and use cases of EU-GOVSATCOM humanitarian services is crucial for the efficient deployment of European governmental satellite services. To enable such a vision, the 5GGOVSATCOM project targets the development and evaluation in a natural user environment of different key enabling technologies that aim to provide full integration of 5G-NTN (and terrestrial networks) in the EU-GOVSATCOM framework. All project developments are planned to be first validated in a controlled lab with satellite (and terrestrial) connectivity and, subsequently, to be …

Recommended citation: Miguel Ángel Vázquez and Sergio Barrachina-Muñoz and Mauro Di Si and Fotis Foukalas and Basilio Garrido and Giovanni Giambene and Makhlouf Hadji and Hamzeh Khalili and Josep Mangues-Bafalluy and Sara Nasirian and Marina Santos and Lorenzo Santilli and Theodoros A Tsiftsis and Marco Viali (2024). 5G-GOVSATCOM: 5G EU-GOVSATCOM Non-terrestrial Networks for Humanitarian Connectivity. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10855100/

A Novel Approach for Scalable and Sustainable 6G Networks

Published in Unknown Venue, 2024

Abstract: Hierarchical, distributed, scalable and Artificial Intelligence (AI)-based management of a massive number of network slices in different domains with the goal of zero-touch management is a major challenge for 6G networks. In this paper, we first propose a new vision for distributed network management and orchestration based on existing standardization architectures. This vision aims to embed AI/Machine Learning (ML) into the AI/ML architectures of Standardization Development Organizations (SDOs) such as the 3rd Generation Partnership Project (3GPP), the European Telecommunications Standards Institute (ETSI) and the International Telecommunication Union (ITU). Our second contribution is a numerical comparison of the benefits of the proposed distributed management and orchestration approach in terms of energy savings through Federated Learning (FL). The experimental topology includes a …

Recommended citation: Luis Blanco and Engin Zeydan and Sergio Barrachina-Muñoz and Farhad Rezazadeh and Luca Vettori and Josep Mangues-Bafalluy (2024). A Novel Approach for Scalable and Sustainable 6G Networks. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10457850/

Coordinated Multi-Armed Bandits for Improved Spatial Reuse in Wi-Fi

Published in Unknown Venue, 2024

Abstract: Multi-Access Point Coordination (MAPC) and Artificial Intelligence and Machine Learning (AI/ML) are expected to be key features in future Wi-Fi, such as the forthcoming IEEE 802.11bn (Wi-Fi 8) and beyond. In this paper, we explore a coordinated solution based on online learning to drive the optimization of Spatial Reuse (SR), a method that allows multiple devices to perform simultaneous transmissions by controlling interference through Packet Detect (PD) adjustment and transmit power control. In particular, we focus on a Multi-Agent Multi-Armed Bandit (MA-MAB) setting, where multiple decision-making agents concurrently configure SR parameters from coexisting networks by leveraging the MAPC framework, and study various algorithms and reward-sharing mechanisms. We evaluate different MA-MAB implementations using Komondor, a well-adopted Wi-Fi simulator, and demonstrate that AI-native SR …

Recommended citation: Francesc Wilhelmi and Boris Bellalta and Szymon Szott and Katarzyna Kosek-Szott and Sergio Barrachina-Muñoz (2024). Coordinated Multi-Armed Bandits for Improved Spatial Reuse in Wi-Fi. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/11140340/

DEMO: On-Demand 5G/6G Edge Verticals via Third-Party UPF Selection and Cloud-Native Relocation

Published in Unknown Venue, 2024

Abstract: Integrating edge computing with 5G/6G, bolstered by standards such as ETSI Multi-access Edge Computing (MEC), becomes indispensable, particularly in addressing end-to-end latency-sensitive vertical applications. Thus, it is imperative to delve into infrastructure and network considerations, including the relocation of server workloads and optimization of user data planes. Notably, 3GPP facilitates third-party vertical providers’ access to user equipment (UE) metrics and data plane capacities through the Network Exposure Function (NEF). This paper showcases a demonstration that focuses on the seamless coordination of cloud-native workload relocation and user plane function (UPF) selection within the 5G network. Here, the interaction between a vertical provider and the 5G core enables informed decisions aimed at ensuring minimal latency by triggering UPF selection and relocation of containerized servers to …

Recommended citation: Sergio Barrachina-Muñoz and Rasoul Nikbakht and Albert Bel and Baranda Jorge and Miquel Payaró and Josep Mangues-Bafalluy (2024). DEMO: On-Demand 5G/6G Edge Verticals via Third-Party UPF Selection and Cloud-Native Relocation. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10733658/

Demo: On-demand Disaggregated Deployment of Cloud-Native Mobile Networks from Core to RAN

Published in Unknown Venue, 2024

Recommended citation: Jorge Baranda and Albert Bel and Sergio Barrachina-Muñoz and Miquel Payaró and Josep Mangues-Bafalluy (2024). Demo: On-demand Disaggregated Deployment of Cloud-Native Mobile Networks from Core to RAN. Unknown Venue.

Distributed Sequential Cloud-Native Deployment of an End-to-End 5G Network with O-RAN Functions

Published in Unknown Venue, 2024

Abstract: The exploitation of novel networking paradigms to manage next-generation mobile networks is essential to meet the requirements of emerging use cases and scenarios. In this demonstration, we showcase a comprehensive end-to-end cloud-native open-source deployment of a 5G mobile network incorporating O-RAN functionality. Spanning across distributed points of presence, this demonstration features a disaggregated and sequential deployment of mobile entities, enabling seamless adaptation to the availability and distribution of computational resources. We highlight the on-demand plug-and-play of different monitoring xApp instances to show the flexibility of the deployment process as a critical enabler towards more autonomous orchestration procedures aimed at optimizing network performance.

Recommended citation: Jorge Baranda and Albert Bel and Sergio Barrachina-Muñoz and Miquel Payaró and Josep Mangues-Bafalluy (2024). Distributed Sequential Cloud-Native Deployment of an End-to-End 5G Network with O-RAN Functions. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10741499/

Empowering Beyond 5G Networks: An Experimental Assessment of Zero-Touch Management and Orchestration

Published in Unknown Venue, 2024

Abstract: Effective zero-touch management and orchestration (ZSM&O) is crucial for scaling network slicing, particularly transitioning toward Beyond 5G (B5G) and 6G networks. This paper empirically validates the network slicing framework developed under the European Union Horizon 2020 MonB5G project. Building on three years of academia-industry collaboration, MonB5G introduces a flexible slicing model featuring umbrella slices that orchestrate modular, specialized slices across multi-domain environments to address next-generation service demands. For the first time, we evaluate its practicality in a 5G cloud-native testbed through a virtual reality (VR) streaming use case, supported by solutions such as federated learning-based CPU forecasting, anomaly detection, and deep reinforcement learning (DRL) for radio access network (RAN) optimization. The paper offers insights from technically demanding …

Recommended citation: Sergio Barrachina-Muñoz and Farhad Rezazadeh and Luis Blanco and Sławomir Kukliński and Engin Zeydan and Ashima Chawla and Lanfranco Zanzi and Francesco Devoti and Vasiliki Vlahodimitropoulou and Ioannis Chochliouros and Anne-Marie Bosneag and Sihem Cherrared and Luca Vettori and Josep Mangues-Bafalluy (2024). Empowering Beyond 5G Networks: An Experimental Assessment of Zero-Touch Management and Orchestration. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10776956/

Performance optimization across the edge-cloud continuum: A multi-agent rollout approach for cloud-native application workload placement

Published in Unknown Venue, 2024

Abstract: The advancements in virtualization technologies and distributed computing infrastructures have sparked the development of cloud-native applications. This is grounded in the breakdown of a monolithic application into smaller, loosely connected components, often referred to as microservices, enabling enhancements in the application’s performance, flexibility, and resilience, along with better resource utilization. When optimizing the performance of cloud-native applications, specific demands arise in terms of application latency and communication delays between microservices that are not taken into consideration by generic orchestration algorithms. In this work, we propose mechanisms for automating the allocation of computing resources to optimize the service delivery of cloud-native applications over the edge-cloud continuum. We initially introduce the problem’s Mixed Integer Linear Programming (MILP …

Recommended citation: Polyzois Soumplis and Georgios Kontos and Panagiotis Kokkinos and Aristotelis Kretsis and Sergio Barrachina-Muñoz and Rasoul Nikbakht and Jorge Baranda and Miquel Payaró and Josep Mangues-Bafalluy and Emmanuel Varvarigos (2024). Performance optimization across the edge-cloud continuum: A multi-agent rollout approach for cloud-native application workload placement. Unknown Venue. https://link.springer.com/article/10.1007/s42979-024-02630-w

Toward Explainable Reasoning in 6G: A Proof of Concept Study on Radio Resource Allocation

Published in Unknown Venue, 2024

Abstract: The move toward artificial intelligence (AI)-native sixth-generation (6G) networks has put more emphasis on the importance of explainability and trustworthiness in network management operations, especially for mission-critical use-cases. Such desired trust transcends traditional post-hoc explainable AI (XAI) methods to using contextual explanations for guiding the learning process in an in-hoc way. This paper proposes a novel graph reinforcement learning (GRL) framework named TANGO which relies on a symbolic subsystem. It consists of a Bayesian-graph neural network (GNN) Explainer, whose outputs, in terms of edge/node importance and uncertainty, are periodically translated to a logical GRL reward function. This adjustment is accomplished through defined symbolic reasoning rules within a Reasoner. Considering a real-world testbed proof-of-concept (PoC), a gNodeB (gNB) radio resource allocation …

Recommended citation: Farhad Rezazadeh and Sergio Barrachina-Muñoz and Hatim Chergui and Josep Mangues and Mehdi Bennis and Dusit Niyato and Houbing Song and Lingjia Liu (2024). Toward Explainable Reasoning in 6G: A Proof of Concept Study on Radio Resource Allocation. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10689363/

An Automated Configurable Cloud-Native Monitoring System for the Radio Access Network

Published in Unknown Venue, 2025

Abstract: Novel networking paradigms based on cloudification and open interfaces are making mobile networks more agile to adapt and meet the requirements of emerging use cases. Based on an automated end-to-end cloud-native open-source deployment of a 5G mobile network with over-the-air capabilities, this demonstration features the inclusion of a cloud-native monitoring system to follow the radio access network (RAN) performance evolution. By just defining the number of gNBs, this monitoring system automatically configures independent data sources and dashboards representing the evolution of received information while such gNBs are progressively created on-demand in a distributed environment.

Recommended citation: Jorge Baranda and Albert Bel and Sergio Barrachina-Muñoz and Miquel Payaró and Josep Mangues-Bafalluy (2025). An Automated Configurable Cloud-Native Monitoring System for the Radio Access Network. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10978753/

End-to-End Slice Orchestration in a 5G cloud-native Mobile Network with O-RAN Split 7.2

Published in Unknown Venue, 2025

Abstract: The adoption of novel network paradigms in the architecture and management of mobile networks is accelerating its evolution. In this demonstration, we contribute to the cloud-native mobile network orchestration domain by presenting an end-to-end system allowing the disaggregated and distributed deployment of mobile network entities from core to RAN based on open-source software. The distinguishing features of this system are the possibility of enabling the configuration of slices that can be later activated on-demand and the use of O-RAN Split 7.2 for over-the-air transmission using commercial equipment.

Recommended citation: Jorge Baranda and Albert Bel and Sergio Barrachina-Muñoz and Miquel Payaró and Josep Mangues-Bafalluy (2025). End-to-End Slice Orchestration in a 5G cloud-native Mobile Network with O-RAN Split 7.2. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/11152761/

Experiment-as-a-Service in the Pipeline: Empowering CI/CD with xG Acceptance Testing

Published in Unknown Venue, 2025

Abstract: Experimentation in 5G and next-generation (xG) mobile networks is crucial for overcoming the limitations of theoretical models and simulations in accurately reflecting real-world complexities. The dynamic nature of advanced wireless communications necessitates practical validation through hands-on testing, a need increasingly addressed by 5G and beyond testbeds. However, challenges remain in ensuring these testbeds are easy to use and open enough to enable users and companies to interact autonomously with the experimental platforms, minimizing human intervention towards a zero-touch approach. This work, presented as a short paper on ongoing research and innovative ideas, introduces a novel approach that leverages Experiment-as-a-Service (ExaS) to enhance Continuous Integration and Continuous Deployment (CI/CD) by integrating xG testbeds into the acceptance testing phase. We discuss the …

Recommended citation: Sergio Barrachina-Muñoz and Horacio Bleda and Manuel Requena and Selva Vía and Miquel Payaró and Josep Mangues-Bafalluy (2025). Experiment-as-a-Service in the Pipeline: Empowering CI/CD with xG Acceptance Testing. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10925993/

Satellite-Terrestrial Integration: 5G Architectures for the Seamless Support of Mission Critical Services

Published in Unknown Venue, 2025

Abstract: This paper studies integration issues for the achievement of TN-NTN systems providing mission-critical (MCX) services in the EU 5G-GOVSATCOM project. The standardization of NTN as an integral part of 5G terrestrial systems is progressing, with important progress made in the last Releases 17 and 18. This important evolution, however, is not complete because the integration of the two networks is also needed at the protocol level. In the first part of this paper, we investigate MCX requirements. Then, two alternative architectures are considered with distinct core networks or with unified core networks, according to Release 20. The second part of this paper presents the issue of the seamless Vertical Handover between TN and NTN, proposing the adoption of a smart gateway server, a new block of the 5G system to manage a seamless switch from the two networks when some critical conditions are met. Using VPNs …

Recommended citation: Sara Nasirian and Giovanni Giambene and Sergio Barrachina-Muñoz and Josep Mangues-Bafalluy and Makhlouf Hadji and Miguel Ángel Vazquez and Lorenzo Santilli and Fotis Foukalas and Hamzeh Khalili (2025). Satellite-Terrestrial Integration: 5G Architectures for the Seamless Support of Mission Critical Services. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/10946027/

Vertical Handover Scheme Evaluation for GOVSATCOM Systems

Published in Unknown Venue, 2025

Abstract: The European Governmental Satellite Communications (EU GOVSATCOM) program aims to federate European satellite operators and integrate their systems with 5G terrestrial networks to improve mission-critical services. This paper investigates the Vertical Handover (VHO) between Terrestrial Networks (TN) and Non-Terrestrial-Networks (NTN) and proposes a scheme suitable for the experimentation of the trial phase of the 5G-GOVSATCOM project. A suitable model has been identified for analyzing the VHO scheme, taking into account the effect of shadowing correlation. Suitable SINR-based VHO triggering conditions have been identified. The VHO performance has been evaluated using key performance indicators (i.e., VHO failure rate and VHO ping-pong rate), identifying the settings that meet the Quality of Service (QoS) requirements.

Recommended citation: Giovanni Giambene and Sara Nasirian and Minh Hoang Nguyen and Sergio Barrachina-Muñoz and Josep Mangues-Bafalluy (2025). Vertical Handover Scheme Evaluation for GOVSATCOM Systems. Unknown Venue. https://ieeexplore.ieee.org/abstract/document/11037172/

GOAT: A Tool for Planning Wireless Sensor Networks

Published: September 15, 2015

Presentation of the paper entitled “GOAT: A Tool for Planning Wireless Sensor Networks”, available here.

Poster: Enhancing Wireless Networks Performance through Learning-based Dynamic Spectrum Access

Published: March 01, 2017

Abstract: The number of devices accessing the Internet through Wireless Local Area Networks (WLANs) is increasing drastically. WLANs are managed by different operators, leading to chaotic wireless spectrum occupancy. By means of transmitting in wider channels through dynamic spectrum access, higher short-term throughputs are achieved. However, the contention among nodes leads to undesirable low performance, which is critical in high-density scenarios like football stadiums and apartment buildings. We propose a learning-based channel selection policy for optimizing WLANs throughput.

Learning optimal routing for the uplink in LPWANs using similarity-enhanced e-greedy

Published: October 12, 2017

Presentation of paper entitled “Learning optimal routing for the uplink in LPWANs using similarity-enhanced e-greedy”, available here.

Poster: Performance Analysis of Dynamic Channel Bonding in Spatially Distributed High Density WLANs

Published: March 09, 2018

Abstract: We present novel insights on the effects of dynamic channel bonding (DCB) policies in WLANs. We depict the complex interactions that are given in spatially distributed scenarios through Continuous Time Markov Networks (CTMNs). Then, we assess the performance of such policies in high density (HD) IEEE 802.11ax scenarios by means of simulations. We show that always picking the widest channels available can be suboptimal in terms of individual throughput and fairness. Thus, more flexible policies like stochastic width selection are required. Besides, we show that policy learning and/or adaptation is required on a per WLAN basis.

Research seminar at the Rice Network Group (#1)

Published: November 12, 2018

Presentation about the research done by Sergio Barrachina at the Wireless Networking group (Universitat Pompeu Fabra).

Research seminar at the Rice Network Group (#2)

Published: February 25, 2019

Presentation of the WACA project: “Inferring the potential of multi-channel access in the 802.11ac/ax 5-GHz band (An experimental approach)”

Towards Energy Efficient LPWANs through Learning-based Multi-hop Routing

Published: April 15, 2019

Presentation of the paper entitled “Towards Energy Efficient LPWANs through Learning-based Multi-hop Routing”, available here.

Towards the implementation of 11ax features in Komondor

Published: June 21, 2019

Presentation of the Komondor simulator, where novel 11ax-based features are implemented. Particular emphasis was put on the Spatial Reuse (SR) part.

On the Performance of the Spatial Reuse Operation in IEEE 802.11ax WLANs

Published: October 28, 2019

Presentation of the paper entitled “On the Performance of the Spatial Reuse Operation in IEEE 802.11ax WLANs”, available here.

Stateless Reinforcement Learning for Multi-Agent Systems: the Case of Spectrum Allocation in Dynamic Channel Bonding WLANs

Published: July 01, 2021

Presentation of the paper entitled “Stateless Reinforcement Learning for Multi-Agent Systems: the Case of Spectrum Allocation in Dynamic Channel Bonding WLANs”, available here.

Teaching Assistant: Networks Laboratory (2016)

Undergraduate course, Universitat Pompeu Fabra, 2016

Course on practical networks concepts (routing, switching, etc.). Cisco devices are mostly used along the entire subject, which is practical in nature. More information here.

Teaching Assistant: Networks (2016-2020)

Undergraduate course, Universitat Pompeu Fabra, 2016

Introductory course on basic networks concepts, based on James F. Kurose and Keith W. Ross, “Computer Networking. A Top-down Approach”, Pearson/Addison Wesley. More information here.

Course Instructor: Networking fundamentals (2020 - currently)

Undergraduate course, Universitat Oberta de Catalunya (UOC), 2021

This course aims to offer students a general vision of the architecture of computer networks, as well as the specific role of these in the different phases of the data life cycle: generation, transmission, storage, and processing. More information here.