Disaggregated and open radio access network (O-RAN) architectures offer benefits such as enhanced interoperability, improved coordination between nodes, and cost reduction. However, they also introduce new security challenges related to open interfaces and distributed control mechanisms. This work focuses on analysing vulnerabilities of SCTP, one most widespread solutions in these interfaces, which facilitates communication with RAN Intelligent Controllers (RIC). The analysis addresses two specific attacks: denial of service and identity spoofing. Both have been implemented and experimentally validated on the FlexRIC platform within the O-RAN architecture framework, going beyond the predominantly theoretical approaches found in the literature. Based on these experiments, we critically evaluate various security solutions proposed for SCTP. While some of these solutions offer partial mitigation capabilities, they also present structural, operational, and compatibility limitations that affect their overall effectiveness. These findings underscore the need to adopt more efficient transport protocols, capable of natively integrating adequate security features for O-RAN environments.

Open Radio Access Network (O-RAN) fosters a new networking paradigm that supports flexible and open architectures, while enabling the functional disaggregation of traditional, monolithic, base stations. Specifically, the Lower-Layer Split (LLS) option 7.2x divides the PHY layer into Low-PHY at Open -Radio Unit (O-RU) and High-PHY at Open -Distributed Unit (O-DU), leveraging the so-called open fronthaul network, which imposes stringent latency requirements. In this work, we introduce and thoroughly examine the time window relationships that define the latency budget allocated to the open fronthaul network. Additionally, we propose a novel methodology to analyze the delay experienced by a realistic traffic pattern over a spine-leaf topology, accounting for various O-DU locations and site pools. To address the increased traffic load introduced by the fronthaul, we present a theoretical model to characterize the average delay across different priority levels when open fronthaul traffic coexists with flows from other Radio Access Technologies (RATs). This model is then validated and broadened through ns-3 simulations. Our findings show the applicability of the proposed methodology, which could be exploited by network operators in the planning phase, evincing its suitability to obtain benchmark delay values, offering a reliable tool for performance evaluation in open fronthaul networks.

5G and beyond technologies are designed to convey multiple QoS requirements coming from highly heterogeneous services. In this regard, 5G extends the QoS definition of previous technologies. In order to fulfill the requirements of new services, it is necessary to develop resource management solutions that effectively and efficiently translate them to usage of resources. Therefore, MAC schedulers are to be designed to accommodate the demands of emerging applications with stringent QoS requirements, such as XR. In this work, we introduce a Lyapunov-based MAC scheduler designed to appropriately tackle coexisting heterogeneous QoS flows. The proposed approach allows the implementation of policies that explicitly consider the QoS requirements, as well as an efficient use of allocated resources. The results obtained through extensive experiments over the ns-3 5G-LENA simulator demonstrate that our scheduler guarantees the required time-average bit rate for every QoS flow at every time window, while ensuring the stability of traffic queues for all users.

The Open-Fronthaul (O-FH) is a Time Sensitive Network (TSN) segment within the Open-RAN (O-RAN) architecture, where the legacy base station is disaggregated following the 7.2x functional split. One of the strategic objectives sought by network operators is to foster the centralization of the Open - Distributed Unit (O-DU), to serve multiple remote sites. Hence, ensuring an accurately modeling of the fronthaul performance becomes critical, due to its stringent timing requirements. In this work, we propose a novel modeling methodology, based on Generalized Jackson Networks (GJN), to derive key performance metrics such as waiting time and utilization. Additionally, we apply Kingman’s approximation to evaluate delay percentiles under high traffic load conditions. This analytical method allows for fast and scalable performance evaluation, avoiding the need for extensive packet-level simulations, which become computationally prohibitive as traffic load steadily increases. Our results evince that under sensible operating situations, the proposed approach yields rather precise results, providing an upper performance bound.

XR applications place increasing pressure on mobile networks to meet their stringent Quality of Service (QoS) demands. In particular, XR services require high throughput and low latency, with traffic patterns that differ greatly from traditional applications. To address these challenges, we propose a novel Medium Access Control (MAC) scheduling solution that takes into account the segmentation of XR media units into Packet Data Units (PDUs), referred to as PDU sets in 5G-Advanced networks. These PDU sets correspond to the core traffic unit for XR services and must be delivered according to their specific QoS requirements, which are dynamically established in real-time by the XR application. The proposed scheduling solution leverages Lyapunov drift-plus-penalty optimization to jointly optimize resource allocation and stabilize traffic queues while ensuring the timely delivery of PDU sets. Our solution is implemented within the ns-3 5G-LENA framework, and the paper features a comparative analysis through extensive simulations, evaluating the performance of our proposal against existing MAC scheduling algorithms. Results evince that the proposed scheduler enhances resource utilization, ensures QoS compliance, and improves network performance.

During the last years we have witnessed a growing trend towards the deployment of disaggregated Radio Access Network (RAN) networks. In this context, the Open-RAN (ORAN) architecture is one of the most relevant approaches for 5G/6G networks, and it is believed to be a key element of forthcoming deployments. The performance of the so called Open - Fronthaul ($\mathrm{O}-\text{FH}$) segment is of the utmost importance to ensure an appropriate overall system performance. In this sense, the overall delay of the communication between nodes within the O-RAN fronthaul needs to be kept at very low values, to fulfill the requirements of the corresponding technologies. In this paper we propose exploiting queuing theory to model the O-FH performance, including a realistic traffic characterization. In particular, we present a theoretical framework based on Open Jackson Networks to model the one-way end-to-end delay, and we compare it with a that obtained by a realistic simulation setup. The results show that the theoretical model provides a reasonably accurate behavior under certain conditions, setting in all cases a tight upper bound for the end-to-end delay, which we identify as a key performance indicator.

Disaggregated and open radio access network architectures offer benefits such as enhanced interoperability, improved coordination between nodes, and cost reduction; however, they also introduce new security challenges related to open interfaces and distributed control mechanisms. This work focuses on analyzing vulnerabilities in one of the protocols used in these interfaces—SCTP—which facilitates communication with Radio Intelligent Controllers (RIC). The analysis centers on two specific attacks: denial of service and identity spoofing. Both attacks have been implemented and experimentally validated on the FlexRIC platform within the O-RAN architecture framework, contrasting with the predominantly theoretical approaches found in the literature. Based on these experiments, a critical evaluation of various security solutions proposed for SCTP is conducted. While some of these solutions offer partial mitigation capabilities, they present structural, operational, and compatibility limitations that affect their overall effectiveness. These findings underscore the need to adopt more modern and efficient transport protocols capable of natively integrating adequate security functions for O-RAN environments.

In 5th Generation (5G) virtualized Radio Access Networks (vRAN), where the protocol stack is split across three different elements (Radio Unit (RU), Distributed Unit (DU), and Centralized Unit (CU)), and data is transmitted across the transport network (fronthaul (FH) and midhaul) between these units, the capacity of the fronthaul pipe can become a limiting factor for packet transmission. To address this challenge, state-of-the-art approaches have introduced several fronthaul control methods, designed to limit the sending rate, to ensure that it does not exceed the available capacity. However, it is important to avoid potential conflicts between the decisions of such fronthaul control methods and those of the Medium Access Control (MAC) scheduling schemes, as they might impact one another. In this context, we provide a thorough analysis of the trade-off between the fronthaul and the air interface limitations and we propose a new FH Control method to limit packet transmissions without altering the decisions made by the MAC scheduler. An extensive simulation campaign in a 3GPP defined scenario with Virtual Reality (VR) and Cloud Gaming (CG) services is conducted, for air-limited and air/fronthaul capacity-limited conditions. The results demonstrate that the proposed fronthaul control method efficiently coordinates the MAC scheduler decisions with the constraints imposed by the fronthaul capacity.

Robust and efficient communication frameworks have become essential for the advancement of manufacturing and industrial processes in the era of Industry 4.0. This paper presents a comprehensive performance analysis of Eclipse Zenoh, a promising solution for the Industrial Internet of Things (IIoT). The analysis is conducted using a real testbed built with Raspberry Pi devices, comparing Eclipse Zenoh’s performance against the widely used Message Queuing Telemetry Transport (MQTT) protocol. The study assesses Eclipse Zenoh’s capabilities in terms of latency, as well as its reliability and congestion control mechanisms over various network topologies, using both Transmission Control Protocol (TCP) and User Datagram Protocol (UDP). The results indicate that Eclipse Zenoh offers significant advantages in specific scenarios, making it a compelling choice for IIoT applications. Additionally, this paper contributes to a deeper understanding of Eclipse Zenoh’s underlying principles and its communication capabilities, positioning it as a versatile and efficient solution for modern industrial environments. • Study of Eclipse Zenoh’s underlying principles. • Latency comparative analysis of Eclipse Zenoh and MQTT. • Evaluation of Eclipse Zenoh’s reliability and congestion control mechanisms over TCP and UDP.

We jointly consider network slicing and functional split for 5G/6G Radio Access Network (RAN). Exploiting virtu-alization techniques, virtual Radio Access Network (vRAN) is an architectural shift that moves some of the functions that were traditionally performed by the base station to centralized nodes, deployed at cloud-based resources. By appropriately selecting the location of these nodes, they can effectively coordinate a number of radio access elements, thus bringing potential gains, for instance, in terms of interference reduction. One pivotal decision for vRAN operation is how to split the functions between these central elements and the corresponding distributed units. Deploying more functions at the cloud could potentially bring more benefits, due to the tighter cooperation between access elements. On the other hand, higher centralization poses more requirements, in terms of computational resources at the nodes where these functions are deployed. Along with the virtualization, RAN slicing enables the deployment of independent service verticals over the same physical infrastructure, and this could greatly benefit from the coordination achieved by exploiting the vRAN features. In this paper we propose a vRAN model to jointly consider functional split and RAN slicing, and we establish the corresponding configuration, exploiting Lyapunov's Theory to tackle the underlying problem. The results show that, in highly heterogeneous networks, the dynamic configuration of the functional split can reach the same performance of fully centralized networks, with substantially fewer computation resources.

The advent of wireless technologies has led to the development of novel services for end-users, with stringent needs and requirements. High availability, very high throughput, low latency, and reliability are all of them crucial performance parameters. To address these demands, emerging technologies, such as non-terrestrial networks or millimeter wave (mmWave), are being included in 5G and Beyond 5G (B5G) specifications. mmWave enables massive data transmissions, at the expense of a more hostile propagation, typical for high frequency bands. Consequently, the inherent instability of the physical channel significantly affects the upper layers of the protocol stack, resulting in congestion and data losses, which might strongly hinder the overall communication performance. These challenges can be addressed not only at the link layer, but at any affected layer. QUIC is a new transport protocol designed to reduce communications latency in many ways. Among other features, it enables the use of multiple streams to effectively manage data flows sent through its underlying UDP socket. This paper introduces an implementation of priority-based stream schedulers along with the design of a flexible interface. Exploiting the proposed approach, applications are able to set the required scheduling scheme, as well as the stream priorities. The feasibility of the proposed approach is validated through an extensive experiment campaign, which combines Docker containers, the ns-3 simulator and the Mahimahi framework, which is exploited to introduce realistic mmWave channel traces. The results evince that an appropriate stream scheduler can indeed yield lower delays for time-sensitive applications by up to 36% under unreliable conditions.

We analyze the performance of QUIC over Non-Terrestrial-Networks (NTN). The presence of this transport protocol has strongly increased since it was originally proposed, but its behavior over wireless networks is still an open question. We focus on NTN, which will play a key role in forthcoming cellular systems, and whose underlying connectivity exhibits a highly variable behavior. We show that using multiple streams, which is one of the most relevant advantages of QUIC, yields performance improvements. We then propose a delay-based scheduler, based on dynamic queuing control, and we compare its behavior with that exhibited by legacy solutions. We carry out an extensive experiment campaign exploiting a novel methodology that combines virtualization techniques, real QUIC implementation, and ns-3 to model NTN links. The results show that the proposed scheduling policies fairly distribute the delay between streams, without jeopardizing the throughput, even under very high load situations.

We study the performance exhibited by the transport protocols, Transport Control Protocol (TCP) and QUIC, over realistic satellite networks. We propose a novel methodology, which combines real implementation (exploiting virtualization techniques) and simulation, to carry out systematic and repetitive experiments. We modify the default operation of the ns-3 framework and we integrate the dynamism that characterizes satellite communication links, particularly Low Earth Orbit (LEO). We carry out a thorough assessment over different setups, changing the operating frequency band and packet buffer lengths. In addition, we ascertain the impact of using the multi-streaming feature that QUIC integrates. The results show that QUIC yields lower delays than TCP, although it might suffer from higher jitter in particular setups. In addition, the results evince that using multiple streams in QUIC does not yield a relevant gain for the default Round-Robin (RR) scheduler. We propose more appropriate scheduling strategies, which are able to yield better performances with unbalanced traffic. Even if the behavior of transport protocols over non-terrestrial-networks might not be always appropriate, the obtained results evince that QUIC can definitively bring benefits when compared to TCP. Furthermore, we have shown that optimal scheduling policies yields a fairer performance when using multiple flows, having unbalanced traffic loads.

Low Earth Orbit (LEO) satellite constellations have been identified for new massive access networks, as a complement to traditional cellular ones, due to their native ubiquity. Despite being a feasible alternative, such networks still raise questions on their performance, in particular regarding the delay and queuing management under realistic channels. In this work, we study the queuing delay of a single satellite-to-ground link, considering a Land Mobile Satellite (LMS) channel in LEO with finite buffer lengths. We analyze the trade-off between delay and packet loss probability, using a novel model based on Markov chains, which we assess and extend with an extensive analysis carried out by means of system level simulation. The developed tools capture with accuracy the queuing delay statistical behavior in the S and Ka frequency bands, where LEO communications are planned to be deployed. Our results show that we can use short buffers to ensure less than 5-10% packet loss, with tolerable delays in such bands.

It is broadly accepted that network function virtualization will play a key role to meet the stringent and heterogeneous requirements of 5G networks. Although fully centralized approaches were initially proposed, they may impose unfeasible requirements over fronthaul links. Consequently, flexible functional split solutions are being fostered, where a central controller adapts the centralization level to current circumstances. In spite of the growing interest in this type of solutions, most of existing works focus on real implementation, while little attention has been paid so far to performance modeling. In this paper we propose a Markov Chain based controller model, which boils down to a Quasi-Birth-Death process. Under reasonable assumptions, this model provides expected values of buffer occupancy and the time frames would spend in the controller. In this sense, it aims to be a tool to support the allocation of computational resources of the virtualized entities. We validate the proposed model by comparing its results with those obtained by simulation, evincing an almost perfect match between both approaches.

We study Flexible Functional Split functionality of 5G vRAN controllers in 5G networks. We propose an innovative model, based on a Markov Chain, which can be used to characterize their performance. We consider both infinite and finite-buffer controllers. In the former, frames would not be lost (provided the system works in a stable regime), and we thus focus on the time frames stay at the controller. For the finite-buffer controller, there might be losses, and we analyze the trade-off between time at the controller (which might hinder the stringent delay requirements of 5G services), and loss probability. Matrix-geometric techniques are used to resolve the corresponding Quasi-Birth-Death process. The validity of the proposed model is assessed by means of an extensive experiment campaign carried out over an ad-hoc event-driven simulator, which is also used to broaden the analysis, considering different service rate distributions, as well as the variability of the studied performance indicators. The results show that the proposed model can be effectively exploited to tackle the dimensioning of these systems, as it sheds light on how their configuration impacts the expected delay and loss rate.

This work tackles the problem faced by network/infrastructure providers of jointly selecting routing and functional split level to satisfy requests from virtual mobile network operators (vMNOs). We build a novel system model that brings together all the involved elements and features, embracing split levels defined by the 3GPP and packet switch fronthaul network. To our best knowledge, this is the first work that provides a solution for multiple vMNO requests considering the two aforementioned sub-problems (i.e., split selection and routing). We use the model defined to formulate an optimization problem, which is characterized by the exponential size of its search space. We propose two heuristic approaches to address this problem: (1) a greedy scheme, and (2) an evolutionary algorithm, which is also improved with a specialized initialization. We conduct extensive experiments to assess the performance and behavior of the proposed methods, over varying network instances. When possible, we also perform comparisons with respect to the optimal solution and a well-known commercial solver. Our results indicate that the proposed techniques represent appropriate trade-offs between solution quality and execution time, and can serve complementary goals: the quality of the results yielded by our evolutionary method are better, but at the cost of longer execution times; in contrast, our greedy algorithm offers a reasonably appropriate performance, with an execution time that is notably lower. Our experiments show that it is possible to produce near-optimal results to the above complex problem through computationally efficient algorithmic solutions.

This paper studies how learning techniques can be used by the congestion control algorithms employed by transport protocols over 5G wireless channels, in particular millimeter waves. We show how metrics measured at the transport layer might be valuable to ascertain the congestion level. In situations characterized by a high correlation between such parameters and the actual congestion, it is observed that the performance of unsupervised learning methods is comparable to supervised learning approaches. Exploiting the ns-3 platform to perform an in-depth, realistic assessment, allows us to study the impact of various layers of the protocol stack. We also consider different scheduling policies to discriminate whether the allocation of radio resources impacts the performance of the proposed scheme.

Smart cities solutions are often monolithically implemented, from sensors data handling through the provided services. The same challenges are regularly faced by different developers, for every new solution in a new city. Expertise and know-how can be reused and the effort shared. In this article, we present the methodologies to minimize the efforts of implementing new smart city solutions and maximizing the sharing of components. The final target is to have a live technical community of smart city application developers. The results of this activity come from the implementation of 35 city services in 27 cities between Europe and South Korea. To share efforts, we encourage developers to devise applications using a modular approach. Single-function components that are reusable by other city services are packaged and published as standalone components, named atomic services. We identify 15 atomic services addressing smart city challenges in data analytics, data evaluation, data integration, data validation, and visualization. Thirty-eight instances of the atomic services are already operational in several smart city services. We detail in this article, as atomic service examples, some data predictor components. Furthermore, we describe real-world atomic services usage in the scenarios of Santander and three Danish cities. The resulting atomic services also generate a side market for smart city solutions, allowing expertise and know-how to be reused by different stakeholders.

Network densification over space and spectrum is expected to be key to enabling the requirements of next generation mobile systems. The pitfall is that radio resource allocation becomes substantially more complex. In this paper, we propose LaSR, a practical multi-connectivity scheduler for OFDMA-based multi-RAT systems. LaSR makes optimal discrete control actions by solving a sequence of simple optimization problems that do not require prior information of traffic patterns. In marked contrast to previous work, the flexibility of our approach allows us to construct scheduling policies that achieve a good balance between system cost and utility satisfaction, while jointly operate across heterogeneous RATs, accommodate real-system requirements, and guarantee system stability. Examples of system requirements considered in this paper include (but are not limited to): constraints on how scheduling data can be encoded onto signaling protocols (e.g., LTE's DCI), delays when turning on/off radio units, or on/off cycles when using unlicensed spectrum. We evaluate our scheduler via a thorough simulation campaign in a variety of scenarios with e.g., mobile users, RATs using unlicensed spectrum (using a duty cycle access mechanism), imperfect queue state information, and constrained signaling protocol.

In this paper we propose a novel model for the uplink in heterogeneous cellular networks. Opposed to previous works, we accurately account for the mutual interference caused by other users' connections, and we pose an optimization problem that can be straightforwardly solved to establish the minimum required transmission power that satisfies the minimum Signal-to-Interference-plus-Noise Ratio (SINR) constraint. We assess the validity of the proposed approach by comparing the observed results with those obtained with a traditional closed-loop power control scheme. The main benefit of our solution is that it does not require any iteration to find the transmission power, while legacy approaches usually need a number of steps before finding it. Finally, we study the behavior of the uplink for different access selection strategies, and we compare the SINR and transmission power of open-loop and closed-loop power control solutions.

It is well known that network function virtualization will be a key enabler to meet the stringent requirements of 5G networks. However, fully centralized approaches, such as Cloud Radio Access Network (C-RAN), might not be feasible, considering the particular needs of the fronthaul links and the large cost of implementing such architectural shift. In this sense, flexible functional split brings a practical solution, which trades off performance and practicability. In spite of the growing interest in flexible functional split, little attention has been paid to the interaction of split selection and scheduling. In this paper, we analyze joint strategies that minimize traffic delay. We compare the global optimum solution with partial optimizations, that can be more suitable in practical implementations, using different scenarios. According to our results, fixed scheduling behaves alike the global optimum in heterogeneous RAN scenarios. Furthermore, we observe that it is usually better to optimize the split degree for fixed scheduling setups, than deciding a scheduling policy for a particular split configuration.

Smart cities are becoming a vibrant application domain for a number of science fields. As such, service providers and stakeholders are beginning to integrate co-creation aspects into current implementations to shape the future smart city solutions. In this context, holistic solutions are required to test such aspects in real city-scale Internet of Things (IoT) deployments, considering the complex city ecosystems. In this paper, we discuss OrganiCity's implementation of an experimentation-as-a-service (EaaS) framework, presenting a toolset that allows developing, deploying, and evaluating smart city solutions in a one-stop shop manner. This is the first time such an integrated toolset is offered in the context of a large-scale IoT infrastructure, which spans across multiple European cities. We discuss the design and implementation of the toolset, presenting our view on what EaaS should provide, and how it is implemented. We present initial feedback from 25 experimenter teams that have utilized this toolset in the OrganiCity project, along with a discussion on two detailed actual use cases to validate our approach. Learnings from all experiments are discussed as well as architectural considerations for platform scaling. Our feedback from experimenters indicates that EaaS is a viable and useful approach.

In this paper we propose a modification of the LTE Radio Link Control procedures so as to reduce the number of retransmissions that need to be carried out when a video streaming service is being transmitted from the end-user terminal to the base station. We exploit the fact that, in this case, some of the frames of the video flow might be lost without a strong impact on the perceived quality of experience. We carry out an extensive simulation study over the ns-3 framework, comparing the performance of the proposed scheme with that exhibited by the legacy operation of the RLC. The results yield that our proposal is able to significantly reduce the number of retransmissions, without a strong impact on the Mean Opinion Score.

This work presents a novel model for multi-hop networks which aims to include electro-magnetic exposure metrics within the routing paradigm. Given the need to include new metrics in the routing decision making, as a prelude to the protocols definition, it is deemed necessary the definition of novel network models and adequate algorithms so that they can be afterwards utilized to assess the performance of the routing protocols. In particular, this work proposes a network model to include the electro-magnetic exposure within the routing costs; besides, an algorithm (Cycle Canceling Algorithm) has been identified that is able to effectively solve the problem resulting from the model. Furthermore, the behavior of the proposed algorithm is compared with other which considers a different metric, so as to corroborate its operation and to provide information on how to tweak its configuration parameters.