We present PTLM (Passive TCP Latency Monitor), a lightweight system for estimating TCP round-trip times (RTT) by passively observing ongoing flows. Unlike active probing approaches such as ICMP ping, PTLM operates entirely in-band by extracting TCP timestamp values (TSval/TSecr) from segments observed at intermediate nodes. This enables accurate latency estimation without injecting probe traffic or modifying endpoints. PTLM computes RTT samples in both directions and aggregates them into an end-to-end view of latency as experienced by applications. Experimental validation in a controlled testbed confirms that PTLM detects RTT variations in real time while maintaining negligible overhead. These results demonstrate PTLM as a practical tool for researchers and operators requiring transparent, TCP-aware latency monitoring.

Industry 5.0 emphasizes human-centric manufacturing, where the operator needs to inform system design. While Operator Digital Twins monitor operator states through biometric data, existing approaches have not exploited this information to adapt industrial Human-Machine Interfaces (HMIs), which remain predominantly static and uniform. This paper proposes an architecture that extends Human Digital Twin systems with LLM-driven personalization for web-based HMIs. The framework collects operator-specific data through a mobile application integrating Health Connect and manual inputs. A Large Language Model interprets operator profiles containing biometric signals, permanent characteristics, and preferences, generating customized CSS stylesheets and configuration parameters that adapt visual properties and interaction modalities while preserving safety-critical elements. The architecture’s applicability is illustrated through diverse conceptual scenarios, such as visual impairments, protective equipment usage, elevated stress states, and ergonomic preferences. This demonstrates how a consistent operator profile format could drive varied interface adaptations to meet different operator needs.

Autonomous driving remains a challenging task, particularly due to safety concerns. Modern vehicles are typically equipped with expensive sensors such as LiDAR, cameras, and radars to reduce the risk of accidents. However, these sensors face inherent limitations: their field of view and line of sight can be obstructed by other vehicles, thereby reducing situational awareness. In this context, vehicle-to-vehicle communication plays a crucial role, as it enables cars to share information and remain aware of each other even when sensors are occluded. One way to achieve this is through the use of Cooperative Awareness Messages (CAMs).In this paper, we investigate the use of CAM data for vehicle trajectory prediction. Specifically, we design and train a neural network, Cooperative Awareness Message-based Graph Neural Network (CAMNet), on a widely used motion forecasting dataset. We then evaluate the model on a second dataset that we created from scratch using Cooperative Awareness Messages, in order to assess whether this type of data can be effectively exploited. Our approach demonstrates promising results, showing that CAMs can indeed support vehicle trajectory prediction. At the same time, we discuss several limitations of the approach, which highlight opportunities for future research.

End-to-end latency is a critical metric in interactive and real-time systems, where even short delays can undermine usability, situational awareness, and trust. While most studies focus on network transmission delays, this overlooks other significant sources of latency, including sensor acquisition, processing, and especially visualization. Rendering pipelines are heavily influenced by hardware, visualization strategies, and data complexity, and in visualization-rich domains such as smart cities, these factors can add considerable overhead. Ignoring them leads to overly optimistic performance assessments and missed opportunities for optimization.In this work, we study the last mile of end-to-end latency, explicitly incorporating the visualization stage and bridging the gap between network-level metrics and user-perceived responsiveness. We introduce the Unreal Smart Cities Visualizer (USCV), a framework we have built to support precise latency assessment in realistic, data-intensive urban scenarios. Our contributions include highlighting the limits of network-centric evaluation, presenting a visualization-aware methodology, and demonstrating USCV as a tool for accurate end-to-end latency measurement.Our results show that visualization delays, particularly in latency-critical environments, are not negligible and cannot be underestimated.

This paper presents the Smart City Architecture (SCA), a middleware system built upon the MQTT (Message Queuing Telemetry Transport) protocol and developed within the MASA (Modena Automotive Smart Area) initiative. SCA enables intelligent urban applications by facilitating seamless and scalable communication among heterogeneous entities, including assets, services, and observers. Its structured, topic-based messaging layer supports efficient telemetry exchange, event-driven processing, and dynamic service interaction. The capabilities of SCA are exemplified through two real-world services—Vulnerable Road User (VRU) and GeoPerception—which provide real-time risk detection and localized situational awareness in smart city scenarios.

Efficient energy provisioning is a fundamental requirement for modern transportation systems, making refueling path optimization a critical challenge. Existing solutions often focus either on inter-vehicle communication or intra-vehicle monitoring, leveraging Intelligent Transportation Systems, Digital Twins, and Software-Defined Internet of Vehicles with Cloud/Fog/Edge infrastructures. However, integrated frameworks that adapt dynamically to driver mobility patterns are still underdeveloped. Building on our previous PIENO framework, we present RI-PIENO (Revised and Improved Petrol-filling Itinerary Estimation aNd Optimization), a system that combines intra-vehicle sensor data with external geospatial and fuel price information, processed via IoT-enabled Cloud/Fog services. RI-PIENO models refueling as a dynamic, time-evolving directed acyclic graph that reflects both habitual daily trips and real-time vehicular inputs, transforming the system from a static recommendation tool into a continuously adaptive decision engine. We validate RI-PIENO in a daily-commute use case through realistic multi-driver, multi-week simulations, showing that it achieves significant cost savings and more efficient routing compared to previous approaches. The framework is designed to leverage emerging roadside infrastructure and V2X communication, supporting scalable deployment within next-generation IoT and vehicular networking ecosystems.

The complete workflow of the RI-PIENO framework is presented, a system for refueling itinerary optimization that extends the original PIENO design. While prior work introduced the conceptual modules of RI-PIENO, their operational pipeline was not described in detail. This study makes the workflow explicit, covering the end-to-end process from CAN Bus data acquisition and stop detection to the construction of daily trip graphs, refueling optimization, and mileage prediction. By clarifying the sequence of operations, the contribution provides a reproducible and extensible foundation for future research and development.

This paper introduces a low-cost and reproducible framework for measuring glass-to-glass (G2G) latency in real-time video systems. Unlike existing solutions, which are often proprietary, expensive, or poorly documented, our approach combines a photodiode, a microcontroller, and lightweight calibration routines to achieve accurate end-to-end latency measurements. The framework is validated across heterogeneous devices, revealing the impact of hardware tiers and video codecs (e.g., H.264 vs. Motion JPEG) on responsiveness. Beyond smartphones, we demonstrate adaptability to complex pipelines such as remote driving and wearable devices, where latency directly affects safety and user experience. Released as an open-source tool, the framework fills a methodological gap in latency research and offers practical guidelines for optimizing multimedia pipelines in domains including virtual reality, telemedicine, and autonomous mobility.

Latency monitoring is a fundamental requirement for TCP-based services in scenarios where responsiveness must meet strict deadlines, typically below 100 ms. This is particularly relevant for emerging applications such as remote driving in smart mobility testbeds and remote operation of industrial machinery in Industry 5.0 environments. Traditional active monitoring techniques, which rely on probe traffic (e.g., ICMP ping), introduce additional load and may fail to capture the true latency experienced by the target service.In this paper, we present PTLM (Passive TCP Latency Monitor), a system that enables non-intrusive and passive monitoring of TCP latency by directly observing application flows at intermediate nodes along the client–server path. PTLM leverages the principles of passive latency estimation introduced in previous work (e.g., pping) but extends them with a practical and deployable solution specifically designed for enterprise networks and experimental living labs.We report the results of an extensive experimental campaign including feasibility, performance, and reliability tests. In particular, experiments conducted in the MASA (Modena Automotive Smart Area) living lab demonstrate that PTLM can successfully detect latency variations that traditional ping-based methods fail to observe. The results validate PTLM as an effective monitoring solution for latency-critical applications, with direct relevance to enterprise deployments (IGNITE 5.0 project) and experimental testbeds supporting autonomous driving and other time-sensitive services.

In recent years, Intelligent Transport Systems (ITS) have gained significant attention, driven by the European Directive 2010/40/EU, aiming to enhance vehicle safety, traffic efficiency, and overall transport experiences. A cornerstone of ITS is Vehicular Ad-hoc Networks, which enable rapid communication through Dedicated Short-Range Communication for Vehicle-to-Vehicle and Vehicle-to-Infrastructure interactions. Standardized messages such as Cooperative Awareness Messages and Decentralized Environmental Notification Messages have become essential for collision avoidance and other safety-critical applications. However, challenges such as network congestion highlight the importance of Decentralized Congestion Control to ensure reliable communication.This study provides insights to optimize network performance by investigating the mechanisms by which Decentralized Congestion Control tries to mitigate congestion, namely, access categories, transmission power, and modulation coding schemes. The assessment is performed by measuring network performance and QoS under varying conditions through the tool iPerf on a real IEEE 802.11p-based testbed. The results indicate that prioritization classes and transmission power improve performance as expected, while modulation coding schemes can affect data rate in a less intuitive way.

The dAIEDGE Network of Excellence (NoE) seeks to strengthen and support the development of a dynamic European cutting-edge Artificial intelligence (AI) ecosystem under the umbrella of the European Lighthouse for AI, and to sustain the development of advanced AI. dAIEDGE fosters the exchange of ideas, concepts, and trends on cutting-edge next generation AI, creating links between ecosystem actors to help both the European Commission (EC) and the European Union (EU) and the peripheral AI constituency identify strategies for future developments in Europe. Our main objective is to advance Europe’s innovation and technology base by developing a comprehensive policy and governance approach to AI in order for the EU to become a world leader in innovation in the data economy and its applications.

In this work, we investigate the performance and suitability of various mobile frameworks for critical smart city applications. With the increasing reliance on mobile apps for urban services, understanding the capabilities and assessing the limitations of different development platforms is crucial. We evaluate Android OS, Apple iOS, and cross-platform solutions like Flutter, focusing on their ability to deliver real-time information efficiently in mobile applications tailored for smart city environments. In our work, we look at the content delivery latency, scalability, cross-platform capabilities, and developer productivity. We also assess the frameworks' integration with existing smart city infrastructure and their handling of distributed location-dependent data. The study compares native implementations using platform-specific SDKs against cross-platform solutions, with particular attention to map-based applications utilizing both native maps and third-party services like Mapbox. We have tested the platforms within the Modena Automotive Smart Area (MASA), a real-world testbed for innovative mobility solutions in Modena, Italy. This environment provided a realistic setting to evaluate the frameworks' performance in critical smart city scenarios. The outcomes of our work offer insights into the relative strengths and limitations of each mobile framework, considering both technical performance and development efficiency. In this work, we aim to guide developers and city planners in selecting the most appropriate mobile framework for smart city applications, balancing performance requirements with development resources and cross-platform needs.

The Modena Automotive Smart Area (MASA) is a cutting-edge testing environment featuring a variety of dynamic physical assets, including smart cameras, roadside units, and connected vehicles. These assets support numerous digital applications, ranging from real-time safety systems to mobility intelligence and 3D visualization of the MASA area. However, the complexity of the physical environment and the diverse needs of these digital applications necessitate a decoupling strategy to ensure efficient operation. This paper presents the design of the MASA Digital Twin, detailing its hierarchical structure, the associated design challenges, and the technological approaches used in its implementation. The MASA Digital Twin serves as a crucial tool for managing the interplay between physical and digital elements, enabling a more structured and adaptable approach to connected mobility and smart city applications.

The deployment of cooperative-intelligent transport systems (C-ITS) has started, and standardization and research activities are moving forward to improve road safety and vehicular efficiency. An aspect that is still felt as a limitation by the research groups active in the field, is the difficulty to validate the solutions with real hardware and software, because of the huge investments that are needed when multiple equipped vehicles need to be considered. In this work, we present a platform with low-cost hardware based on a Raspberry Pi and a Wi-Fi module transmitting at 5.9 GHz, and on the open-source software Open Stack for Car (OScar), which is compliant with the ETSI C-ITS standards. With a limited cost in the order of 200 €, the platform realizes a device which is standard compliant and can be used as either on-board unit (OBU) or road side unit (RSU). The limited cost makes the testbed scalable to several units with limited budget and the limited size makes it also deployable on mini-cars to test advanced connected and autonomous vehicle (CAV) networks and applications. Our tests demonstrate its interoperability with other devices, compliance in terms of power spectrum, and a range of a few hundred meters in line-of-sight (LOS) conditions using the standard settings of ITS-G5.

In the context of Intelligent Transportation Systems, a Vehicular Ad-Hoc Network provides communication among nearby vehicles and roadside infrastructure. Commercial devices enabling this type of communication via the IEEE 802.11p standard are expensive and proprietary, limiting research and independent field testing. Furthermore, as the industry is their target client, they integrate features like metal waterproof en-closures or mounting brackets, which often result in relatively cumbersome devices unable to accommodate use by vulnerable road users with limited space and weight-bearing capabilities. Aiming to address these concerns, this paper presents a low-cost and open-source device assembled with off-the-shelf components, which we named Open DSRC Unit or ODU in short. The design minimizes the steps required to implement the unit while maintaining a degree of flexibility for potential extension with future upgrades. As a result, the device can act as both a RoadSide Unit and an On-Board Unit, leaving open the possibility of implementing custom messages and acting with custom roles.

Enhancing the safety of Vulnerable Road Users (VRUs) poses a significant research challenge in the context of connected mobility and a plethora of technological opportunities trying to balance efficiency and widespread applicability. This paper presents a VRUs’ safety application focused on applying 5G Multi-Access Edge Computing (MEC), commercial mobile devices, public cellular networks, and data fusion between vehicle positioning and city camera infrastructure. The application showcases the designed system and its experimental evaluation in the Modena Automotive Smart Area (MASA) through an experimental 5G MEC infrastructure to build a secure and efficient connected mobility environment.

The main objective of connected vehicles is to signif-icantly improve safety for travel participants and nearby people. Cooperative Driving Automation denotes the set of autonomous applications requiring cooperation among connected vehicles, including those with driving automation features engaged. As the operational purpose of the cooperation depends on the application class and the level of driving automation, it follows that the communication strategies and, therefore, the design principles of the human-machine interfaces of participating vehicles must change as well. However, the literature is missing a standardized and coherent strategy for the design and implementation of these interfaces, which may have undesirable impacts on the risk reduction profile of cooperative applications. This paper wants to be a first step in the definition of suitable design principles for such interfaces. We contribute an overview of related solutions providing a selection of relevant works, and we synthesize a set of fundamental human-machine interface design principles for safety - related cooperative applications, hypothesizing an inverse relationship between the level of driving automation and the need for active approaches to maximise the safety of connected vehicles and nearby road users.

The network infrastructure is a key factor for Intelligent Transportation Systems (ITS). Only reliable networking support can enable the low latency required by ITS for safety-related applications, where effectiveness, reliability, and timeliness play crucial roles. These characteristics are required to reach autonomous driving and, tailored for a living lab, are required to test it and design novel applications for connected vehicles and, generally speaking, enhance road safety. This paper introduces a test campaign performed to stress the Modena Automotive Smart Area (MASA) backbone to efficiently evaluate the performance of the network infrastructure before starting the deployment of ITS services, including the installation of smart cameras and Road-Side Units (RSUs). The suite of tests has been designed to accommodate the automotive requirements, with the goal of evaluating the network latency in uncongested and congested situations, including the presence of QoS requirements. The results show that the MASA network is suitable for safety-related applications, introducing less than 100ms of induced latency in severe congested events for all the tested spots. This result is achievable thanks to the backbone characteristics and the partnership with the municipality that shares the physical network with the university, avoiding IST black boxes.

Cooperative awareness messages (CAM) are a family standardized by ETSI to distribute relevant information to all the nodes in vehicle coverage, such as time, position, speed, direction, etc. The parameters needed to trigger these messages, as well as the information contained in the messages themself, can be obtained with a GPS receiver. Our paper aims to increase the efficiency of CAM generation and dissemination in a less-is-more style, considering different GPS devices of different qualities. We achieve this goal by comparing the effectiveness of two GPS, belonging to two different market segments, with an order of magnitude of a price gap between them. We compared them in two different scenarios, similar in layout and traffic behavior but different in terms of GPS coverage conditions.Field trials with DSRC IEEE 802.11p have been carried out in an urban environment where different GPS coverage conditions widely emerge, with the possible presence of large buildings that emphasize all the GPS challenges: reducing the number of visible GPS satellites, introducing multi-path effects, fading, and reducing the signal strength.While having some notable differences in the two scenarios, we found the triggers’ distributions to be similar between both the receiver devices. Instead, the average time between consecutive awareness messages has been found to be significantly lower in the case of bad coverage compared with the open-sky scenario, something that may reflect the presence of unwanted messages triggered by the GPS errors rather than the real vehicle motion. Therefore, we designed a new CAM generation algorithm that also considers the GPS error to reduce the messages transmitted on the radio medium.

Since the definition of the bufferbloat phenomenon, several Linux kernel modules have been introduced in its TCP/IP stack, and there is a lack of experimental studies on their effects when coupled with WLAN technologies, in particular, IEEE 802.11n and IEEE 802.11ac. One essential algorithm introduced is named TCP Small Queues (TSQ) and has the role of limiting the number of packets that a TCP socket can enqueue in the stack, waiting for the physical layer to send the packets before enqueueing extra data. A second significant TCP algorithm is named TCP Pacing (TP) and regulates the pace used by the socket to enqueue packets in the stack, regulating the formation of bursts of data. These mechanisms affect the frame aggregation logic on WLAN networks and compromise the throughput-latency tradeoff of all the TCP variants. This paper presents an experimental evaluation of these techniques investigating the wireless network performance of several TCP congestion control variants under the presence of different TSQ and TP policies, modeling also their interaction.

In this paper, we report and analyze results from a field test campaign aimed at assessing the real-world performance of IEEE 802.11p for safety-related applications. Regulator bodies in the EU and the US recommend the use of domestic-level transmission powers for general usage while granting the opportunity of employing higher powers for safety purposes. While the latter are generally expected to result in higher network performance, we want to quantitatively assess what they translate to in terms of metrics relevant from an application point of view, such as, goodput, round-trip times, jitter, and losses. These are studied and associated with conditions out of the network control at urban and suburban speeds, that is, in absence or in presence of different degrees of congestion, and in complete or partial line-of-sight. In general, we find evidence of an inverse correlation between the degree of congestion and the benefits granted by higher transmission powers. Up to the tested speed, IEEE 802.11p appears able to provide safety guarantees even at relatively long distances, as long as an appropriate transmission power is employed. At the same time, it must be acknowledged that higher power alone cannot overcome the significant dips in performance resulting from highly congested environments and non-line-of-sight scenarios.

This paper shows the inefficiency of TCP BBR in exploiting the Wi-Fi bandwidth. This limitation of BBR has been observed with both IEEE 802.1ln and IEEE 802.11ac, where the mechanism of frame aggregation is used to boost the throughput of data transmission. In the last years, many TCP variants have been introduced to limit the bufferbloat phenomena and bound the latency, through a reduction of the queue backlog injection rate. However, this mechanism impacts on the Wi-Fi frame aggregation logic, impeding TCP congestion controls to reach the full throughput potential of a Wi-Fi interface. While this problem can be solved with TCP CUBIC allowing the sender node to enqueue more packets, for TCP BBR the fix is not the same, as it has a customized pacing algorithm. With this contribution, we propose BBR+, a new BBR version that allows to fine tune the congestion control pace, achieving 6 times more throughput over IEEE 802.1ln channels and 16 times more throughout over IEEE 802.11ac channels, at the cost of an increased latency that is however always less than the latency obtainable with TCP CUBIC.

V2X technologies are based on heterogeneous and safety-related applications that rely on broadcast messages, which are typical in V2V communications, and to unicast messages, which are, instead, typical in V2I/I2V communications. To ease unicast communications from the infrastructure to the vehicle, like rescue operations, addressing the challenging routing aspect for VANETs, we designed an Infrastructured RSSI-based Opportunistic routiNg algorithm for Mobile Adhoc Networks (IRONMAN), also focusing on the energy consumption of the solution developed. IRONMAN takes opportunistic routing decisions based on the RSSI calculated by the Road-Side Units (RSUs), instead of the classical GPS-based solutions. Through a real testbed, we demonstrate that IRONMAN outperforms standard Linux-based routing solutions for ad-hoc networks, like BATMAN and HWMP, providing almost optimal goodput without adding any overhead related to the routing decisions.

In this article, we study the application-level performance of safety-related communications over IEEE 802.11p, presenting the first outcomes resulting from several short- and medium-range field tests. These have been performed with low-cost off-the-shelf equipment operating on the IEEE 801.11p PHY/MAC stack, with devices configured or modified, when necessary, with open-source software to ensure repeatability. In particular, this article discusses the relation that transmission power, antenna quality, distance, and different degrees of congestion, alone and combined, have on round-trip times, TCP Goodput, UDP Goodput, Jitter, and Datagrams or Packets lost. It also details an investigation on the hidden terminal problem, by presenting the results of field tests where destructive interference due to hidden terminals has been artificially introduced at the host premises. Finally, this article presents the metrics obtained by performing initial mobility tests in urban and suburban scenarios. The results are encouraging and attest that, with the appropriate transmission power, it is possible to provide satisfying safety guarantees under the tested conditions.

Since the definition of the bufferbloat phenomenon, several Linux kernel modules have been introduced in the TCP/IP stack. While these solutions have been widely studied over wired networks, there is a lack of experimental results involving WLAN technologies, in particular, IEEE 802.11n and IEEE 802.11ac. One important algorithm introduced is named TCP Small Queues (TSQ) and has the role of limiting the number of packets that a TCP socket can enqueue in the stack, waiting for the physical layer to deliver the packets before enqueueing extra data. This mechanism breaks the frame aggregation logic on WLAN and compromises the throughput-latency tradeoff of all the TCP variants. This paper presents an experimental evaluation of this problem investigating the network efficiency of several TCP congestion controls under the presence of different TSQ policies.

In this work, we focus on the well-known hidden terminal problem applied to the IEEE 802.11p context, from an infrastructure-centric point of view (I2V). The problem occurs in scenarios where two nodes are out of each other's range while being independently able to communicate with a third that, intuitively speaking, is positioned in the middle of the former two. If the two nodes transmit to the third at the same frequency and at the same time, though not exactly the same signal, the third would be unable to identify the two source signals and, therefore, would suffer from interference. Although the occurrence of this problem may be unlikely in I2V practice, certain applications, such as road safety, require the problem to be addressed anyhow. This article shows the outcomes of field trials conceived to experience first-hand the occurrence of the issue in IEEE 802.11p networks, experiment with different interference management techniques, and design or select the optimal approach to minimize interference. Results unequivocally attest that, in this context, an ad-hoc Time-Division Multiple Access (TDMA) approach provides the best guarantees in any condition. It is also shown how, on the other hand, the common method of using the Request To Send/Clear To Send (RTS/CTS) protocol to prevent the issue in unicast scenarios may result in a disappointing performance, due to the nature of safety-related I2V communications that employ short packets to be delivered with minimum latency.

A Seismic Alert System (SAS), also called Earthquake Warning System (EWS) or Earthquake Early Warning System (EEW or EEWS), represents one of the most important measures that can be taken to prevent and minimize earthquake damage. These systems are mainly used to detect P-waves and the faster seismic waves and to subsequently trigger an alarm about the incoming S-waves, the slower and most dangerous seismic waves. In some cases, distributed systems are also able to alert some locations before the impending P-waves strike them. This paper presents Earthcloud, a cloud-based SAS that aims to provide all the former capabilities while retaining financial accessibility. Earthcloud first results, generated from four months of data acquisition, are compared with those coming from other systems. In particular, the paper focuses on processing and communication delays, showing how the Earthcloud new detection strategy may minimize delays. Although a thorough test campaign with more sensor nodes is needed to assess performance reliably, especially for highly dense urban scenarios, initial results are promising, with total latencies for Earthcloud always kept under the 1-second mark, despite being at the expense of solid magnitude estimation.

In this paper, we present and characterize a phenomenon that arises when network congestion is met with packet redundancy at a distributed bottleneck. Congestion typically causes packet drops at the queueing level, especially when Active Queue Management techniques are employed to mitigate the bufferbloat effect. Redundancy may be present in the form of packet replication over different paths, as a solution to increase network resilience and network availability guarantees. When both network congestion and packet redundancy are in place, a counterintuitive throughput-boosting effect may originate from them. We named this phenomenon bufferboost, for the key role played by packet drops introduced to avoid bufferbloat effects. The contributions of this paper are the definition of the buffer-boost phenomenon, its modelling through a mathematical upper bound formulation, its isolation in an emulated environment for reproducibility and its validation through an extensive numerical evaluation that also verifies the introduced model. Results show that bufferboost is a favorable side effect able to boost network throughput.

The IEEE 802.11p amendment is part of the IEEE 802.11 family standard since the end of 2012. It specifies technical property such as the use of the 5.9GHz band with a 10MHz wide channel and a new operation mode, that each 802.11p compliant device should be set to: the Outside Context of a Basic Service Set (OCB) mode. OCB mode does not need authentication nor association and the only parameter to set is the central channel frequency and the channel bandwidth to communicate on. The Linux kernel has been recently updated with the introduction of the OCB mode, allowing the open-source community to test and develop network services on top of 802.11p networks. In this paper, the Linux OCB is presented and tested. A real testbed to measure performance of standard TCP communications in OCB mode is provided for the first time and experimental characterizations of the throughput and latency over OCB communications are given. Moreover, the paper individuates the best TCP modules' configuration to operate on 802.11p networks with low latency.

In recent years, the Linux kernel has adopted an algorithm called TCP Small Queues (TSQ) for reducing queueing latency by controlling buffering in the networking stack. This solution consists of a back-pressure mechanism that limits the number of TCP segments within the sender TCP/IP stack, waiting for packets to actually be transmitted onto the wire before enqueueing further segments. Unfortunately, TSQ prevents the frame aggregation mechanism in the IEEE 802.11n/ac standards from achieving its maximum aggregation, because not enough packets are available in the queue to build aggregates from, which severely limits achievable throughput over wireless links. This paper demonstrates this limitation of TSQ in wireless networks and proposes Controlled TSQ (CoTSQ), a solution that improves TSQ so that it controls the amount of data buffered while allowing the IEEE 802.11n/ac aggregation logic to fully exploit the available channel and achieve high throughput. Results on a real testbed show that CoTSQ leads to a doubling of throughput on 802.11n and up to an order of magnitude improvement in 802.11ac networks, with a negligible latency increase.

Recent Linux kernel updates have turned on the light again on the needs to reduce network latency in any environment, in particular in Wireless LAN. After the bufferbloat problem definition, many TCP congestion controls have been developed, different queueing algorithms have been deployed and advanced updates on wireless drivers and TCP modules have been reported as well. The contribute of this paper is to present and analyze through real extensive experiments these advanced new solutions highlighting a configuration able to limit a WLAN latency to a value close to 1ms. This result is one order of magnitude lower than the previous literature study and enables WLAN technology to support ultra-low latency communication.

A Seismic Alert System (SAS) is one of the most important measures that can be taken to prevent and minimize earthquake damage. The role of a SAS is to detect as soon as possible an earthquake in progress and to then immediately alert about the impending earthquake waves all locations in danger. Clearly, to be of any utility, the communication of the alarm has to be transmitted way faster than the propagation speed of the earthquake waves. This paper presents the rationale, setup and first results of a deployed Earthcloud prototype, an experimental SAS designed to be low-cost, low-power, and cloud-based. Earthcloud is devised to alert locations that are not too close yet not too far from the earthquake epicenter, i.e., those that can benefit from an alarm received from a few seconds to tens of seconds earlier. The system has been designed to leverage existing Internet infrastructures in order to perform both computation and communication in the cloud, minimizing costs and maximizing communication speed and deployment ease. Data harvested by Earthcloud has been cross-referenced with data from the Italian National Institute of Geophysics and Volcanology and, although still in a prototype stage, the first results indicate that the system can correctly detect earthquakes.

Satellite networking is known to suffer from specific network performance issues, such as high latency and low throughput stability; this derives mainly from the high propagation delay, in particular with GEO satellites. This characteristic poses limitations on the benefits that general AQM solutions could introduce; in fact, reducing congestion and mitigating queueing delay is a vital feature that could boost the performance of satellite networks. This paper investigates PINK (Passive INverse feedbacK), a queue management algorithm designed to indirectly impose an individual resource allocation policy in order to mitigate the bufferbloat effect and the network congestion while exploiting the channel throughput and guaranteeing optimal flow fairness without forcing any packet drop. PINK modifies the TCP Acknowledgements (ACKs) segments passing through the Satellite access gateway. The modification consists in replacing the advertised Receive Windows field (RCV.WNDs) with custom values, in order to enforce a particular bandwidth utilization upper bound. To compute new RCV.WND values, PINK needs only the number of active connections, the flows RTT and the transmission channel bandwidth. The design characteristics of this new AQM let it works efficiently in satellite networks, and we validate this statement through several simulations performed with the ns-3 network simulator.

Vehicle-to-Everything (V2X) communications encapsulate significant challenges as a result of the vast number of wireless technologies deployed, nodes mobility and large applications range. One of the greatest challenges is to provide adequate QoS guarantees even in this demanding environment. State-of-the-art solutions for QoS provisioning over wireless links are based on cross-layering packet schedulers that deal both with the QoS guarantees and the wireless link issues. Unfortunately, such an approach is not flexible and requires technology-dependent solutions, with the definition of a different software version for of the each technology deployed. To overcome this issue, we design a modular architecture which permits the use of existing high-performance packet schedulers for wired links over generic wireless technologies, as they are, and at the same time allows the flexibility to adapt to different channel conditions. We also provide a mathematical analysis of the QoS bounds of this novel architecture together with simulations analysis to validate it. This approach paves the way for efficient QoS provisioning and throughput-boosting in V2X systems.

This paper proposes PINK (Passive INverse feedbacK), a queue management algorithm designed to indirectly impose a certain resource allocation policy on defined sets of client hosts. PINK adds intelligence at intermediate nodes that connect client hosts to bottleneck links or to external networks in general, allowing these nodes to dynamically modify the TCP Acknowledgments (ACKs) segments passing through. This is made by setting TCP ACK advertised Receive Windows field (RCV.WNDs) to custom values, in order to enforce a specific bandwidth utilization upper bound. To compute new RCV.WND values, PINK needs only the number of active connections, the flows RTTs and the transmission channel bandwidth. It follows that PINK permits to impose a centralized bandwidth management without the cooperation of clients, which means that no modification or addition whatsoever to end hosts is needed with the goal of enabling a smart environment by simply configuring the access node. Furthermore, as demonstrated in this paper, our proposal does not constraints client hosts performance without purpose; on the contrary, PINK improves efficiency on multiplexed channels by exploiting channel throughput, maintaining a low queuing delay, and guaranteeing optimal flow fairness without forcing any packet drop.

During their day-to-day tasks, public safety operators rely on commercial mobile networks in order to perform data communications and make use of data-based services. In major disasters, however, it is the norm to witness high degrees of network congestion and, often, to experience service outages caused by infrastructural damage. This may strongly hinder the operativity of emergency operators, that expect to rely on resilient communication infrastructures and that demand network availability no matter what. In order for today mobile networks to provide such capabilities, some degree of redundancy should be introduced, either in hardware as infrastructural deployments or in software as data replication mechanisms. This paper focuses on the latter approach. It proposes a network framework to enable collaborative hosts to concurrently forward replicated data over an arbitrary number of channels, in order to compensate for high packet losses or sudden unavailability of routing paths. The data replication and the forwarding behavior are concerted by an SDN controller, that transparently implements a network abstraction to virtually pool hosts network resources. The paper also presents the test bed that has been built and used to extract the emulation results. These demonstrate that the proposal have the potential to strongly improve data communication capabilities in constrained scenarios, in the form of higher data rates and stronger resilience guarantees. Last but not least, it is shown that services availability may be provided in much more cases, even when regular operativity fails.

After a disaster, it is unlikely to expect current terrestrial infrastructures to provide the coverage and the Quality of Service required by emergency operators. Currently, PPDR operators go towards a portable LTE infrastructure that provides an access network to field operators, backhauled by a wireless mesh network that can route traffic from and towards Internet through a satellite gateway. We firstly propose a new per-flow strategy for a backpressure-based routing protocol, BP-MR, and then in the aforementioned environment we analyse the original BP-MR per-packet, the proposed per-flow, and OLSR as routing protocol for the mesh network coupled with three TCP congestion control (Cubic, Hybla, Vegas) performing a typical HTTP transfer. We analysed the throughput, the latency, and the scalability over the number of the flows/operators. An extensive simulation set allows to conclude that employing BP-MR per-flow in the mesh network coupled with TCP Vegas for performing the end-to-end transfer improves the performance for PPDR professionals.

In scenarios where a number of client nodes share a gateway in order to access a high-delay link, the original TCP as well as TCP variants specifically designed to improve performance on those links fail to provide optimal performance; this is due to the indirect inference of both end-to-end congestion and local channel conditions. To mitigate the former, C2ML (Congestion Control Middleware Layer) has been proposed as a tool for centralized and collaborative management of resources that can strongly improve performance for client hosts without affecting network resilience and connection survivability. To complete the picture, this paper proposes DyBRA, an improved version of C2ML with a bandwidth management algorithm designed to dynamically allocate bandwidth among client hosts on the basis of channel conditions, leading to improved performance regardless of the TCP variant employed by clients. Through simulations performed with the ns-3 network simulator, we show how DyBRA strongly improves throughput and TCP friendliness while reducing queue usage and latency.

When multiple nodes share the same gateway or access the same link, the throughput of wireless communications has the unfortunate problem of being limited by traffic congestion; the situation may also further degrade if they establish multiple TCP connections mapped over the same access channel. In end-to- end connections, TCP congestion control plays a critical role in order to not overflow the channel, although most of the network bandwidth bottlenecks are caused by the wireless systems. When TCP is coupled with high-delay channels, the protocol underperform; this is mainly due to long propagation delay, as it is the case with satellite links. To overcome the limitations of TCP on these links, various variants have been proposed, both rate-based or or burst-based. In this paper we present a cooperative transmission control that enhances the effectiveness of TCP asking only for a narrow sender-side modification, operating exclusively at the access stage. It allows to boost throughput over high delay channels, increasing also fairness and friendliness between different TCP algorithms. After the description, we validate its effectiveness and show its properties by means of experimental results, derived from simulations performed on the ns-3 network simulator.

This paper presents preliminary work on PINK (Proactive INjection into acK), an AQM algorithm able to enhance TCP congestion control properties without dropping packets. PINK is a completely transparent solution that does not require any modification to the existing protocol stack of end hosts, and it is particularly suitable for high-delay PPDR systems. The algorithm is based on an explicit feedback scheme, able to enforce a fair bandwidth sharing among clients by modifying the Receive Window in TCP acknowledgements returning to them; such a feedback is computed for each flow, and it only needs the number of active connections, the flows RTTs and the shared link bandwidth. Therefore, PINK is a per-flow stateless AQM that works independently from the TCP algorithm used by clients, and it is fair regardless the flows RTTs, which is a key feature for PPDR systems. The effectiveness of the proposed algorithm is demonstrated using the ns-3 simulator.

Network-enabled services for public protection and disaster relief (PPDR) professionals have been more than necessary in today's emergency situations. Under the extreme circumstances of an emergency, it is essential to have networks which support the required data throughput as well as high availability in spite of high traffic volume, and which minimize the end-to-end delay for applications: however, the choice between the existing technologies is not so easy for PPDR entities, given the high number of parameters associated to satisfying the stringent PPDR requirements, high investments required to permit desirable availability as well as modernization of the existing services (i.e. voice and data) and design constraints posed by network providers as current deployed network reach their boundaries when emergencies occur. This paper analyzes three different emergency scenarios and then presents a subset of the results obtained in terms of financial and economic recommendations, along with technical reports on throughput and end-to-end delay.

The vast majority of efforts aimed to improve network performance are focused on the increase of application throughput. The same holds in the context of Emergency Networks, where operators ask for more bandwidth in order to exploit data-intensive services. Following a steady growth in network capacities and number of users, large buffers have been inserted all over the Internet. Their effects on networks are non-trivial: while they may effectively serve the purpose of exploiting the channel potential, they also create unnecessary delays by damaging the behavior of the most common transport protocol, TCP. Nevertheless, they are being assumed by new congestion control algorithms, especially those tailored for high-latency links such as satellite ones. According to the anywhere-anytime paradigm, these channels represents a key technology for both Emergency and General-Purpose networks. In this paper we first show how buffer lengths impact the perceived delay over satellite links that employ a recently proposed burst-based TCP protocol, and then present a cooperative transmission control that reduce buffers usage and latency while keeping high throughput and flow fairness, thus allowing for a better service provision through satellite links.

The packet scheduling problem has been deeply studied for lot of years by researchers in the computer science and telecommunications fields as an important solution that decides the order in which packets are sent over a link in order to provide QoS on a network. Recently, the packet scheduling has become again a challenging topic due to the massive use of wireless technologies (e.g. WiFi, LTE, 4G/5G), both for public and PPDR networks, with which to provide high QoS guarantees is still an open problem. Unfortunately, it is difficult to compare different solutions and actually test them in order to select the most proper packet scheduler for each particular environment.

Wireless communication technologies are critical for public protection and disaster relief (PPDR) professionals during the emergency operations that follow natural or man-made disasters, scenarios in which commercial terrestrial networks often fail to provide the necessary support. The reason is threefold: they simply get disrupted by the disaster, they cannot sustain the sudden surge of network demand or they fail to deliver the necessary bandwidth and/or other QoS guarantees. In every PPDR operation reliable voice communications are critical, especially in the very early stages of the response; nevertheless, there is an increasing demand from the PPDR community for a wider range of data-centric services. While current technologies used for PPDR operations provide a rich set of voice-centric services, they are unable to sustain high-bandwidth data-oriented applications. As the PPDR-TC EU consortium, we propose a hybrid approach to tackle the question of determining the future architecture for Pan-European PPDR networks based on the integration of Terrestrial and Satellite technologies, presenting our first simulation results on the integration of LTE and Satellite Networks.