QUIC is emerging as the de facto transport protocol for modern applications and forms the basis of HTTP/3. Within the European Space Agency (ESA) project QUICoS, we developed QUIC-Wave, a satellite-tailored extension of QUIC designed to address the limitations of TCP-based transport in high-latency and lossy satellite environments (GEO, MEO, LEO). Unlike Performance Enhancing Proxy (PEP) approaches, QUIC-Wave preserves end-to-end semantics and encryption while enhancing congestion control. The protocol extensions are engineered to sustain throughput and responsiveness under satellite-specific conditions such as long RTTs, bandwidth variability, and mobility-induced handovers, while maintaining compliance with QUIC specifications and interoperability with terrestrial networks. To validate QUIC-Wave, we conducted extensive real experiments using standard browsers and servers. Results show that QUIC-Wave supports interactive web browsing and multimedia streaming with improved performance over satellite links, without compromising either end-to-end encryption or protocol integrity.

The ongoing digitization of Operational Technology (OT) and the integration of Industrial Internet of Things (IIoT) devices are fundamentally transforming modern industrial systems. However, the heterogeneity of hardware and software ecosystems amplifies the complexity of this transformation, making orchestration and lifecycle management especially challenging. To address these challenges, modern DevOps practices—such as Continuous Integration and Continuous Deployment (CI/CD), runtime observability, and fine-grained access control—are essential. These practices help accelerate time-to-market, maintain service quality, manage operational complexity, and uphold security standards. Advancing toward seamless integration of OT within cloud-native environments, we introduce a prototype Orchestrator based on the Kubernetes plarform, aimed at providing a comprehensive lifecycle management for OT devices in industrial contexts. Our proposal bridges the traditional divide between IT and OT by seamlessly integrating with existing CI/CD pipelines and implementing Role-Based Access Control (RBAC) tailored to device-level permissions. Through a unified abstraction layer, it simplifies the management of heterogeneous, multi-vendor hardware, enabling scalable, secure, and efficient operations across diverse industrial deployments.

• Comprehensive tracking system using Decentralized Identifiers and Verifiable Credentials to ensure Federated Learning (FL) process governance. • Robust influence estimation to quantify the trustworthiness of clients and data contributions. • Automated policy-driven revocation mechanism for models and data based on established open standards. • Seamless integration into FL-based architectures, enabling the development of transparent and trustworthy models supporting Digital Twin functions. • Extensive experiments conducted on a real prototype across diverse settings demonstrate the effectiveness and efficiency of the solution. As Digital Twin (DT) ecosystems increasingly rely on distributed and collaborative intelligence, ensuring trust and reliability of the underlying Machine Learning (ML) models becomes critical, especially when raw data cannot be centrally aggregated due to privacy or security concerns. Federated Learning (FL) has emerged as a promising paradigm for collaborative model training across distributed data sources while preserving data privacy. However, the inherent opacity of the FL process introduces several challenges; individual data contributions, as well as local node updates, remain inaccessible to centralized oversight, hindering the overall trustworthiness of the global model training process. In addition, data and updates of the local model can be biased, or even maliciously modified, negatively affecting the global model. In the context of DTs, such vulnerabilities can directly compromise decision-making, leading to operational safety risks and affecting the system’s reliability. To this end, we propose TrustFLow, a comprehensive framework that integrates Decentralized Identifiers (DIDs) and Verifiable Credentials (VCs) deployed over a distributed ledger infrastructure to securely trace the provenance of data and evolution of models in FL. TrustFLow tracking capabilities enable linking data to sources, tamper-proof monitoring, and process traceability. In addition, TrustFLow provides crucial functionalities for estimating the influence of individual producers (datasets) on the global model and for revoking both biased data and the global model(s) influenced by them. These features contribute to a broader vision of federated governance, where accountability, transparency, and trust are enforced between all participants. In addition, our framework offers the benefit of seamless integration into any FL-driven DT architecture. To evaluate our proposal, we have conducted an extensive set of experiments that measure the efficiency and effectiveness of the framework under different settings.

We investigate a scenario where multiple sources independently and voluntarily contribute status reports, which are then aggregated through a federated process. To address the challenge of partial participation in distributed systems, we introduce the age of federated information (AoFI), a novel metric that quantifies data freshness. This metric is specifically designed to bridge the gap between classical age of information, which is unsuitable for collaborative tasks, and the often impractical age of correlated information, which requires full participation. To model distributed optimization across multiple independent sources, we adopt a game-theoretic framework. In this framework, users strategically minimize their individual penalty, computed as a global-local combination of the overall AoFI on the common receiver’s side and their individual energy expenditure. We derive the worst-case Nash equilibrium of this game and compare its efficiency with the centralized optimization optimum. Our efficiency analysis reveals a critical design tradeoff for practical industrial internet of things (IIoT) deployments: while decentralized coordination is highly efficient in high-participation regimes, performance in low-participation regimes is paradoxically optimized by actively restricting the number of sources to prevent strategic inefficiencies.

Mobile Edge Computing (MEC) facilitates low-latency service delivery by bringing computation to the network edge, while microservice architectures enhance system flexibility and scalability through modular application decomposition. Their integration allows applications to dynamically scale and efficiently isolate faults in response to fluctuating demand. However, the heterogeneous and dynamic nature of edge environments poses significant challenges to the cost efficiency, security, and privacy of such deployments. Unlike prior work that handles security and privacy as constraints or overlooks AN dynamics, we characterize both AN selection and service placement as mutually dependent decision layers within a unified control structure. Our proposal balances the computational overheads incurred by security and privacy verification against deployment costs, preventing aggressive cost-reduction efforts from compromising system protections. Considering the unpredictability of run-time and network conditions, we propose an online algorithm for progressive decision-making. The deployment problem is decomposed into one-slot optimization sub-problems, each NP-hard, for which we develop a greedy-based heuristic algorithm. Experiments across diverse loads, request patterns, and security/privacy thresholds show that the proposed algorithm consistently achieves the lowest average deployment cost, with cost reductions of at least 41.67% compared with the baselines, while maintaining comparable or higher request acceptance ratios and generally lower, well-balanced edge-server workloads.

Critical industrial applications call for very stringent delay and high reliability requirements. To support them, even in the presence of Mobile Nodes (MNs), the 5G cellular technology provides the Ultra-Reliable Low-Latency Communications (URLLC) service class, which guarantees packet delivery with a maximum delay of a few ms and a reliability of 99.999%. In this paper, we investigate how to provide similar performance guarantees using IPv6 over the TSCH mode of IEEE 802.15.4e (6TiSCH) based on short-range wireless communication. To this aim, we propose an original resource scheduling algorithm, namely Enhanced Shared-Downstream Dedicated-Upstream (E-SD-DU). In addition, the paper provides the readers with the original contribution of an analytical model to determine the MNs that can be supported while satisfying the specified application requirements (and the related deployment cost). The obtained results show that our scheduling algorithm can guarantee a delay of $\mathbf{1 0 ~ m s}$ with a reliability of $\mathbf{9 9. 9 9 9 \%}$.

The increasing reliance on Machine Learning (ML) to extract insights and value from data is driving researchers and businesses to seamlessly integrate it throughout the entire Cloud Continuum (CC), spanning from large-scale cloud infrastructures to edge computing and end devices. However, traditional service orchestration frameworks are fine-tuned to manage single-site general-purpose applications, struggling with the complexity of CC ML deployments, which seek customized strategies for enhanced performance and resiliency. To this end, we propose Machine Learning cloud Continuum Operations (MLCOps), an overlay solution that supports ML applications in CC deployments. MLCOps implements an innovative multisite orchestration layer and provides a new service runtime support, allowing one to react quickly to changing conditions. MLCOps advocates a layered approach to carry out specialized strategies, implementing global and local actions on infrastructure and environment to ensure the performance and availability of the deployed ML services. Without loss of generality, we show how the framework could be instantiated to support an anomaly detection task. In this context, we assess various (re)configuration strategies that can take place in actual deployments, assessing the ability of MLCOps to preserve the reliability of CC ML application deployments under dynamic workload conditions.

In the rapidly evolving data economy, the ability to securely and efficiently share data between organizations has become paramount, unlocking new opportunities for innovation and growth. In this context, different initiatives have worked on conceptual proposals and enabling technological building blocks, addressing design aspects of data spaces. However, the current landscape lacks practical implementations and integration of secure data-sharing primitives supporting a decentralized data ecosystem. To this end, we conduct an analysis of previous efforts and initiatives, identifying gaps. We then introduce VESPACE , a blockchain-based platform for data spaces that enables participants to selectively and securely share verifiable data with authorized users while maintaining control over their access. Our framework incorporates data sovereignty principles implemented through Decentralized Identifiers (DIDs), Verifiable Credentials (VCs), and blockchain technology, qualifying decentralized identity and access control as key features to establish user trust in decentralized data ecosystems. We present a prototype system implementation of VESPACE , evaluating the design choices, showcasing the feasibility of our proposal. • We analyze standards and projects to guide verifiable, auditable data space design • We propose VESPACE , a verifiable data space aligned with FAIR and SSI principles. • We evaluate a prototype to assess the scalability of the implemented security primitives.

The recent trend pushing towards reliance on edge computing, virtualization and programmatic 5G network control has sparked the development of a myriad of open-source resource management and orchestration projects for improved control and added flexibility, making up for a rich and complex ecosystem of frameworks and tools with varying degree of support for standardized features. In this technological panorama, the ETSI Multi-Access Edge Computing (MEC) standard proposes a conceptual reference architecture, standardizing edge integration, interoperability and application management in an extended 5G edge-core architecture. In this context, we propose an application-aware orchestration solution for 5G edge-core distributed deployments, currently lacking support in state-of-the-art frameworks and tools. The proposal is built on an experimental and distributed deployment of the OpenAirInterface minimal MEC platform implementation and relies on the Kubernetes Operator pattern for the automatic MECApp lifecycle management. To validate our approach, we conduct a series of experiments, reporting key metrics of interest.

Low Earth Orbit (LEO) satellites offer a promising solution for ubiquitous connectivity and can be utilized in 5G Non-Terrestrial Networks (NTNs) for applications like IoT, autonomous driving, and rural communication. They are particularly suited for smart mobility in urban environments, where fast data transmission and real-time control of vehicles and infrastructure are crucial. In this study, we compare TCP protocols for satellite communication in smart mobility scenarios and propose a solution that uses a limited buffer size to reduce per-packet delays without affecting the throughput.

Smart logistics is paramount within the multifaceted framework of smart cities. The evolving landscape of sales channels has intensified the demand for efficient logistics solutions capable not only of optimizing the delivery process but also of controlling the environmental impact within the urban setting. Digital Twin solutions have emerged as promising tools to navigate the complexities of modern logistics scenarios. Acc2Twin is an ongoing project, targeting the optimization of the pallet wrapping cycle for package delivery, reducing plastic waste. The solution accurately reconstructs delivery routes and relies on driving profiles to infer the physical forces experienced by delivery trucks, used to assess the stretch and integrity of the plastic film. In this article, we focus our attention on RouteVel, a system component adopted to enrich topological data by augmenting point density through a mix of interpolation techniques, enabling precise analysis of acceleration profiles used as input to the physics-based Digital Twin to assess the pallet wrapping cycle stability. The paper also provides insight into the performance assessment of the tool to understand its potential and the potential points for improvement.

Reliable communications play a pivotal role in ensuring an efficient response and the coordination of recovery and rescue efforts. However, conventional communication methods may not always be accessible or dependable in such situations. In such circumstances, constellations of Low Earth Orbit (LEO) satellites can provide high bandwidth capabilities with relatively low latency, making them well-suited for supporting on-the-ground disaster management teams. Satellites can either complement or replace terrestrial telecommunication infrastructures. In this context, reliance on the recently defined QUIC protocol allows for a seamless transition from terrestrial to satellite communication as needed. Therefore, we investigate the possible use of a dual-stack node architecture along with the employment of the QUIC transport protocol for emergency communications, assuming that the backhaul link used to transfer users’ applications data may need to be changed (seamlessly). We conduct an extensive emulation study, evaluating the performance of QUIC under varying queuing policies and Congestion Control Algorithm (CCA) behaviour, providing practical insights and recommendations to enhance the protocol’s efficiency and robustness. The key aspects and configurations of QUIC protocol stack are identified, presenting optimal communication configurations leveraging CoDel and BBR CCA.

The emerging paradigm of resource disaggregation enables the deployment of cloud-like services across a pool of physical and virtualized resources, interconnected using a network fabric. This design embodies several benefits in terms of resource efficiency and cost-effectiveness, service elasticity and adaptability, etc. Application domains benefiting from such a trend include cyber-physical systems (CPS), tactile internet, 5G networks and beyond, or mixed reality applications, all generally embodying heterogeneous Quality of Service (QoS) requirements. In this context, a key enabling factor to fully support those mixed-criticality scenarios will be the network and the system-level support for time-sensitive communication. Although a lot of work has been conducted on devising efficient orchestration and CPU scheduling strategies, the networking aspects of performance-critical components remain largely unstudied. Bridging this gap, we propose KuberneTSN, an original solution built on the Kubernetes platform, providing support for time-sensitive traffic to unmodified application binaries. We define an architecture for an accelerated and deterministic overlay network, which includes kernel-bypassing networking features as well as a novel userspace packet scheduler compliant with the Time-Sensitive Networking (TSN) standard. The solution is implemented as tsn-cni, a Kubernetes network plugin that can coexist alongside popular alternatives. To assess the validity of the approach, we conduct an experimental analysis on a real distributed testbed, demonstrating that KuberneTSN enables applications to easily meet deterministic deadlines, provides the same guarantees of bare-metal deployments, and outperforms overlay networks built using the Flannel plugin.

The advent of the digital innovation era is changing service, use, and resources management paradigms, offering a wide range of new and essential opportunities. In particular, the advent of the Internet of Things (IoT), i.e., the ability to connect individual objects to the Internet, also capable of communicating autonomously, has its particular declination on the connected vehicle. It is combined with the potential of advanced sensors placed pervasively on vehicles, which offer multifunctional monitoring capabilities of the entire system: from individual components up to the whole vehicle, including driver behavior and conditions and many exogenous parameters to the vehicle (road and weather conditions, congestion, risk situations, changes to mobility plans, etc.). In this perspective, machine learning (ML) models can transform raw data into new knowledge; they can contribute in an innovative way to define and suggest decisions, strategies, and criteria for resource use. Nowadays, most intelligent mobility projects also integrate artificial intelligence (AI) and ML solutions. In this article, we present and discuss the application of unsupervised learning techniques on a vehicular IoT data set. The main goal is to generate new knowledge about a geographical zone by analyzing historical drivers behavioral data. The autonomous vehicle’s framework can exploit the generated valuable insights to optimize the routes and prevent critical issues.

The continuous digitalization and application of modern ICT technologies in the Smart City and Tourism domains are paving the way to new, integrated and connected experiences with strong economic and social impact. However, the integration of services and data coming from different providers is hindered by a rapidly evolving ecosystem of tools and techniques, introducing substantial delays and costs in solution design, deployment, testing, and refinement. Serverless computing is a novel cloud computing model where the customers' business logic, structured as lightweight functions, is automatically put into execution in response to an incoming event. This emergent paradigm promises to be an appealing solution, lowering the development and management barrier for the adaptation, integration, and roll-out of services. However, the ephemeral nature of serverless functions clashes with the necessity of creating and maintaining persistent connections to the various data providers. In this work, we present the Serverless Persistence Support (SPS) service, a novel, distributed, and scalable service implementing an adaptation layer able to improve data access performance from serverless functions. To validate our proposal, we conduct a thorough analysis on a realistic testbed, contrasting various data layer supports and assessing SPS performance when compared to the classic approach where connections and operations are executed inside the business logic. The experimental analysis shows that our solution exhibits better performance both in terms of latency and throughput, while also improving resource utilization.

The increasing pace of sensing and communication technology rollout is paving the way for concrete deployments of smart city applications, enabling a data-driven modeling of processes and the environment. In particular, the Urban Facility Management (UFM) process is growing in importance, recognized to have a direct impact on the sustainability and the development of our cities. In [1] we presented a system's view of a Digital Twin solution for the UFM process. The solution relies on (near)real-time data to quantify the activity index in an area of interest, used as a basis for planning decisions. In this study, we focus on the predictive subsystem, tasked with computing near-to-mid term predictions of the activity index, equipping UFM operators with a flexible decision-support system. Without loss of generality, we present an analysis of the vehicular traffic component, part of the activity index, assessing the accuracy of different predictive schemes, discussing some operational implications.

Industry 4.0 aims to revolutionize and digitize the manufacturing sector by enabling and facilitating interoperability, solution agility, flexible (re)configuration of production chain(s) while, at the same time, reducing costs by exploiting real time data. These capabilities require to link the plant floor with data flows from/to the enterprise borders and include as core enabling technologies the Internet of Things (IoT), cloud, and edge computing key to move and execute parts of the business logic. The new capabilities might be leveraged in an innovative way, especially in the plant floor to dynamically change the monitoring/control logic of the smart machinery. In our reference scenario, the data flows originating from the plant floor can be processed and filtered locally, creating the basis for a selective Quality of Service (QoS) mechanism allowing for the implementation of reactive services, such as predictive maintenance. To that end, we propose an innovative serverless edge processing solution used for monitoring geo-distributed industrial plants. The proposal is validated in realistic settings, under different operational regimes, exhibiting acceptable performance trends under realistic periodic and variable traffic scenarios.

Serverless platforms are increasingly gaining importance in the cloud computing landscape due to their benefit of shortening the time to market of solutions and capability of automatic, fast, fine-grained scaling of resources. In this context, function chaining represents an appealing feature, allowing the composition of two or more functions to create a complex computation from simpler units while incentivizing modularity and reusability of functions. In this paper, we propose a portable and transparent, container-based serverless architecture that introduces an innovative infrastructural support, enabling an efficient composition of functions co-located on the same host. The proposal relies on a shared-memory approach and a message-oriented middleware serving as a communication medium among components. The experimental assessment shows the approach comes with the benefit of optimized resource usage and performance benefits measured in terms of request completion rate and a decrease in response latency.

Industrial networked computing environments are expected to serve a wide range of applications with heterogeneous Quality-of-Service (QoS) requirements. This capability demands for novel, QoS-aware network management and configuration techniques resilient in the face of network changes. State-of-the-art approaches only focus on aspects related to the management of network devices. In this work, we move a step further, proposing an end-to-end QoS management approach in Time-Sensitive Networking (TSN) compliant networks, capable of handling reconfiguration events e.g., link-drop. Shedding some light on our proposal, we first discuss its functional building blocks, successively validating the approach on a real TSN testbed.

The recent trend of network disaggregation and community push towards open source network management and orchestration projects has given rise to a rich ecosystem of frameworks and tools. In particular, ETSI NFV proposes a conceptual, reference architecture standardizing management and control interfaces in softwarized mobile broadband networks. These frameworks present highly customizable features, embodying varying degrees of complexity, communed by a steep learning curve. In this article, we propose a stepby-step description of a virtualized testbed environment setup, adopting an NFV-compliant ecosystem, describing an implementation of the NFV SOL002 reference point which aims to standardize the lifecycle management of virtualized functions. In addition, we present an experimental assessment measuring the mobile core deployment times.

Abstract Wearable technology is no longer science fiction. Thanks to the growing capability in the production chain to miniaturize complex electronics, a wide variety of gadgets that can be worn or included in dresses and accessories have emerged. These smart gadgets can collect data about the physical condition of the user and/or the environment providing the basis for innovative and valuable services. The main goal of this paper is to assess this context through field experiments undertaken in a testbed comprised of sensing hardware deployed on open source boards such as Arduino. Moreover, coupled with the sensing tier, we propose a proof‐of‐concept deployment architecture enabling a wide range of wearable sensors to collect and transmit data to a logically centralized unit.

Abstract Mobile Ad-Hoc Networks are currently experiencing a second youth in terms of research interest as well as providing benefits to our society. Clearly, this has been fostered by the wide range of applications that have become actually feasible thanks to the pervasive and increasing presence of smartphones, drones, sensors and other small devices with communication and sensing capability. Aiming to deploy solutions able to self-organize without the need for any infrastructure support, packet routing remains an open and critical research problem. Several routing solutions have been conceived to guarantee delivery and low overhead in this context. A promising approach, trying to limit the information needed and stored in the network, is represented bystatelesssolutions, a class of solutions not relying on topology state information. However, since they exploit local knowledge, the achieved performance in terms of packet delivery and latency is not always up to expectations. To this aim, we propose a dynamic routing protocol based on atabu searchapproach, relying on local network knowledge and in-packet short-term memory to alleviate the local minima problem. A through experimental assessment is conducted, measuring protocol performance under different configurations and profiles, evidencing its benefits.

The fruition of multimedia contents has been revolutionized by the spread of broadband technology. Furthermore, the advent of the cloud is now moving the computational load, once prerogative of domestic devices, to remote servers. This is bringing achievements that were unthinkable only few years ago, like the provisioning of new multimedia services through the Internet. To guarantee a proper user experience, a low E2E latency and a high bandwidth are both essential. Unfortunately, this is difficult to accomplish in a shared and best-effort network like the Internet. We need to focus on the study and analysis of modern network protocols to identify viable solutions for a suitable user experience. This is especially the case of QUIC, a recent transport protocol able to reduce significantly some issues mentioned above. Our aim is to explore QUIC and its integration into a Smart Access Point, enabling a better management of heterogeneous co-existing media flows.

Cloud computing has transformed the way IT services are provisioned and consumed, shifting the burden of configuration and management to the cloud provider. A lot of research has been conducted in the field aimed at optimizing and/or devise new in-cloud service delivery models. Yet, service outages are a norm rather than an exception. A natural evolution for application developers, especially for those applications that must meet high availability requirements, is to rely on resources and services provisioned by multiple cloud simultaneously. The so-called multi-cloud, distributed deployment model coupled with a monitoring solution spanning multiple domains could help in a timely identification and isolation of faulty components, alleviating service impairment issues. To this end, we propose an extension to NoMISHAP, a Platform as a Service (PaaS) multicloud middleware, introducing a cross layer monitoring solution for use in distributed cloud environments. Experimental results show the effectiveness of our approach and its ease of adoption for management tasks.

Air quality and the presence of tiny particular matter are crucial factors in human health, especially when considering urban scenarios. In this context, smart mobility coupled with low-cost sensors can create a distributed and sustainable platform for social sensing able to provide pervasive data to citizens and public administrations. Sustainable and eco-aware decisions can then be supported by empirical evidence, resulting in an improved life and city administration. In this paper, we present ArduECO, a simple Arduino-based wireless device able of collecting air quality data. Without loss of generality, we have designed our device as a box that can be installed on a bike; in this way, beyond private bikes, municipalities could exploit their bike sharing fleets as pervasive sensing systems.

The increase in the amount of traffic with heterogeneous QoS requirements poses several challenges to end-to-end service provisioning. Network resource management and service differentiation are two crucial functionalities employed by service providers, proven essential in order to meet the end user requirements. In particular, application-driven networking has emerged as a viable alternative embodying the potential of enabling specific flow optimizations meeting application-specific requirements. In this context, Service Function Chaining (SFC) is seen as an enabling technology for the flexible management of specific service/application traffic. In this paradigm the network functions are seen as an ordered chain of interconnected functions handling traffic delivery (data plane), control and management. In this article we present a work in progress of a virtualized, container-based testbed with orchestration and management capabilities supporting service chains.

Although much has been done in the field of accessibility, the World Wide Web is not yet for everyone. Many Internet users often find difficulties in navigating web pages. This is particularly true for people with visual impairments and blind people. In this paper, we present a review of the state of the art of the application of accessibility rules to web pages and describe which are the common problems that people with sight impairments must endure when surfing the Internet; to this aim, we use information collected during an interview with a blind user who is an expert in navigating the web using a screen reader.

In this paper we propose a theoretical model, which may be put to good use to analyze the energy consumption of a smartphone where a random number of different applications are assumed to run, for random intervals of time, consuming the available energy resources. The problem is formulated in terms of the following mobile application(s) parameters, namely: (i) the maximum possible running time, (ii) the average amount of energy consumed per time unit while running, (iii) the average number of apps that are employed during a given smartphone's usage. The model is solved in terms of the probability distribution function of the energy consumed on a given smartphone. The proposed model is then validated by simulation means, in order to prove its applicability in quantifying the amount of energy consumed.

The actual advent of autonomous vehicles and the general improvement of traffic safety pass through quick and reliable message dissemination in a certain Area of Interest (AoI). Message dissemination among the vehicles composing an Internet of Vehicles (IoV) is of paramount importance and has to make use of fast and efficient multi-hop message forwarding to broadcast information. While most of existing works focus only on simple car platooning scenarios (e.g., a highway), we discuss here a fast multi-hop broadcast protocol able to quickly and reliably propagate an alert message even in general 2D (and 3D) topology scenarios.

We consider the scenario in which several TCP connections share the same access point (AP) and a congestion avoidance/control mechanism is adopted with the aim of assigning the available bandwidth to the clients with a certain fairness. When UDP traffic with real-time requirements is present, the problem becomes even more challenging. Very well-known congestion avoidance mechanisms are the Random Early Detection (RED) and the Explicit Congestion Notification (ECN). More recently, the Smart Access Point with Limited Advertised Window (SAP-LAW) has been proposed. Its main idea is that of computing the maximum TCP rate for each connection at the bottleneck, taking into account the UDP traffic to keep a low queue size combined with a reasonable bandwidth utilization. In this paper, we propose a new congestion control mechanism, namely, Smart-RED, inspired by SAP-LAW heuristic formula. We study its performance by using mean field models and compare the behaviours of ECN/RED, SAP-LAW, and Smart-RED under different scenarios. We show that while Smart-RED maintains some of the desirable properties of the SAP-LAW, it solves the problems it may have in case of bursty UDP traffic or TCP connections with very different needs of bandwidth.

The worldwide diffusion of mobile technology has opened the door to a new era of distributed sensing. Indeed, mobile sensing and wireless technology can be exploited to create new information and services that have the potential to improve our lives in many ways. This becomes even more interesting if the benefits could reach the whole community, even people with disadvantages that are often left out by the digital divide. To this aim, we have developed a system able to offer an enhanced route navigation system, while at the same time gathering quality data through smartwatches. Even more interesting, we have endowed our system with an interaction paradigm based on vibration patterns so as to guide the user without the need for looking at the device. Our proposal avoids user distraction and field trials demonstrate its effectiveness when employed by visually impaired people.

It is easy to foresee a future with many smart and connected things, static or moving around, occupying space and creating an Internet of Things (IoT) with a 3D topology. Unfortunately, state-of-the-art routing protocols for ad-hoc networks have been designed to work in 2D scenarios. We here evaluate how these routing protocols would perform in a 3D IoT.

Wearable devices are constantly expanding in number and functionalities within both the IT market and the fashion market. Smart watches have become very popular and have moved from a tool only showing information related to the smartphone to a device able to monitor and display a vast plethora of data, including data related to the owner's health (e.g., hearth rate, body temperature, steps per day, etc.). This huge amount of data that wearables in the world can generate could be further elaborated to become even more useful. Yet, designing effective solutions to collect, store and elaborate sensors data is a challenging task. To this aim, in this paper, we present a framework to model a wearable sensors network in a simple and flexible in order to adapt to different scenarios.

Vehicular networks are receiving more and more attention from researchers and practitioners. In this context, it is particularly interesting to study realistic scenarios where vehicles are connected among themselves, or with other nodes. Think, for instance, of cooperating interconnecting objects forming an Internet of Vehicles (IoV) to collectively decide on maneuvers. Such connected autonomous vehicles would certainly require fast but also reliable group communications. Broadcast in wireless networks would be useful in this scenario if a tradeoff between reliable message delivery and low overhead can be solved. To this aim, we evaluate the performance of probabilistic flooding schemes and propose a heuristic-based solution that seems promising in fitting the IoV's needs.

Summary Interactive applications as online games and mobile devices have grown in popularity. From their combination, new and interesting cooperative services could be generated. For instance, gamers endowed with Augmented Reality (AR) visors, connected as wireless nodes in an ad‐hoc network, can interact with each other while immersed in the game. To enable this vision, we discuss here a hybrid architecture enabling game play in ad‐hoc mode instead of the traditional client‐server setting. In our architecture, one of the player nodes also acts as the server of the game, whereas other backup server nodes are ready to become active servers in case of network disconnection, ie, due to low energy level of the currently active server. This allows to have a longer gaming session before a disconnection occurs due to energy exhaustion. In this context, the server election strategy with the aim of maximizing network lifetime is not so straightforward. To this end, we have analyzed this issue through a Mixed Integer Linear Programming (MILP) model considering static network topologies and both numerical and simulation‐based analysis shows that the backup servers solution fulfills its design objective. Contemplating for mobility, we present a simulation study employing actual packet routing protocols and discuss the tradeoffs that emerge.

In recent years we have seen a great proliferation of smart vehicles, ranging from cars to little drones (both terrestrial and aerial), all endowed with sensors and communication capabilities. It is hence easy to foresee a future with even more smart and connected vehicles moving around, occupying space and creating an Internet of Vehicles (IoV). In this IoV, a multitude of nodes (both static and mobile) will generate a continuous multihop flow of local information to support local smart environment applications. Therefore, one interesting environment for the IoV would be in the form of 3-D mobile ad-hoc networks (MANETs). Unfortunately, MANET routing protocols have generally been designed and analyzed keeping in mind a 2-D scenario; there is no guarantee on how they would support a 3-D topology of the IoV. To this end, we have considered routing protocols deemed as the state-of-the-art for classic MANETs and tested them over 3-D topologies to evaluate their assets and technical challenges.

Scalable routing for wireless communication systems is a compelling and challenging task. To this aim, routing algorithms exploiting geographic information have been proposed. These algorithms refer to nodes by their location, rather than their address, and use those coordinates to route greedily towards a destination. With the advent of unmanned airborne vehicle (UAV) technology, a lot of research effort has been devoted to extend position-based packet routing proposals to three dimensional environments. In this context, Flying Ad-hoc Networks (FANETs), comprised of autonomous flying vehicles, pose several issues. This work focuses on the state-of-the-art, stateless geographic packet routing protocols conceived or adapted for three-dimensional network scenarios. Proposals are evaluated over a common scenario through a comprehensive comparative analysis.

Different theories state that future market values strongly depend on psychological and financial factors: when investors feel positive moods they invest and the value of the stock market increases; conversely, when they feel negative moods they do not invest and the value of the stock market decreases. Today, researchers are trying to exploit the data publicly available in social media and, in particular, different researches showed a connection between Twitter messages and the stock market index. In this paper, we do not focus on a generic stock market index, now we focus on the sole sentiment analysis. Instead, our goal is to investigate whether tweet messages can be used to predict the future trend (e.g., positive, negative or neutral) of the stocks of specific companies listed in the Dow Jones stock market. In particular, we focus on companies belonging to three different economic sectors (technology, service and health-care) and we consider the trend of 5 different metrics for each stock (e.g., highest, lowest, opening price, etc.) and the trend of 13 different variables of the tweets (e.g., volume, sentiment, tweets with links, etc.). Through an evaluation that employed more than 800,000 tweets, we show that some of the proposed ad-hoc prediction methods well predict (i.e., up to 82% of success) the next day trend of the stock values of specific companies.

One of the most profitable and emerging high-tech markets is the one that involves games for PC and consoles; a market that is growing year by year and that is rapidly evolving. Several big game corporations are implementing now the remote video streaming through the domestic network between two devices; a feature that regards not only PCs but also consoles. This paper investigates one of the main services of this type, the Steam In-Home Streaming, to analyze the generated network traffic when considering different types of game. Gathered data can help to understand whether this type of service can actually be supported by today's regular Internet connections.

In these last few years we are witnessing a tremendous change in the way video games are developed. On the one hand, large development teams with a multi-layered organisation are employed. On the other hand, we see an increasing request for online services and functionalities. Combining these two trends together usually results in large projects involving parallel and distributed systems. Despite the adoption of team-oriented source code and asset repository managers, code testing and debugging is still left to human direct management. In particular, distributed debugging is a complex problem due to the synchronisation required between network nodes to correctly reconstruct the sequence of events leading to a malfunctioning feature. To solve the aforementioned problem, we designed and implemented DREAD: an architecture to support distributed debugging in real-time games. When adopting our architecture, developers will record events on edge systems, collect them on a centralised sync, and then consolidate everything in a synchronous way. Following this approach, it will be easily possible to detect unexpected software behaviours and trace back to their causes.

In this paper we propose event goodput, i.e., the fraction of events which may be successfully managed by a system, as a relevant metric to describe the performance of battery powered real-time sensor networks. Unlike other performance metrics as response, completion, maximum lateness times, all representing fundamental, but different, figures of merit for the description of the behavior of real-time systems, event goodput provides an immediate and a direct relation with the events which may be satisfactorily managed (or not) by a real-time application. We will show such metric well serves the purpose of describing the performance of battery powered, random event-driven networks, such as sensor networks deployed for surveillance and intrusion detection applications, operating in time critical scenarios. In essence, such real-time systems may be assessed in terms of the fraction of events which they successfully/unsuccessfully detect and report within a time interval of interest. The importance of such metric is here demonstrated providing a simulation model and results where the use of the event goodput metric is discussed in conjunction with those metrics which are traditionally utilized for the assessment of a real-time sensor networks.

Mobile networks are expected to serve a wide range of verticals, however the Long Term Evolution (LTE) network is optimized for basic mobile operator services only. The network functions serving LTE networks are largely implemented as dedicated single function devices that offer poor customization options. This intrinsic inflexibility makes current LTE networks unable to meet the requirements of future mobile networks. For example, LTE networks experience signaling storms because the signals exchanged by the network functions cannot be optimized according to the current usage pattern of mobile services. Modularizing these network functions would enable a refactoring of the LTE network, allowing operators to compose networks that adapt and evolve with the influx of verticals. In this article, we present a new approach for refactoring the network functions serving LTE networks which can be leveraged to compose a modular mobile network optimized for the verticals using its services. As an example, we demonstrate that deploying network functions at the edge significantly reduces the signals exchanged within a mobile network.

Mobile games have come to revolutionize the mobile handset and gaming industry, pushing chip vendors to compete in order to provide better and better graphics capabilities by means of dedicated processors. This capability coupled with the sensing and communication ability offered by smartphones, provides the developers with the building blocks for innovative gaming solutions. In particular, multiplayer mobile games could exploit context and proximity information, providing an added value to the gaming experience. In this context, we present the design and analysis of a modern mobile and multiplayer version of the classic Pong game. In addition to the classic interaction model through remote server(s), players could interact and play locally by exploiting ad-hoc connectivity offered by the Wi-Fi Direct technology.

Among the many uses of Artificial Intelligence techniques in video games, one particularly relevant from the perspective of the entertainment of the player is the ability to mimic believable behaviours in non-playing characters for first-person-shooter games. In our opinion, the solutions commonly adopted in the industry could be improved by simulating decision making under condition of incomplete information. To tackle this aspect, we propose a perspective approach that pairs behaviour trees to a simplified Publisher-Subscribers communication pattern.

Active Queue Management (AQM) techniques have been proposed to support scenarios with many connections sharing the same bottleneck. The basic idea is that a smart management of the bottleneck queue can avoid the saturation of the link and ensure a smoother use of the available bandwidth. This is generally achieved by exploiting the flux control mechanism of TCP and its behavior in case of packet losses or other explicit notifications. In this paper we consider classic and innovative AQM techniques and analyse their performance under different scenarios through the use of mean field models.

Cities have evolved as a natural environment for cars rather than people. This has limited people's ability to move around, living and interacting with the urban space affecting the experienced quality of life. Clearly, this regards all of us and, in particular, people affected by impairments. One of the main barriers in building services to fill the gap between the urban environment and people living in it is surprisingly represented by the lack of information. Think for instance to Google maps; you can ask for a path between any two destinations and you will receive a response with the shortest path whether you are travelling by car, public transportation or just walking. Yet, there is no path or information available regarding people on a wheelchair or blind. Instead, we discuss in this paper how the vast popularity of sensor-endowed smartphones can be exploited to create unprecedented services able to improve the interaction with the environment, the social inclusion and the quality of life.

In these last few years we are witnessing a change in the way video games are implemented. Starting from an early age, where a single developer was sometimes in charge of the whole creative process, we have moved now toward extremely large groups with a multi-layered organisation. This increasing complexity of team organisation, together with a tremendous growth of projects size, calls for the adoptions of development approaches leveraging on scalability and distributed computing environments. Unfortunately, today's development and execution environments for games (usually called game engines) are suffering from a number of architectural constraints. As a result, we strongly believe current engines will not be able to provide the flexibility and scalability required by game developers of the next generation. To overcome the above limitations, in this paper we propose SMASH (Stackless Microkernel Architecture for SHared environments): an architecture where a game engine is decomposed in several dynamic and independent software modules interacting via a microkernel-like message bus. Game modules can just be inserted, debugged, and removed from a running engine once its internal messaging protocol is clearly defined. Moreover, following this approach, game modules can be dynamically dislocated on multiple machines to obtain a truly distributed, scalable, and fault-resilient system where adaptation can be achieved mostly without downtime.

The market penetration of in-home entertainment systems is playing a crucial role in the diffusion of interactive multimedia services. In this context, thin-client game systems have received a lot of attention, shifting the computational burden of the game play toward the server while the client renders a fat video stream. This paper proposes an analysis of the network characteristics of the Remote Play for PlayStation 4 and PlayStation Vita, providing some insights on the network dynamics of this system under different game types. The measurements involve video games of different genres, analyzing the bitrates, the packet size, capturing the dynamics of the whole streaming session. Results indicate that the service generates a large quantity of big packets downstream and smaller and lesser packets upstream. Gathered data can help to understand if this type of service could be offered through the today's normal Internet connections.

This paper investigates one of the main game streaming services, the Steam In-Home Streaming, to analyze the generated network traffic. Gathered data can be used to model this type of traffic in simulations and to determine whether it could be supported by Internet connections around the world.

With vehicular networks quickly becoming the new wireless frontier of the Internet, car passengers embody the next consumers that will be targeted by multimedia content providers. However, researchers and practitioners are still struggling to tackle the technical challenges that raise in this scenario such as, for instance, the continuous variations in the number and type of flows served by the access points along the road. Considering different traveling scenarios in terms of vehicles' speed and location we discuss how access points could be improved to properly address these challenges, ensuring coexistence among heterogeneous types of flow, even in presence of moving vehicles that generate frequent network traffic variations.

Computer-centered services and broadband wireless connectivity have boosted the demand for delivery of multimedia-based entertainment from the Internet to in-house wireless appliances. In this context, rich-media applications can be supported by a variety of protocols, each sharing the same bottleneck, affecting one another's performance. Indeed, in current systems, real-time applications (e.g., video streaming, online games) suffer from delays caused by the interference of elastic, best-effort (e.g., TCP-based download sessions) traffic. In this paper we propose a solution to this problem, addressed by deploying a Vegas-like congestion control algorithm at the home gateway, requiring no client-side modification.

Mobile communication devices are expected to overtake traditional desktop PCs and become the dominant point of entry to the Internet. This technology shift has boosted user demand for multimedia applications and services which are now typically accessed through the wireless interface. Users expect to be always connected and able to run a variety of applications which sometimes impose contrasting requirements. Of particular research interest in this scenario is the coexistence between two popular categories of traffic: elastic and real-time, both of them covering a wide range of user applications. In this paper, we investigate the above issue in the scenario where service connectivity is provided through a multihop wireless network. To this end, we study two representative applications, one for each of the above categories, which are content download and interactive game play. We show by means of extensive simulations, how both the content download's goodput and the online game's per-packet delivery delay can be improved through an appropriate solution implemented on the wireless Internet Gateway.

Recent research has proposed swarming protocols as a possible approach to offload the Internet infrastructure when some content can be shared by several users. However, simulations have been generally used as experimental means. Instead, we present an application platform that allows a rapid development and testing of swarming protocols using off-the-shelf smartphones.

Cloud-based entertainment is gaining momentum. With the cost of commodity hardware lowering by the day and the consumer market penetration of in-house digital entertainment systems, a new generation of interactive services has come into being. This new technological wave has launched new content producers and providers that are rapidly adapting to match the consumer demand. In this context, thin client or cloud-based gaming is attracting much attention, shifting the computational burden to the cloud while the consumer enjoys a fat video feed accessed through its thin client via the shared wireless gateway. However, this model of interaction raises new challenges that demand for specific networking solutions aimed at addressing the heterogeneous flow coexistence problem at the home wireless gateway. We propose a solution to this problem by devising a Transmission Control Protocol Vegas-like congestion control algorithm deployed on top of the home gateway. Our solution works out of the box with the standard protocols at the server, router, and client levels, thereby making deployment straightforward. Experimental assessment with real traffic traces shows that our solution addresses the problem effectively.

ABSTRACT The mobile revolution has brought us the possibility to enjoy our favorite applications anywhere and anytime. In this context, interactive games over mobile networks embody a fascinating case study both for their commercial success and for their technical challenges, thus, sparking interest and development. The current state of the art of interactive games over mobile networks is captured in this article. We discuss main requirements and analyze possible combinations of existing solutions to provide better support for highly interactive game sessions with mobile players. Copyright © 2012 John Wiley & Sons, Ltd.

Sensor-enabled smartphone's have become a mainstream platform for researchers due to their ability to collect and process large quantities of data, hence creating new opportunities for innovative applications. Yet, the limits in employing sensors to opportunistically detect human behaviors are not clear and deserve investigation. To this purpose, in this article, we discuss movement pattern recognition in day-by-day urban street behavior. As a case study, we restrict at recognizing situations when a pedestrian stops, crosses a street ruled by a traffic light; to do so we only use data coming from the accelerometer of the pedestrian's smartphone.

Opportunistic Networking (ON) is an emerging networking paradigm exploiting contact opportunities and node mobility to move data between nodes. Differently from infrastructure networks, where conventional information like network topology could be used to route messages, ON demands for new techniques able to cope with a dynamic evolving network topology and scenarios with limited or no information. Further, the heterogeneity of the autonomous actors involved in the network processes translates into different network protocol constraints which, if not considered carefully could lead to scalability problems of the devised solutions. In this context, in this article, we provide a survey of relevant opportunistic solutions and their motivation, with emphasis on the data gathering and dissemination processes. Despite the major research effort, it emerges there is no one silver bullet.

Infrastructure networks like Internet have some coverage gaps (e.g. rural areas) where no service connectivity is provided. Cellular networks could be used in alternative but they usually associate their services with a usage cost. Nowadays, the growing number of mobile devices equipped with a wireless interface and the end-user trend to shift toward wireless technology has opened new possibilities for networking. Opportunistic networking seems a feasible solution in filling in these coverage gaps by providing service connectivity where it is not sustained by an infrastructure. In this context we provide a delay tolerant platform that ensures service connectivity where it is absent. Our approach follows the Delay/Disruption Tolerant Networking (DTN) paradigm by implementing a store-and-forward communication model between mobile users and carrier entities (e.g. buses), where a user delegates the carrier a task (bundle), the carrier stores it locally and whenever service connectivity is available (e.g. wi-fi at the bus station) tries to accomplish it, successively notifying the user of the task output next time they encounter again.