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The availability of network softwarization and virtualization technology in the field of telecommunications has opened the door to a radical review of the applications, protocols, and deployment models. In this evolving framework, old assumptions and constraints specific to satellite communications must be carefully re-assessed. To this aim, we revisit the role of the performance enhancing proxy (PEP), replaced by a chain of custom virtual network functions properly enabled to optimize common web traffic performance over a backhaul dynamically enabled with a supplementary satellite link. The resulting virtual PEP (vPEP) is compliant with the breakthrough virtualization and slicing paradigms and can fruitfully exploit the advanced features of the most recent IETF technologies such as QUIC and MPTCP.

Serverless computing is an emerging proposition in the cloud offering landscape that promotes a higher level of abstraction, further decoupling software operations from the underlying hardware. Often recognized as an economically driven computational approach, the serverless model relies on the execution of short-lived stateless functions, enabling a fine-grained accounting and control of resources. In this context, function composition represents an appealing feature, allowing the composition of two or more functions to create tailored processing pipelines, incentivizingmodularityandreusabilityof functions, while paving the way to application-specific run-time optimizations. This work presents DIFFUSE: a DIstributed and decentralized platForm enabling Function composition in Serverless Environments. DIFFUSE embodies an innovative infrastructural support, enabling the efficient and transparent composition of functions by relying on pluggable middleware support, serving as a conveyor of messages among the platform components. Broadening the deployment spectrum of our proposal, we assess differentmiddleware solutions, each presenting distinct delivery profiles, evidencing the tradeoffs that emerge.

We are still in the midst of Industry 4.0 (I4.0), with more manufacturing lines being labeled as smart thanks to the integration of advanced ICT in Cyber–Physical Systems (CPS). While I4.0 aims to provision cognitive CPS systems, the nascent Industry 5.0 (I5.0) era goes a step beyond, aiming to build cross-border, sustainable, and circular value chains benefiting society as a whole. An enabler of this vision is the integration of data and AI in the industrial decision-making process, which does not exhibit yet a coordination between the Operation and Information Technology domains (OT/IT). This work proposes an architectural approach and an accompanying software prototype addressing the OT/IT convergence problem. The approach is based on a two-layered middleware solution, where each layer aims to better serve the specific differentiated requirements of the OT and IT layers. The proposal is validated in a real testbed, employing actual machine data, showing the capacity of the components to gracefully scale and serve increasing data volumes.

The ubiquity of mobile technology has opened the door to the new era of mobile sensing. Through this new paradigm, physical phenomena can be observed in a distributed way, crowd-sourcing the data measurement tasks to smartphones and/or other popular smart wearables. Mobile sensing and wireless communications can hence be employed to gather data and generate new information and services, benefiting our society. As a proof-of-concept, we have developed a mobile sensing platform able to pervasively collect environmental data. To improve the quality of collected data we have also created an application for pedestrian navigation that works both on smartphones (also using Augmented Reality) and on smartwatches, thus ensuring an appropriate exposition of the mobile device (and its sensors) when collecting data. Furthermore, our navigation app is able to provide users with personalized pedestrian routes that take into account environmental parameters and not only the route length. Finally, we have also devised a web service able to provide graphical visualization and historical evolution of sensed data.

When COVID-19 first struck the provinces of Northern Italy in early 2020 (especially in Lombardy and in EmiliaRomagna), the conditions there made it a perfect storm. The virus outbreak spread with an unusual violence (in the period from late February to April 2020), with a catastrophic toll in terms of human deaths. Taken by surprise, Italy mandated a complete nation-wide lockdown, successively resorting to ministerial decrees alleviating and postponing the restrictions. Now more than ever, there is an increased awareness on ICT used to combat the pandemic. In this article, we present a quantitative analysis evidencing the impact of restrictions on mobility. To this end, we rely on a vehicular mobility dataset confined in the downtown area of Bologna, Italy. Pursuing the objective, we propose a modified version of a state-of-theart data mining algorithm, allowing us to efficiently identify and quantify mobility flows. The proposal, if combined with additional data sources, could allow for a fine-grained and timely decision making, combating the pandemic.

The ever increasing pace of IoT deployment is opening the door to concrete implementations of smart city applications, enabling the large-scale sensing and modeling of (near-)real-time digital replicas of physical processes and environments. This digital replica could serve as the basis of a decision support system, providing insights into possible optimizations of resources in a smart city scenario. In this article, we discuss an extension of a prior work, presenting a detailed proof-of-concept implementation of a Digital Twin solution for the Urban Facility Management (UFM) process. The Interactive Planning Platform for City District Adaptive Maintenance Operations (IPPODAMO) is a distributed geographical system, fed with and ingesting heterogeneous data sources originating from different urban data providers. The data are subject to continuous refinements and algorithmic processes, used to quantify and build synthetic indexes measuring the activity level inside an area of interest. IPPODAMO takes into account potential interference from other stakeholders in the urban environment, enabling the informed scheduling of operations, aimed at minimizing interference and the costs of operations.

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 by stateless solutions, 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 a tabu search approach, 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.

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.

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) multi-cloud 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.

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.

Immersive technology is expected to become a key player in the next wave of consumer electronics with potential applications spanning a wide variety of sectors. Yet, there are a number of technological hurdles which need to be addressed. Without speed and computation capability, interactivity cannot be ensured. More than often the constrained nature of the mobile device demands is complemented by cloud ones through the use of cloud offloading techniques. With cloud offloading, battery consumption and processing performance problems are translated into sensor data selection and network latency problems. In this context, we focus our study on some functional building blocks that can be used in conjunction and deployed in a 5G virtualized architecture to alleviate bandwidth and latency requirements of immersive application scenarios. To this end, we have created an experimental scenario exploiting real data to test our combined solution based on the field of view cut and optimized transport protocols, discussing the tradeoffs that emerge.

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.

Automated Guided Vehicles (AGVs) are increasingly being employed in logistics to carry out tiring and repetitive tasks inside large industrial buildings. In these settings, AGVs perform more efficiently than human workers in that they exhibit no signs of fatigue, their movements can be tracked automatically and their path can be timed to feed/collect objects in a quasi-predictable time frame and to even perform some object manipulations/refinement during transportation. In this article, we present a simulation analysis assessing the feasibility of commodity WiFi for operations control in an autonomous production site. In this context, AGVs and infrastructure endpoints are involved in periodic data exchange, the later gathering and acting upon AGV health data in order to ensure the systems operations continuity. To this end, we have setup a realistic simulation scenario mimicking the sites’ operational environment discussing some trade-offs that emerge.

In this paper, we propose GeoSaW, a delay-tolerant routing protocol for Airborne Networks in Search and Rescue scenarios. The protocol exploits the geographical information of UAVs to make appropriate message forwarding decisions. More precisely, the information about the future UAV&rsquo, s motion path is exploited to select the best UAV carrying the message towards the destination. Simulation results show that the proposed solution outperforms the classic DTN routing protocols in terms of several performance metrics.

We discuss MDTN: a delay tolerant application platform built on top of the Public Transportation System (PTS) and able to provide service access while exploiting opportunistic connectivity. Our solution adopts a carrier-based approach where buses act as data collectors for user requests requiring Internet access. Simulations based on real maps and PTS routes with state-of-the-art routing protocols demonstrate that MDTN represents a viable solution for elastic nonreal-time service delivery. Nevertheless, performance indexes of the considered routing policies show that there is no golden rule for optimal performance and a tailored routing strategy is required for each specific case.

The number of physical objects connected to the Internet constantly grows and a common thought says the IoT scenario will change the way we live and work. Since IoT technologies have the potential to be pervasive in almost every aspect of a human life, in this paper, we deeply analyze the IoT scenario. First, we describe IoT in simple terms and then we investigate what current technologies can achieve. Our analysis shows four major issues that may limit the use of IoT (i.e., interoperability, security, privacy, and business models) and it highlights possible solutions to solve these problems. Finally, we provide a simulation analysis that emphasizes issues and suggests practical research directions.

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.

[EN] Flying ad-hoc networks are becoming a promising solution for different application scenarios involving unmanned aerial vehicles, like urban surveillance or search and rescue missions. However, such networks present various and very specific communication issues. As a consequence, there are several research studies focused on analyzing their performance via simulation. Correctly modeling mobility is crucial in this context and although many mobility models are already available to reproduce the behavior of mobile nodes in an ad-hoc network, most of these models cannot be used to reliably simulate the motion of unmanned aerial vehicles. In this article, we list the existing mobility models and provide guidance to understand whether they could be actually adopted depending on the specific flying ad-hoc network application scenarios, while discussing their advantages and disadvantages.

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.

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.

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.

The Internet edge has evolved from a simple consumer of information and data to eager producer feeding sensed data at a societal scale. The crowdsensing paradigm is a representative example which has the potential to revolutionize the way we acquire and consume data. Indeed, especially in the era of smartphones, the geographical and temporalscopusof data is often local. For instance, users’ queries are more and more frequently about a nearby object, event, person, location, and so forth. These queries could certainly be processed and answered locally, without the need for contacting a remote server through the Internet. In this scenario, the data is alimented (sensed) by the users and, as a consequence, data lifetime is limited by human organizational factors (e.g., mobility). From this basis, data survivability in the Area of Interest (AoI) is crucial and, if not guaranteed, could undermine system deployment. Addressing this scenario, we discuss and contribute with a novel protocol named AirCache, whose aim is to guarantee data availability in the AoI while at the same time reducing the data access costs at the network edges. We assess our proposal through a simulation analysis showing that our approach effectively fulfills its design objectives.

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.

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.

Testing Vehicular Network protocols can be quite problematic. In fact, vehicular experiments are often expensive in both economic and temporal terms. As a consequence, researchers generally resort to software simulations which are a neccessary first step but still not sufficient. In this paper, we present two possible experimentation frameworks that could give a boost to the testing of protocols for vehicular networks: the first framework is based on Android smartphones, while the second is based on commodity laptop computers. In order to assess the feasibility and the performance of the proposed frameworks, we implemented through them a representative vehicle-to-vehicle multi-hop broadcast algorithm, i.e., the Fast Broadcast algorithm.

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.

Mobile Ad-hoc Networks (MANETs) exhibit unpredictable topology with heterogeneous node contact rates, high mobility and limited information. When dealing with such challenging environments, the mobility model has a key role in testing the performance and proving the expected behavior of routing algorithms. While synthetic mobility models have been largely used to measure quantitative aspects of routing protocols, they are not sufficient as they do not capture reliably the properties of movement in the real life scenarios. In this paper we present some experimentation done in THE_ONE simulation environment, involving our M2MShare, a peer-to-peer (P2P) delay tolerant file sharing platform for mobile networks. For testing purposes we have chosen the Working Day Movement (WDM) model which is shown to make a good approximation of human mobility patterns and provides the flexibility of configuring real life test scenarios.

Mobile phones have already evolved from simple voice communication means into a powerful device able to handle multimedia documents, personal productivity applications, and all sort of connections to the Internet. It is hence expected to see a popular application such as file sharing to become widely utilized even in this context. Indeed, the combination among mobile users and file sharing seems a match made in heaven: people could exchange files of interest just passing by each other. Moreover, new context related applications may be developed to exploit this possibility enriching our lives. In this work, we present design issues and implementation details about a real P2P file sharing application for mobile phones.