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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.

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.

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.

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.

The fast-paced evolution of ICT technology is revolutionizing our every day life, endowing us with a seamless digital assistant accessible through smart-devices. In this context, even the way we approach tourism and holidays has undergone many changes. In fact, most of us nowadays exploit smart devices to plan, book and manage the experience. This different approach to tourism is often called Smart Tourism and it is acquiring more and more importance for business, public administrations, and tourists themselves. The idea behind our proposal is to further enhance existing structure and services of a city, promoting and encouraging the smart tourism concept while satisfying the ever increasing necessity, dynamicity and stringent Quality of Service (QoS) requirements future application scenarios embody. To this end, we propose a conceptual architectural model following a Mobile Edge Computing (MEC) approach, exploiting virtualization and multiple geographically distributed Function as a Service (FaaS) edge clouds equipped with storage capabilities. While preserving the general aspect of our study and without loss of generality, we envision a reference scenario where users consume and produce data that are geographically bound to a location of interest. This modus operandi could help unlock smart tourism potential, focusing on local communal phenomena, harvesting socio-technical data which would otherwise not be possible on a global scale through traditional centralized information systems. Along with the proposal, we discuss some preliminary evaluation of the envisioned platform, outlining some research directions.

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.

Augmented and virtual reality technology are expected to become key technological players in the next wave of consumer electronics with potential applications spanning a wide variety of economic sectors. Yet, there are a number of technological hurdles which need to be addressed. Without speed and computation capability interactivity cannot work. More than often the constrained nature of the mobile device demands are 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 a network function which could be deployed in a 5G virtualized architecture to alleviate bandwidth requirements of immersive application scenarios. To this end, we rely on a real dataset, providing user-centric metadata on several 4k, 360-degree videos. Different computational methods are proposed and contrasted, evidencing the goodput of the approaches.

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.

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.

Recent market trends in self-driving technology have revived the attention on vehicular networks, posing a demand for intelligent solutions supporting the proliferation of many useful applications. Inter-vehicular communication presents an opportunity, capable of providing the basis for localized, timely, collective intelligence. In this context, critical safety applications are particularly challenging, urging for quick multi-hop message propagation schemes within an area of interest. The anycast communication model embodied by safety applications and the shared broadcast medium demand for intelligent message propagation schemes minimizing latency. To this end, the state of the art approach is based on having different contention windows among vehicles so as to probabilistically select specific ones as forwarders in order to reduce the number of hops and transmissions needed to propagate the message. However, this solution has been mainly studied empirically. In this article, we present and discuss an analytical model, shedding light on the expected behavior and performance of such approach, along with a validation analysis conducted through the well known simulator NS-2.

The Internet edge has evolved from a simple consumer of information and data to an eager producer feeding data at a societal scale. This change in paradigm embodies a burden for service providers in terms of constant maintenance and upgrade of infrastructure. The Edge Computing paradigm addresses the issue by shifting the computational burden at the network edge, gathering and analyzing data where it is produced. In this context, we present a feasibility analysis of an autonomous production site comprised of multiple mobile rovers and infrastructure endpoints, both involved in periodical information exchange under different duty cycling regimes. Infrastructure Access Points (APs) are positioned in-situ gathering and analyzing data, ensuring the system correct behavior. In this article, we discuss the experimental setup and the carried simulation analysis evidencing the tradeoffs that emerge.

We present the design and implementation aspects of a virtualized Performance Enhancing Proxy (vPEP), in a 5G compliant architecture involving the satellite as an alternate, additional backhaul link. The deployment of hybrid terrestrial-satellite configurations is realized through the vPEP agent, meant as a chain of Virtual Network Functions (VNFs), enhancing protocol performance and/or bringing value-added services in the end-to-end path. To this end, we discuss a possible integration approach of the satellite link into the 5G service-based architecture, outlining key functional components. In addition, we present a preliminary evaluation study employing a vPEP embodying the QUIC protocol in a possible web-browsing, 5G optimized slice.

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.

Unmanned aerial vehicles (UAV), or commonly referred to as Drones, have captured our imagination bringing new and challenging service provisioning schemes into the networking scenario. We might indeed be reaching the day where communication-enabled drones might be employed in synergy with deployed public networks offering alternate service access means. In this context, we contribute with quantitative analysis of classic routing algorithms in a 3D mobile environment, shedding some light on their performance tradeoffs.

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.

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.

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.

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.

Many enchanting cultural heritage locations are hidden from tourists, especially when considering countries full of historic attractions. Tourists tend to consider only mainstream monuments and towns, neglecting wonderful little jewels along their travel itinerary. However, this is generally not their fault, as travelers cannot be aware of all the surrounding beauties when visiting a new region. To this aim, we discuss and analyze here PhotoTrip, an interactive tool able to autonomously recommend charming, even if not mainstream, cultural heritage locations along travel itineraries. PhotoTrip is able to identify these points of interest by gathering pictures and related information from Flickr and Wikipedia and then provide the user with suggestions and recommendations. An important technical challenge for this kind of services is the ability to provide only the most relevant pictures among the many available for any considered itinerary. To this aim, we have exploited social networks, crowdsourcing and gamification to involve users in the process of improving the response quality of our system.

[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.

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.

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.

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 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.

Internetworking often requires a large amount of users to share a common gateway to obtain connectivity to the Internet. Congestion avoidance mechanisms are used to prevent the saturation of the gateway which represents a bottleneck of the system. The most popular congestion avoidance mechanisms are the Explicit Congestion Notification (ECN) and the Random Early Detection (RED). Recently, a new method for the congestion avoidance has been proposed: the Smart Access Point with Limited Advertised Window (SAP-LAW). The main idea is to hijack the acknowledge packets in the TCP connections in order to artificially reduce the advertised destination window according to some bandwidth allocation policy. Therefore, the flux control mechanism is artificially exploited to control the congestion at the bottleneck. The advantage of this approach is that it does not require any modification in the TCP implementations at the clients. In this paper, we propose stochastic models for the ECN/RED and SAP-LAW mechanisms in order to compare their performances under different scenarios. The models are studied in mean field regime, i.e., under a great number of TCP connections and UDP based transmissions. Augmenting previous work on ECN/RED, we consider the presence of UDP traffic with bursts, and short lived TCP connections. The models for SAP-LAW are totally new. The comparison is performed in terms of different performance indices including average queue length, system throughput and expected queuing time.

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.

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.

In recent years, the number of appliances connected to the Interned has steadily increased thanks to the wide popularity of WIFI/3G enabled mobile devices. This has led to an increase of multimedia resource consumption, causing traffic overload problems for classic resource providers. Different solutions have been studied to shift this traffic overhead from the server(s) towards the client(s) through the employment of the so called swarming protocols. However, most of these solutions have been verified only through simulations. While simulations consist in a necessary first step, they can be far from the actual outcome of employing real protocols and devices. To this end, in this paper we describe BlueFall, an application that could allow to test swarming protocols using actual mobile phones. Pursuing our goal, we provide some preliminary evidence on two simple swarming schemes we have implemented in our testbed.

In these last years we are witnessing a growing availability of personal mobile devices equipped with short-range communication technologies. This new technology wave is pushing for innovative services based on location and context which are difficult to provide by means of the classical 3G networks infrastructure. Among these new services, portable games based on contact are already moving down this path and extending to a large, urban and multiplayer scale thanks to the exploitation of Delay Tolerant and Opportunistic Networks. In this paper we contribute with practical directions to game designers about constraints impacting on gameplay and game mechanics when designing the above games for an urban-wide scale. Our investigation is also performed by means of simulations on the topology of a real city in order to estimate technical bounds to the practical design of compelling games.

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.

When discussing vehicular networking we have also to consider the multitude of commuters daily travelling to work through public transportation means such as buses, metros, and trains. Indeed, through their smartphones, commuters can generate communication traffic while moving, thus embodying a significant part of an urban communication scenario. In this context, we discuss in this article a way to port the P2P paradigm into mobile disconnected networks composed by commuters’ smartphones. Different from classical P2P file-sharing systems, our solution is designed to specifically leverage on the mobility pattern of commuters. In essence, users can exchange multimedia contents when in proximity with each other; they can also leverage on peer mobility and encounters in order to extend a requesting peer reacharea to other local disconnected networks. This is achieved by implementing a DTN-like store-delegate-and-forward communication model over underlying social networks where a peer can delegate unaccomplished file download tasks to frequently encountered peers: e.g., other commuters sharing a part of the path between home and workplace. We show how involving only frequently encountered peers/commuters improves the success ratio for the file search task while reducing useless communication overhead.

Mobile phones are offering a wide set of functionalities capable of improving the user way of communicating with the world. Due to user mobility and to the inherent ubiquity of these devices, social relations are now being created and maintained using mobile social applications. To this aim, in this work, we present our application Nudge Nudge, a proximity based social application which aims to connect close people in both terms of geographic distance and personality.

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.