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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.

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.

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.

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.

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.

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 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.

In this contribution, the most widely-used and popular cryptographic algorithms, both symmetric and asymmetric, are compared in terms of security, and in terms of performance and efficiency when implemented in MATLAB. Among symmetric algorithms, Data Encryption Standard (DES) and Advanced Encryption Standard (AES) are taken into consideration, and among asymmetric algorithms, the RSA cipher is analyzed. Following that, encryption issues in smart traffic control systems are discussed, and the possibility of integrating the studied cryptographic algorithms to those systems is introduced. Lastly, the paper suggests an advanced time-plan in order to optimize the traffic signal timing based on different demand patterns on different time-intervals of the day, while eliminating the encryption and decryption burdens by using different techniques like pipelining and queueing.

The advent of broadband technology has revolutionized the fruition of multimedia contents. Moreover, the cloud is now moving the computational load from domestic devices to remote servers, enabling the provisioning of new multimedia services through the Internet. To provide a proper user experience, a low E2E latency and a high bandwidth are both required. Unfortunately, this is difficult to achieve in a shared network like the Internet. My PhD project focuses on the study and analysis of modern network protocols to identify viable solutions for a suitable user experience.

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.

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.

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.

In our work, a Field-programmable gate array (FPGA) based architecture for compressive sensing using Orthogonal Matching Pursuit (OMP) algorithm is suggested. The storing and transmission of data is done and it will be made efficient when the sampled signal is compressed. In this technique of compressive sensing, the demerits of directly achieving compressed signal without coming across any transitional stage by considering all samples is reduced. Reconstruction of sampled data will be done using numerical computing intensive theorems which has many flaws.Implementation of Reconstruction stage is complex software implementation of these algorithms is awfully slow and consumption of the power will be more as the system has large number of layers due to most of the resource sharing at multiple levels.Contrarily implementation in hardware has much advantage in hardware parallelism, ability of creating custom data path and hardware dedication for each task. In proposed method hardware implementation OMP algorithm is utilized because of its shorter computation time and low complex nature. The main objective of the proposed method is to implement an OMP algorithm to optimize essential reconstruction time without negotiating intended accuracy.

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 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.

In the recent years, ICT use in vehicular technology has expanded very fast. Inter-vehicle communication (IVC) is seen as the natural next step in this evolution whose availability will give rise to the next generation of smart vehicles. As this technology is deployed, a wide range of services varying from safety to entertainment will become factually accessible to passengers. Many of these envisaged services require a one-to-many communication model which demand for intelligent solutions able to propagate the message in areas of the network where it has not been heard before. To this end, we propose an enhancement of an existent optimal message propagation scheme proposed in the context of one dimensional vehicular networks, namely Fast-Broadcast. Our proposal generalizes the former with the objective of guiding message dissemination to an entire area of interest in generic road topologies. Our proposed scheme exploits bloom filter properties to further advance message propagation into the network. We contrast our approach with the original, lightweight state-of-the-art proposal, showing that it fulfills its design objectives.

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.

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.

Scalable routing for ad-hoc wireless systems is a compelling and challenging task. In particular, due to mobility of nodes, topological information is volatile and changes in time. In this context, routing algorithms exploiting geographic information have been proposed to address this issue. This class of protocols exploits nodes' location, rather than their address and routing tables, to greedily route data towards a destination. Mainly proposed and tuned in the context of 2D MANETs these protocols exhibit less overhead in terms of control traffic and state, however, they are susceptible to local minina due to their localized decision making. In this context, we propose a hybrid position-topology based algorithm named Greedy Distance Vector (GDV), which tries to strike a balance between a greedy and topology-based forwarding process in a 3D environment. GDV greedily routes data packet toward a destination by exploiting nodes coordinates and whenever a local minima is found shifts to a topology, reactive-based approach to recover the delivery process. We present a preliminary simulation and discuss the benefits of the approach.

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.

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.

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.

The technological evolution in the mobile sector has experienced an exponential growth in the last years. The number of functionalities has grown, and of course the way we use these devices has changed. Starting with calls and messages, introducing cameras, implementing Internet connectivity, and finally introducing the sensor technology, we arrive to today's smartphones. Following this trend, a popular application as gaming has extended its domain from home computers and consoles to the mobile realm. While there are many developers working on modern game genres, we devised a mobile game that join the rediscovery of ancient board games with the pleasure to play on a smart device. Through the development of the digital version of a game that was played centuries ago, we have created a very attractive tool able to raise the interest of children toward ancient history. We hence discuss here our attempt to digitally rediscover and enhance an ancient board game called "Fox and Geese"

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.

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.

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.

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.

Most of the current embedded systems operate on digital domain even though input and output is analog in nature. All these devices contain ADC (Analog to Digital converter) to convert the analog signal in to digital domain which is used for processing as per the application. Images, videos and other data can be exactly recovered from a set of uniformly spaced samples taken at the Nyquist rate. Due to the recent technology signal bandwidth is becoming wider and wider. To meet the higher demand, signal acquisition system need to be improved. Traditional Nyquist rate which is used in signal acquisition suggests taking more numbers of samples to increase the bandwidth but while reconstruction most of the samples are not used. If samples are as per Nyquist rate then, this increases the complexity of encoder, storage of samples and signal processing. To avoid this new concept Compressive Sensing is used as an alternative for traditional sampling theory. This paper presents a survey and simplified theoretical view on compressive sensing and reconstruction and proposed work is introduced.

ADC (Analog to Digital Converter) which follows the Nyquist rate has changed signal processing. Most of the real time applications required too many samples if Nyquist rate is followed. This may involve more cost or even practically not feasible to build systems capable of acquiring samples at Nyquist rate. Compressive Sensing (CS) is a recent trend emerged as a better concept than Nyquist technique by enabling reconstruction of sparse signals which are acquired bellow Nyquist rate. The authors propose reconstruction of Image using Compressive Sensing Technique. Various matrices like Partial Hadmard, Bernoulli Matrix, Uniform Spherical and Random Matrix with proper threshold are used. The reconstruction time, SNR and MSE are measured. Experiments are carried on various sized image with Foreward Hadmard Transform. The experimental results show that for an image of size 256×256 the reconstruction time is 9 sec with signal to noise ratio 23 dB. For inage of size 512×512 the reconstruction time is 15 sec with signal to noise ratio as 26dB. This gives the opportunity to build CS hardware as an alternative for ADC.

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.

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.

Online social networks (OSN) have revolutionized many aspects of our daily lives and have become the predominant platform where content is consumed and produced. This trend coupled with recent advances in the field of Artificial Intelligence (AI) have paved the way to many interesting features, enriching user experience in these social platforms. Photo sharing and tagging is an important activity contributing to the social media data ecosystem. These data once labeled constitute a fruitful input for the system which is exploited to better the services of interest to the user. However, these labeling activity is imperfect and user subjective, hence prone to errors inherent to the process. In this paper, we present the design and the analysis of an Android app (namely GHio-Ca), an automatic photo tagging service relying on state-of-the-art image recognition APIs. The application is presented to the user as a camera app used to share pictures on social networks while relying on external services to automatically retrieve tags best representing the picture theme. Along with the system description we present a user evaluation involving 30 subjects.

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.

Cloud-based entertainment is becoming a hot topic for researchers and practitioners. In this context, thin client or cloud based gaming promise to attract users with the possibility to dematerialize the console and let the user play any possible game for any platform through the Internet. Basically, the computational burden is left to the cloud while the user enjoys a fat video feed accessed through her/his thin client via the shared wireless gateway. Unfortunately, this model of interaction also raises new complex technical issues that requires specific networking solutions. In this short paper we aim at addressing the heterogeneous flow coexistence problem at the home wireless gateway. We propose a solution based on a TCP Vegas-like congestion control algorithm deployed on top of the home gateway. Our solution works out of the box with the standard protocols at server, router and client level, thereby making deployment straightforward.