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

The 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.

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.

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.

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.

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.