Nowadays, people usually connect to the Internet through a multitude of different devices. Video streaming takes the lion's share of the bandwidth, and represents the real challenge for the service providers and for the research community. At the same time, most of the connections come from indoor, where Wi-Fi already experiences congestion and coverage holes, directly translating into a poor experience for the user. A possible relief comes from the TV white space (TVWS) networks, which can enhance the communication range thanks to sub-GHz frequencies and favorable propagation characteristics, but offer slower datarates compared with other 802.11 protocols. In this paper, we show the benefits that TVWS networks can bring to the end user, and we present CABA, a connection aware balancing algorithm able to exploit multiple radio connections in the favor of a better user experience. Our experimental results indicate that the TVWS network can effectively provide a wider communication range, but a load balancing middleware between the available connections on the device must be used to achieve better performance. We conclude this paper by presenting real data coming from field trials in which we streamed an MPEG dynamic adaptive streaming over HTTP video over TVWS and Wi-Fi. Practical quantitative results on the achievable quality of experience for the end user are then reported. Our results show that balancing the load between Wi-Fi and TVWS can provide a higher playback quality (up to 15% of average quality index) in scenarios in which the Wi-Fi is received at a low strength.

This paper presents an Android application exploiting a collaborative multi-RAT approach (cellular and Wi-Fi Radio Access Technologies) for adaptively streaming video content. The application has been developed and tested on real Android devices of different vendors. Each device coordinates with the others to download portions of a video stream through its own preferred RAT, and shares the results with the neighboring devices through a proximity, high bit rate network based on Wi-Fi Direct. As a result, the aggregate bandwidth available to the group of collaborating devices allows a faster download and a higher quality of video playback streaming, with respect to what is achievable by a single device. The application is designed to exploit common Android devices along with the key functionalities of an Information Centric Network: routing-by-name, in-network caching and multicasting.

The spectrum scarcity is a known problem for a multitude of services. Several bands have been licensed, and nowadays it is difficult to find unused spectrum. Cognitive radio networks have been proposed as a possible solution to contrast the experienced spectrum scarcity. One case of particular interest come from the scarce utilization of TV frequencies, which form the so-called TV White Spaces. In this paper we investigate the utilization of occupied frequencies by secondary devices for indoor communication. We conduct spectrum measurements to quantify the availability of spectrum, and study how indoor communications could impact the DTV receiver. We show that this portions of spectrum, called gray spaces, can be utilized under certain circumstances, for example in highly populated areas, which is the scenario in which it is harder to find TV White Spaces. Simulation studies show the impact gray spaces can have on the available spectrum for opportunistic use.

Nowadays, large volumes of commercials reach the desks of executives magnifying the potentials of this new discipline. This is probably the first time in which we recognize our need for a data mining tool, our questions being: "what have all these tools and services in common, which of them are market leaders and which of them offer the best functionalities?" Text data bases, for instance, like commercials, news, and summaries can be classified by programs that without a real understanding of the text can separate them into homogeneous groups. This is achieved through a combination of conceptual clustering and frequency analysis on words. This application is by no means exclusively related to telecommunications, everybody can rely on data providers for almost any kind of phenomena, from retail sites to goods movements among harbours. External data are a considerable mass and this is common to other industries as well, but probably none with the same amount as Telecommunications. Internal data are generated by all the transactions happening over the network. At this stage the only problem left seems to be the exploitation of all the available data.