A smartphone agent for QoE evaluation and user classification over mobile networks

The continuous growth of mobile users and bandwidth-consuming applications and the shortage of radio resources put a serious challenge on how to efficiently exploit existing networks and contemporary improve Quality of Experience. One of the most relevant problem for network operators is thus to find an explicit relationship between QoS and QoE, for the purpose of maximizing the latter while saving precious resources. In order to accomplish this challenging task, we present TeleAbarth, an innovative Android application entirely developed at TelecomItalia Laboratories, able to contemporary collect network measurements and end-users quality feedback regarding the use of smartphone applications. We deployed TeleAbarth in a field experimentation in order to study the relationship between QoS and QoE for video streaming applications, in terms of downstream bandwidth and video loading time. On the basis of the results obtained, we propose a technique to classify user behavior through his or her reliability, sensibility and fairness

Managing big data experiments on smartphones

The explosive number of smartphones with ever growing sensing and computing capabilities have brought a paradigm shift to many traditional domains of the computing field. Re-programming smartphones and instrumenting them for application testing and data gathering at scale is currently a tedious and time-consuming process that poses significant logistical challenges. Next generation smartphone applications are expected to be much larger-scale and complex, demanding that these undergo evaluation and testing under different real-world datasets, devices and conditions. In this paper, we present an architecture for managing such large-scale data management experiments on real smartphones. We particularly present the building blocks of our architecture that encompassed smartphone sensor data collected by the crowd and organized in our big data repository. The given datasets can then be replayed on our testbed comprising of real and simulated smartphones accessible to developers through a web-based interface. We present the applicability of our architecture through a case study that involves the evaluation of individual components that are part of a complex indoor positioning system for smartphones, coined Anyplace, which we have developed over the years. The given study shows how our architecture allows us to derive novel insights into the performance of our algorithms and applications, by simplifying the management of large-scale data on smartphones

A novel on-board Unit to accelerate the penetration of ITS services

In-vehicle connectivity has experienced a big expansion in recent years. Car manufacturers have mainly proposed OBU-based solutions, but these solutions do not take full advantage of the opportunities of inter-vehicle peer-to-peer communications. In this paper we introduce GRCBox, a novel architecture that allows OEM user-devices to directly communicate when located in neighboring vehicles. In this paper we also describe EYES, an application we developed to illustrate the type of novel applications that can be implemented on top of the GRCBox. EYES is an ITS overtaking assistance system that provides the driver with real-time video fed from the vehicle located in front. Finally, we evaluated the GRCbox and the EYES application and showed that, for device-to-device communication, the performance of the GRCBox architecture is comparable to an infrastructure network, introducing a negligible impact