Application Platforms for the Internet of Things: Theory, Architecture, Protocols, Data Formats, and Privacy

The Internet of Things (IoT) is the next industrial revolution: we will interact naturally with real and virtual devices as a key part of our daily life. This technology shift is expected to be greater than the Web and Mobile combined. As extremely different technologies are needed to build connected devices, the Internet of Things field is a junction between electronics, telecommunications and software engineering. Internet of Things application development happens in silos, often using proprietary and closed communication protocols. There is the common belief that only if we can solve the interoperability problem we can have a real Internet of Things. After a deep analysis of the IoT protocols, we identified a set of primitives for IoT applications. We argue that each IoT protocol can be expressed in term of those primitives, thus solving the interoperability problem at the application protocol level. Moreover, the primitives are network and transport independent and make no assumption in that regard. This dissertation presents our implementation of an IoT platform: the Ponte project. Privacy issues follows the rise of the Internet of Things: it is clear that the IoT must ensure resilience to attacks, data authentication, access control and client privacy. We argue that it is not possible to solve the privacy issue without solving the interoperability problem: enforcing privacy rules implies the need to limit and filter the data delivery process. However, filtering data require knowledge of how the format and the semantics of the data: after an analysis of the possible data formats and representations for the IoT, we identify JSON-LD and the Semantic Web as the best solution for IoT applications. Then, this dissertation present our approach to increase the throughput of filtering semantic data by a factor of ten.

The twofold role of Cloud Computing in Digital Forensics: target of investigations and helping hand to evidence analysis

This PhD thesis discusses the impact of Cloud Computing infrastructures on Digital Forensics in the twofold role of target of investigations and as a helping hand to investigators. The Cloud offers a cheap and almost limitless computing power and storage space for data which can be leveraged to commit either new or old crimes and host related traces. Conversely, the Cloud can help forensic examiners to find clues better and earlier than traditional analysis applications, thanks to its dramatically improved evidence processing capabilities. In both cases, a new arsenal of software tools needs to be made available. The development of this novel weaponry and its technical and legal implications from the point of view of repeatability of technical assessments is discussed throughout the following pages and constitutes the unprecedented contribution of this work

MCAO for Extremely Large Telescopes: the cases of LBT and E-ELT

Several MCAO systems are under study to improve the angular resolution of the current and of the future generation large ground-based telescopes (diameters in the 8-40 m range). The subject of this PhD Thesis is embedded in this context. Two MCAO systems, in dierent realization phases, are addressed in this Thesis: NIRVANA, the 'double' MCAO system designed for one of the interferometric instruments of LBT, is in the integration and testing phase; MAORY, the future E-ELT MCAO module, is under preliminary study. These two systems takle the sky coverage problem in two dierent ways. The layer oriented approach of NIRVANA, coupled with multi-pyramids wavefront sensors, takes advantage of the optical co-addition of the signal coming from up to 12 NGS in a annular 2' to 6' technical FoV and up to 8 in the central 2' FoV. Summing the light coming from many natural sources permits to increase the limiting magnitude of the single NGS and to improve considerably the sky coverage. One of the two Wavefront Sensors for the mid- high altitude atmosphere analysis has been integrated and tested as a stand- alone unit in the laboratory at INAF-Osservatorio Astronomico di Bologna and afterwards delivered to the MPIA laboratories in Heidelberg, where was integrated and aligned to the post-focal optical relay of one LINC-NIRVANA arm. A number of tests were performed in order to characterize and optimize the system functionalities and performance. A report about this work is presented in Chapter 2. In the MAORY case, to ensure correction uniformity and sky coverage, the LGS-based approach is the current baseline. However, since the Sodium layer is approximately 10 km thick, the articial reference source looks elongated, especially when observed from the edge of a large aperture. On a 30-40 m class telescope, for instance, the maximum elongation varies between few arcsec and 10 arcsec, depending on the actual telescope diameter, on the Sodium layer properties and on the laser launcher position. The centroiding error in a Shack-Hartmann WFS increases proportionally to the elongation (in a photon noise dominated regime), strongly limiting the performance. To compensate for this effect a straightforward solution is to increase the laser power, i.e. to increase the number of detected photons per subaperture. The scope of Chapter 3 is twofold: an analysis of the performance of three dierent algorithms (Weighted Center of Gravity, Correlation and Quad-cell) for the instantaneous LGS image position measurement in presence of elongated spots and the determination of the required number of photons to achieve a certain average wavefront error over the telescope aperture. An alternative optical solution to the spot elongation problem is proposed in Section 3.4. Starting from the considerations presented in Chapter 3, a first order analysis of the LGS WFS for MAORY (number of subapertures, number of detected photons per subaperture, RON, focal plane sampling, subaperture FoV) is the subject of Chapter 4. An LGS WFS laboratory prototype was designed to reproduce the relevant aspects of an LGS SH WFS for the E-ELT and to evaluate the performance of different centroid algorithms in presence of elongated spots as investigated numerically and analytically in Chapter 3. This prototype permits to simulate realistic Sodium proles. A full testing plan for the prototype is set in Chapter 4.

Dynamic power management: from portable devices to high performance computing

Electronic applications are nowadays converging under the umbrella of the cloud computing vision. The future ecosystem of information and communication technology is going to integrate clouds of portable clients and embedded devices exchanging information, through the internet layer, with processing clusters of servers, data-centers and high performance computing systems. Even thus the whole society is waiting to embrace this revolution, there is a backside of the story. Portable devices require battery to work far from the power plugs and their storage capacity does not scale as the increasing power requirement does. At the other end processing clusters, such as data-centers and server farms, are build upon the integration of thousands multiprocessors. For each of them during the last decade the technology scaling has produced a dramatic increase in power density with significant spatial and temporal variability. This leads to power and temperature hot-spots, which may cause non-uniform ageing and accelerated chip failure. Nonetheless all the heat removed from the silicon translates in high cooling costs. Moreover trend in ICT carbon footprint shows that run-time power consumption of the all spectrum of devices accounts for a significant slice of entire world carbon emissions. This thesis work embrace the full ICT ecosystem and dynamic power consumption concerns by describing a set of new and promising system levels resource management techniques to reduce the power consumption and related issues for two corner cases: Mobile Devices and High Performance Computing.

Opportunistic Data Gathering and Dissemination in Urban Scenarios

In the era of the Internet of Everything, a user with a handheld or wearable device equipped with sensing capability has become a producer as well as a consumer of information and services. The more powerful these devices get, the more likely it is that they will generate and share content locally, leading to the presence of distributed information sources and the diminishing role of centralized servers. As of current practice, we rely on infrastructure acting as an intermediary, providing access to the data. However, infrastructure-based connectivity might not always be available or the best alternative. Moreover, it is often the case where the data and the processes acting upon them are of local scopus. Answers to a query about a nearby object, an information source, a process, an experience, an ability, etc. could be answered locally without reliance on infrastructure-based platforms. The data might have temporal validity limited to or bounded to a geographical area and/or the social context where the user is immersed in. In this envisioned scenario users could interact locally without the need for a central authority, hence, the claim of an infrastructure-less, provider-less platform. The data is owned by the users and consulted locally as opposed to the current approach of making them available globally and stay on forever. From a technical viewpoint, this network resembles a Delay/Disruption Tolerant Network where consumers and producers might be spatially and temporally decoupled exchanging information with each other in an adhoc fashion. To this end, we propose some novel data gathering and dissemination strategies for use in urban-wide environments which do not rely on strict infrastructure mediation. While preserving the general aspects of our study and without loss of generality, we focus our attention toward practical applicative scenarios which help us capture the characteristics of opportunistic communication networks.