Architectures for Context Aware Services in Smart Environments

This thesis deals with Context Aware Services, Smart Environments, Context Management and solutions for Devices and Service Interoperability. Multi-vendor devices offer an increasing number of services and end-user applications that base their value on the ability to exploit the information originating from the surrounding environment by means of an increasing number of embedded sensors, e.g. GPS, compass, RFID readers, cameras and so on. However, usually such devices are not able to exchange information because of the lack of a shared data storage and common information exchange methods. A large number of standards and domain specific building blocks are available and are heavily used in today's products. However, the use of these solutions based on ready-to-use modules is not without problems. The integration and cooperation of different kinds of modules can be daunting because of growing complexity and dependency. In this scenarios it might be interesting to have an infrastructure that makes the coexistence of multi-vendor devices easy, while enabling low cost development and smooth access to services. This sort of technologies glue should reduce both software and hardware integration costs by removing the trouble of interoperability. The result should also lead to faster and simplified design, development and, deployment of cross-domain applications. This thesis is mainly focused on SW architectures supporting context aware service providers especially on the following subjects: - user preferences service adaptation - context management - content management - information interoperability - multivendor device interoperability - communication and connectivity interoperability Experimental activities were carried out in several domains including Cultural Heritage, indoor and personal smart spaces – all of which are considered significant test-beds in Context Aware Computing. The work evolved within european and national projects: on the europen side, I carried out my research activity within EPOCH, the FP6 Network of Excellence on “Processing Open Cultural Heritage” and within SOFIA, a project of the ARTEMIS JU on embedded systems. I worked in cooperation with several international establishments, including the University of Kent, VTT (the Technical Reserarch Center of Finland) and Eurotech. On the national side I contributed to a one-to-one research contract between ARCES and Telecom Italia. The first part of the thesis is focused on problem statement and related work and addresses interoperability issues and related architecture components. The second part is focused on specific architectures and frameworks: - MobiComp: a context management framework that I used in cultural heritage applications - CAB: a context, preference and profile based application broker which I designed within EPOCH Network of Excellence - M3: "Semantic Web based" information sharing infrastructure for smart spaces designed by Nokia within the European project SOFIA - NoTa: a service and transport independent connectivity framework - OSGi: the well known Java based service support framework The final section is dedicated to the middleware, the tools and, the SW agents developed during my Doctorate time to support context-aware services in smart environments.

Progettazione ed implementazione di una piattaforma di cloud computing per il supporto ad applicazioni voip

Progettazione ed implementazione di una piattaforma di cloud computing per erogare macchine virtuali, in particolare macchine utilizzate come proxy server da applicazioni VoIP

Sviluppo di modelli motore e veicolo per l'analisi di strategie di controllo in applicazioni Software e Hardware In the Loop

This work describes the development of a simulation tool which allows the simulation of the Internal Combustion Engine (ICE), the transmission and the vehicle dynamics. It is a control oriented simulation tool, designed in order to perform both off-line (Software In the Loop) and on-line (Hardware In the Loop) simulation. In the first case the simulation tool can be used in order to optimize Engine Control Unit strategies (as far as regard, for example, the fuel consumption or the performance of the engine), while in the second case it can be used in order to test the control system. In recent years the use of HIL simulations has proved to be very useful in developing and testing of control systems. Hardware In the Loop simulation is a technology where the actual vehicles, engines or other components are replaced by a real time simulation, based on a mathematical model and running in a real time processor. The processor reads ECU (Engine Control Unit) output signals which would normally feed the actuators and, by using mathematical models, provides the signals which would be produced by the actual sensors. The simulation tool, fully designed within Simulink, includes the possibility to simulate the only engine, the transmission and vehicle dynamics and the engine along with the vehicle and transmission dynamics, allowing in this case to evaluate the performance and the operating conditions of the Internal Combustion Engine, once it is installed on a given vehicle. Furthermore the simulation tool includes different level of complexity, since it is possible to use, for example, either a zero-dimensional or a one-dimensional model of the intake system (in this case only for off-line application, because of the higher computational effort). Given these preliminary remarks, an important goal of this work is the development of a simulation environment that can be easily adapted to different engine types (single- or multi-cylinder, four-stroke or two-stroke, diesel or gasoline) and transmission architecture without reprogramming. Also, the same simulation tool can be rapidly configured both for off-line and real-time application. The Matlab-Simulink environment has been adopted to achieve such objectives, since its graphical programming interface allows building flexible and reconfigurable models, and real-time simulation is possible with standard, off-the-shelf software and hardware platforms (such as dSPACE systems).

Hybrid Methods for Resource Allocation and Scheduling Problems in Deterministic and Stochastic Environments

This work presents exact, hybrid algorithms for mixed resource Allocation and Scheduling problems; in general terms, those consist into assigning over time finite capacity resources to a set of precedence connected activities. The proposed methods have broad applicability, but are mainly motivated by applications in the field of Embedded System Design. In particular, high-performance embedded computing recently witnessed the shift from single CPU platforms with application-specific accelerators to programmable Multi Processor Systems-on-Chip (MPSoCs). Those allow higher flexibility, real time performance and low energy consumption, but the programmer must be able to effectively exploit the platform parallelism. This raises interest in the development of algorithmic techniques to be embedded in CAD tools; in particular, given a specific application and platform, the objective if to perform optimal allocation of hardware resources and to compute an execution schedule. On this regard, since embedded systems tend to run the same set of applications for their entire lifetime, off-line, exact optimization approaches are particularly appealing. Quite surprisingly, the use of exact algorithms has not been well investigated so far; this is in part motivated by the complexity of integrated allocation and scheduling, setting tough challenges for ``pure'' combinatorial methods. The use of hybrid CP/OR approaches presents the opportunity to exploit mutual advantages of different methods, while compensating for their weaknesses. In this work, we consider in first instance an Allocation and Scheduling problem over the Cell BE processor by Sony, IBM and Toshiba; we propose three different solution methods, leveraging decomposition, cut generation and heuristic guided search. Next, we face Allocation and Scheduling of so-called Conditional Task Graphs, explicitly accounting for branches with outcome not known at design time; we extend the CP scheduling framework to effectively deal with the introduced stochastic elements. Finally, we address Allocation and Scheduling with uncertain, bounded execution times, via conflict based tree search; we introduce a simple and flexible time model to take into account duration variability and provide an efficient conflict detection method. The proposed approaches achieve good results on practical size problem, thus demonstrating the use of exact approaches for system design is feasible. Furthermore, the developed techniques bring significant contributions to combinatorial optimization methods.

Sistemi riconfigurabili a basso consumo per applicazioni di monitoraggio distribuito

The term Ambient Intelligence (AmI) refers to a vision on the future of the information society where smart, electronic environment are sensitive and responsive to the presence of people and their activities (Context awareness). In an ambient intelligence world, devices work in concert to support people in carrying out their everyday life activities, tasks and rituals in an easy, natural way using information and intelligence that is hidden in the network connecting these devices. This promotes the creation of pervasive environments improving the quality of life of the occupants and enhancing the human experience. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. Ambient intelligent systems are heterogeneous and require an excellent cooperation between several hardware/software technologies and disciplines, including signal processing, networking and protocols, embedded systems, information management, and distributed algorithms. Since a large amount of fixed and mobile sensors embedded is deployed into the environment, the Wireless Sensor Networks is one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes which can be deployed in a target area to sense physical phenomena and communicate with other nodes and base stations. These simple devices typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). WNS promises of revolutionizing the interactions between the real physical worlds and human beings. Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. To fully exploit the potential of distributed sensing approaches, a set of challengesmust be addressed. Sensor nodes are inherently resource-constrained systems with very low power consumption and small size requirements which enables than to reduce the interference on the physical phenomena sensed and to allow easy and low-cost deployment. They have limited processing speed,storage capacity and communication bandwidth that must be efficiently used to increase the degree of local ”understanding” of the observed phenomena. A particular case of sensor nodes are video sensors. This topic holds strong interest for a wide range of contexts such as military, security, robotics and most recently consumer applications. Vision sensors are extremely effective for medium to long-range sensing because vision provides rich information to human operators. However, image sensors generate a huge amount of data, whichmust be heavily processed before it is transmitted due to the scarce bandwidth capability of radio interfaces. In particular, in video-surveillance, it has been shown that source-side compression is mandatory due to limited bandwidth and delay constraints. Moreover, there is an ample opportunity for performing higher-level processing functions, such as object recognition that has the potential to drastically reduce the required bandwidth (e.g. by transmitting compressed images only when something ‘interesting‘ is detected). The energy cost of image processing must however be carefully minimized. Imaging could play and plays an important role in sensing devices for ambient intelligence. Computer vision can for instance be used for recognising persons and objects and recognising behaviour such as illness and rioting. Having a wireless camera as a camera mote opens the way for distributed scene analysis. More eyes see more than one and a camera system that can observe a scene from multiple directions would be able to overcome occlusion problems and could describe objects in their true 3D appearance. In real-time, these approaches are a recently opened field of research. In this thesis we pay attention to the realities of hardware/software technologies and the design needed to realize systems for distributed monitoring, attempting to propose solutions on open issues and filling the gap between AmI scenarios and hardware reality. The physical implementation of an individual wireless node is constrained by three important metrics which are outlined below. Despite that the design of the sensor network and its sensor nodes is strictly application dependent, a number of constraints should almost always be considered. Among them: • Small form factor to reduce nodes intrusiveness. • Low power consumption to reduce battery size and to extend nodes lifetime. • Low cost for a widespread diffusion. These limitations typically result in the adoption of low power, low cost devices such as low powermicrocontrollers with few kilobytes of RAMand tenth of kilobytes of program memory with whomonly simple data processing algorithms can be implemented. However the overall computational power of the WNS can be very large since the network presents a high degree of parallelism that can be exploited through the adoption of ad-hoc techniques. Furthermore through the fusion of information from the dense mesh of sensors even complex phenomena can be monitored. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas:Low Power Video Sensor Node and Video Processing Alghoritm and Multimodal Surveillance . Low Power Video Sensor Nodes and Video Processing Alghoritms In comparison to scalar sensors, such as temperature, pressure, humidity, velocity, and acceleration sensors, vision sensors generate much higher bandwidth data due to the two-dimensional nature of their pixel array. We have tackled all the constraints listed above and have proposed solutions to overcome the current WSNlimits for Video sensor node. We have designed and developed wireless video sensor nodes focusing on the small size and the flexibility of reuse in different applications. The video nodes target a different design point: the portability (on-board power supply, wireless communication), a scanty power budget (500mW),while still providing a prominent level of intelligence, namely sophisticated classification algorithmand high level of reconfigurability. We developed two different video sensor node: The device architecture of the first one is based on a low-cost low-power FPGA+microcontroller system-on-chip. The second one is based on ARM9 processor. Both systems designed within the above mentioned power envelope could operate in a continuous fashion with Li-Polymer battery pack and solar panel. Novel low power low cost video sensor nodes which, in contrast to sensors that just watch the world, are capable of comprehending the perceived information in order to interpret it locally, are presented. Featuring such intelligence, these nodes would be able to cope with such tasks as recognition of unattended bags in airports, persons carrying potentially dangerous objects, etc.,which normally require a human operator. Vision algorithms for object detection, acquisition like human detection with Support Vector Machine (SVM) classification and abandoned/removed object detection are implemented, described and illustrated on real world data. Multimodal surveillance: In several setup the use of wired video cameras may not be possible. For this reason building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. Energy efficiency for wireless smart camera networks is one of the major efforts in distributed monitoring and surveillance community. For this reason, building an energy efficient wireless vision network for monitoring and surveillance is one of the major efforts in the sensor network community. The Pyroelectric Infra-Red (PIR) sensors have been used to extend the lifetime of a solar-powered video sensor node by providing an energy level dependent trigger to the video camera and the wireless module. Such approach has shown to be able to extend node lifetime and possibly result in continuous operation of the node.Being low-cost, passive (thus low-power) and presenting a limited form factor, PIR sensors are well suited for WSN applications. Moreover techniques to have aggressive power management policies are essential for achieving long-termoperating on standalone distributed cameras needed to improve the power consumption. We have used an adaptive controller like Model Predictive Control (MPC) to help the system to improve the performances outperforming naive power management policies.

Progettazione e Sviluppo di Applicazioni Web per Cloud Computing

Negli ultimi anni si sente sempre più spesso parlare di cloud computing. L'idea di fondo di questo concetto è quella di pagare per il solo effettivo utilizzo di un servizio, disponibile sulla rete, avendo a disposizione la possibilità di poter variare le proprie risorse utilizzabili a seconda delle necessità, che potrebbero essere, per esempio, applicazioni standard oppure spazi di storage per i dati. Quando cominciò a diffondersi l'utilizzo del Web, la rete Internet veniva raffigurata come una nuvola (cloud) in modo tale che si rendesse l'idea di un'entità esterna rispetto alla nostra casa o al nostro posto di lavoro, un qualcosa cioè al di fuori dei luoghi abituali in cui vengono utilizzati i PC. Tale rappresentazione diventa ora utile per poter spiegare il concetto di cloud computing. Infatti, grazie a questa nuova tecnologia, dati e programmi normalmente presenti nei nostri computer potranno ora trovarsi sul cloud. Molti reparti IT sono costretti a dedicare una parte significativa del loro tempo a progetti di implementazione, manutenzione e upgrade che spesso non danno un vero valore per l'azienda. I team di sviluppo hanno cominciato quindi a rivolgersi a questa nuova tecnologia emergente per poter minimizzare il tempo dedicato ad attività a basso valore aggiunto per potersi concentrare su quelle attività strategiche che possono fare la differenza per un'azienda. Infatti un'infrastruttura come quella cloud computing promette risparmi nei costi amministrativi che raggiungono addirittura il 50% rispetto ad un software standard di tipo client/server. Questa nuova tecnologia sta dando inizio ad un cambiamento epocale nel mondo dello sviluppo delle applicazioni. Il passaggio che si sta effettuando verso le nuove soluzioni cloud computing consente infatti di creare applicazioni solide in tempi decisamente più brevi e con costi assai inferiori, evitando inoltre tutte le seccature associate a server, soluzioni software singole, aggiornamenti, senza contare il personale necessario a gestire tutto questo. L'obiettivo di questa tesi è quello di mostrare una panoramica della progettazione e dello sviluppo di applicazioni Web nel cloud computing, analizzandone pregi e difetti in relazione alle soluzioni software attuali. Nel primo capitolo viene mostrato un quadro generale in riferimento al cloud, mettendo in luce le sue caratteristiche fondamentali, esaminando la sua architettura e valutando vantaggi e svantaggi di tale piattaforma. Nel secondo capitolo viene presentata la nuova metodologia di progettazione nel cloud, operando prima di tutto un confronto con lo sviluppo dei software standard e analizzando poi l'impatto che il cloud computing opera sulla progettazione. Nel terzo capitolo si entra nel merito della progettazione e sviluppo di applicazioni SaaS, specificandone le caratteristiche comuni ed elencando le piattaforme di rilievo allo stato dell'arte. Si entrerà inoltre nel merito della piattaforma Windows Azure. Nel quarto capitolo viene analizzato nel particolare lo sviluppo di applicazioni SaaS Multi-Tenant, specificando livelli e caratteristiche, fino a spiegare le architetture metadata-driven. Nel quinto capitolo viene operato un confronto tra due possibili approcci di sviluppo di un software cloud, analizzando nello specifico le loro differenze a livello di requisiti non funzionali. Nel sesto capitolo, infine, viene effettuata una panoramica dei costi di progettazione di un'applicazione cloud.

Workflow Patterns for Service Oriented Computing in JOLIE

Il presente lavoro di tesi ha come punto focale la descrizione, la verifica e la dimostrazione della realizzabilità dei Workflow Patterns di Gestione del Flusso(Control-Flow) e Risorse (Resource) definiti da parte della Workflow Pattern Initiative (WPI)in JOLIE, un innovativo linguaggio di programmazione orientato ai servizi nato nell'ambito del Service Oriented Computing. Il Service Oriented Computing (SOC) è un nuovo modo di pensare la programmazione di applicazioni distribuite, i cui concetti fondamentali sono i servizi e la composizione. L’approccio SOC definisce la possibilità di costruire un’applicazione in funzione dei servizi che ne realizzano il comportamento tramite una loro composizione, definita secondo un particolare flusso di lavoro. Allo scopo di fornire la necessaria conoscenza per capire la teoria, le meccaniche e i costrutti di JOLIE utilizzati per la realizzazione dei pattern, il seguente lavoro di tesi è stato diviso in quattro parti, corrispondenti ad altrettanti capitoli. Nel primo capitolo viene riportata una descrizione generale del SOC e della Business Process Automation (BPA), che costituisce l’ambiente in cui il SOC è inserito. Per questo viene fatta una disamina della storia informatica sui sistemi distribuiti, fino ad arrivare ai sistemi odierni, presentando in seguito il contesto del BPA e delle innovazioni derivanti dalle sue macro-componenti, di cui il SOC fa parte. Continuando la descrizione dell’approccio Service Oriented, ne vengono presentati i requisiti (pre-condizioni) e si cerca di dare una definizione precisa del termine “servizio”, fino all'enunciazione dei principi SOC declinati nell’ottica delle Service Oriented Architectures, presentando in ultimo i metodi di composizione dei servizi, tramite orchestrazione e coreografia. L’ultima sezione del capitolo prende in considerazione il SOC in un’ottica prettamente industriale e ne evidenzia i punti strategici. Il secondo capitolo è incentrato sulla descrizione di JOLIE, gli aspetti fondamentali dell’approccio orientato ai servizi, che ne caratterizzano profondamente la definizione concettuale (SOCK), e la teoria della composizione dei servizi. Il capitolo non si pone come una descrizione esaustiva di tutte le funzionalità del linguaggio, ma considera soprattutto i concetti teorici, le strutture di dati, gli operatori e i costrutti di JOLIE utilizzati per la dimostrazione della realizzabilità dei Workflow Pattern del capitolo successivo. Il terzo capitolo, più lungo e centrale rispetto agli altri, riguarda la realizzazione dei workflow pattern in JOLIE. All'inizio del capitolo viene fornita una descrizione delle caratteristiche del WPI e dei Workflow Pattern in generale. In seguito, nelle due macro-sezioni relative ai Control-Flow e Resource pattern vengono esposte alcune nozioni riguardanti le metodologie di definizione dei pattern (e.g. la teoria sulla definizione delle Colored Petri Nets) e le convezioni adottate dal WPI, per passare in seguito al vero e proprio lavoro (sperimentale) di tesi riguardo la descrizione dei pattern, l’analisi sulla loro realizzabilità in JOLIE, insieme ad un codice di esempio che esemplifica quanto affermato dall'analisi. Come sommario delle conclusioni raggiunte sui pattern, alla fine di ognuna delle due sezioni definite in precedenza, è presente una scheda di valutazione che, con lo stesso metodo utilizzato e definito dalla WPI, permette di avere una rappresentazione generale della realizzabilità dei pattern in JOLIE. Il quarto capitolo riguarda gli esiti tratti dal lavoro di tesi, riportando un confronto tra le realizzazioni dei pattern in JOLIE e le valutazioni del WPI rispetto agli altri linguaggi da loro considerati e valutati. Sulla base di quanto ottenuto nel terzo capitolo vengono definite le conclusioni del lavoro portato avanti sui pattern e viene delineato un’eventuale scenario riguardante il proseguimento dell’opera concernente la validazione ed il completamento della studio. In ultimo vengono tratte alcune conclusioni sia riguardo JOLIE, nel contesto evolutivo del linguaggio e soprattutto del progetto open-source che è alla sua base, sia sul SOC, considerato nell’ambito del BPA e del suo attuale ambito di sviluppo dinamico.

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.

Heterogeneous multicore systems for signal processing

This thesis explores the capabilities of heterogeneous multi-core systems, based on multiple Graphics Processing Units (GPUs) in a standard desktop framework. Multi-GPU accelerated desk side computers are an appealing alternative to other high performance computing (HPC) systems: being composed of commodity hardware components fabricated in large quantities, their price-performance ratio is unparalleled in the world of high performance computing. Essentially bringing “supercomputing to the masses”, this opens up new possibilities for application fields where investing in HPC resources had been considered unfeasible before. One of these is the field of bioelectrical imaging, a class of medical imaging technologies that occupy a low-cost niche next to million-dollar systems like functional Magnetic Resonance Imaging (fMRI). In the scope of this work, several computational challenges encountered in bioelectrical imaging are tackled with this new kind of computing resource, striving to help these methods approach their true potential. Specifically, the following main contributions were made: Firstly, a novel dual-GPU implementation of parallel triangular matrix inversion (TMI) is presented, addressing an crucial kernel in computation of multi-mesh head models of encephalographic (EEG) source localization. This includes not only a highly efficient implementation of the routine itself achieving excellent speedups versus an optimized CPU implementation, but also a novel GPU-friendly compressed storage scheme for triangular matrices. Secondly, a scalable multi-GPU solver for non-hermitian linear systems was implemented. It is integrated into a simulation environment for electrical impedance tomography (EIT) that requires frequent solution of complex systems with millions of unknowns, a task that this solution can perform within seconds. In terms of computational throughput, it outperforms not only an highly optimized multi-CPU reference, but related GPU-based work as well. Finally, a GPU-accelerated graphical EEG real-time source localization software was implemented. Thanks to acceleration, it can meet real-time requirements in unpreceeded anatomical detail running more complex localization algorithms. Additionally, a novel implementation to extract anatomical priors from static Magnetic Resonance (MR) scansions has been included.