Uniquitous internet middleware: architecture design and prototype evaluation

Technology advances in recent years have dramatically changed the way users exploit contents and services available on the Internet, by enforcing pervasive and mobile computing scenarios and enabling access to networked resources almost from everywhere, at anytime, and independently of the device in use. In addition, people increasingly require to customize their experience, by exploiting specific device capabilities and limitations, inherent features of the communication channel in use, and interaction paradigms that significantly differ from the traditional request/response one. So-called Ubiquitous Internet scenario calls for solutions that address many different challenges, such as device mobility, session management, content adaptation, context-awareness and the provisioning of multimodal interfaces. Moreover, new service opportunities demand simple and effective ways to integrate existing resources into new and value added applications, that can also undergo run-time modifications, according to ever-changing execution conditions. Despite service-oriented architectural models are gaining momentum to tame the increasing complexity of composing and orchestrating distributed and heterogeneous functionalities, existing solutions generally lack a unified approach and only provide support for specific Ubiquitous Internet aspects. Moreover, they usually target rather static scenarios and scarcely support the dynamic nature of pervasive access to Internet resources, that can make existing compositions soon become obsolete or inadequate, hence in need of reconfiguration. This thesis proposes a novel middleware approach to comprehensively deal with Ubiquitous Internet facets and assist in establishing innovative application scenarios. We claim that a truly viable ubiquity support infrastructure must neatly decouple distributed resources to integrate and push any kind of content-related logic outside its core layers, by keeping only management and coordination responsibilities. Furthermore, we promote an innovative, open, and dynamic resource composition model that allows to easily describe and enforce complex scenario requirements, and to suitably react to changes in the execution conditions.

Quality of Service in Distributed Stream Processing for large scale Smart Pervasive Environments

The wide diffusion of cheap, small, and portable sensors integrated in an unprecedented large variety of devices and the availability of almost ubiquitous Internet connectivity make it possible to collect an unprecedented amount of real time information about the environment we live in. These data streams, if properly and timely analyzed, can be exploited to build new intelligent and pervasive services that have the potential of improving people's quality of life in a variety of cross concerning domains such as entertainment, health-care, or energy management. The large heterogeneity of application domains, however, calls for a middleware-level infrastructure that can effectively support their different quality requirements. In this thesis we study the challenges related to the provisioning of differentiated quality-of-service (QoS) during the processing of data streams produced in pervasive environments. We analyze the trade-offs between guaranteed quality, cost, and scalability in streams distribution and processing by surveying existing state-of-the-art solutions and identifying and exploring their weaknesses. We propose an original model for QoS-centric distributed stream processing in data centers and we present Quasit, its prototype implementation offering a scalable and extensible platform that can be used by researchers to implement and validate novel QoS-enforcement mechanisms. To support our study, we also explore an original class of weaker quality guarantees that can reduce costs when application semantics do not require strict quality enforcement. We validate the effectiveness of this idea in a practical use-case scenario that investigates partial fault-tolerance policies in stream processing by performing a large experimental study on the prototype of our novel LAAR dynamic replication technique. Our modeling, prototyping, and experimental work demonstrates that, by providing data distribution and processing middleware with application-level knowledge of the different quality requirements associated to different pervasive data flows, it is possible to improve system scalability while reducing costs.