Semantic IoT Solutions - A Developer Perspective

Semantic technologies have recently gained significant support in a number of communities, in particular the IoT community. An important problem to be solved is that, on the one hand, it is clear that the value of IoT increases significantly with the availability of information from a wide variety of domains. On the other hand, existing solutions target specific applications or application domains and there is no easy way of sharing information between the resulting silos. Thus, a solution is needed to enable interoperability across information silos. As there is a huge heterogeneity regarding IoT technologies on the lower levels, the semantic level is seen as a promising approach for achieving interoperability (i.e. semantic interoperability) to unify IoT device description, data, bring common interaction, data exploration, etc.This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreements No.732240 (SynchroniCity) and No. 688467 (VICINITY); from ETSI under Specialist Task Forces 534, 556, 566 and 578. This work is partially funded by Hazards SEES NSF Award EAR 1520870, and KHealth NIH 1 R01 HD087132-01

Monitoring and Information Alignment in Pursuit of an IoT-Enabled Self-Sustainable Interoperability

To remain competitive with big corporations, small and medium-sized enterprises (SMEs) often need to be more dynamic, adapt to new business situations, react faster, and thereby survive in today‘s global economy. To do so, SMEs normally seek to create consortiums, thus gaining access to new and more opportunities. However, this strategy may also lead to complications. Due to the different sources of enterprise models and semantics, organizations are experiencing difficulties in seamlessly exchanging vital information via electronic means. In their attempt to address this issue, most seek to achieve interoperability by establishing peer-to-peer mappings with different business partners, or by using neutral data standards to regulate communications in optimized networks. Moreover, systems are more and more dynamic, frequently changing to answer new customer‘s requirements, causing new interoperability problems and a reduction of efficiency. Another situation that is constantly changing is the devices used in the enterprises, as the Enterprise Information Systems, devices are used to register internal data, and to be used to monitor several aspects. These devices are constantly changing, following the evolution and growth of the market. So, it is important to monitor these devices and doing a model representation of them. This dissertation proposes a self-sustainable interoperable framework to monitor existing enterprise information systems and their devices, monitor the device/enterprise network for changes and automatically detecting model changes. With this, network harmonization disruptions are detected in a timely way, and possible solutions are suggested to regain the interoperable status, thus enhancing robustness for reaching sustainability of business networks along time

Deployment and Operation of Complex Software in Heterogeneous Execution Environments

This open access book provides an overview of the work developed within the SODALITE project, which aims at facilitating the deployment and operation of distributed software on top of heterogeneous infrastructures, including cloud, HPC and edge resources. The experts participating in the project describe how SODALITE works and how it can be exploited by end users. While multiple languages and tools are available in the literature to support DevOps teams in the automation of deployment and operation steps, still these activities require specific know-how and skills that cannot be found in average teams. The SODALITE framework tackles this problem by offering modelling and smart editing features to allow those we call Application Ops Experts to work without knowing low level details about the adopted, potentially heterogeneous, infrastructures. The framework offers also mechanisms to verify the quality of the defined models, generate the corresponding executable infrastructural code, automatically wrap application components within proper execution containers, orchestrate all activities concerned with deployment and operation of all system components, and support on-the-fly self-adaptation and refactoring

A Multi-Criteria Framework to Assist on the Design of Internet-of-Things Systems

The Internet-of-Things (IoT), considered as Internet first real evolution, has become immensely important to society due to revolutionary business models with the potential to radically improve Human life. Manufacturers are engaged in developing embedded systems (IoT Systems) for different purposes to address this new variety of application domains and services. With the capability to agilely respond to a very dynamic market offer of IoT Systems, the design phase of IoT ecosystems can be enhanced. However, select the more suitable IoT System for a certain task is currently based on stakeholder’s knowledge, normally from lived experience or intuition, although it does not mean that a proper decision is being made. Furthermore, the lack of methods to formally describe IoT Systems characteristics, capable of being automatically used by methods is also an issue, reinforced by the growth of available information directly connected to Internet spread. Contributing to improve IoT Ecosystems design phase, this PhD work proposes a framework capable of fully characterise an IoT System and assist stakeholder’s on the decision of which is the proper IoT System for a specific task. This enables decision-makers to perform a better reasoning and more aware analysis of diverse and very often contradicting criteria. It is also intended to provide methods to integrate energy consumptionsimulation tools and address interoperability with standards, methods or systems within the IoT scope. This is addressed using a model-driven based framework supporting a high openness level to use different software languages and decision methods, but also for interoperability with other systems, tools and methods

Semantic Web and the Web of Things: concept, platform and applications

The ubiquitous presence of devices with computational resources and connectivity is fostering the diffusion of the Internet of Things (IoT), where smart objects interoperate and react to the available information providing services to the users. The pervasiveness of the IoT across many different areas proves the worldwide interest of researchers from academic and enterprises worlds. This Research has brought to new technologies and protocols addressing different needs of emerging scenarios, making difficult to develop interoperable applications. The Web of Things is born to address this problem through the standard protocols responsible for the success of the Web. But a greater contribution can be provided by standards of the Semantic Web. Semantic Web protocols grant univocal identification of resources and representation of data in a way that information is machine understandable and computable and such that information from different sources can be easily aggregated. Semantic Web technologies are then interoperability enablers for the IoT. This Thesis investigates how to employ Semantic Web protocols in the IoT, to realize the Semantic Web of Things (SWoT) vision of an interoperable network of applications. Part I introduces the IoT, Part II investigates the algorithms to efficiently support the publish/subscribe paradigm in semantic brokers for the SWoT and their implementation in Smart-M3 and SEPA. The preliminary work toward the first benchmark for SWoT applications is presented. Part IV describes the Research activity aimed at applying the developed semantic infrastructures in real life scenarios (electro-mobility, home automation, semantic audio and Internet of Musical Things). Part V presents the conclusions. A lack of effective ways to explore and debug Semantic Web datasets emerged during these activities. Part III describes a second Research aimed at devising of a novel way to visualize semantic datasets, based on graphs and the new concept of Semantic Planes.La presenza massiva di dispositivi dotati di capacità computazionale e connettività sta alimentando la diffusione di un nuovo paradigma nell'ICT, conosciuto come Internet of Things. L'IoT è caratterizzato dai cosiddetti smart object che interagiscono, cooperano e reagiscono alle informazioni a loro disponibili per fornire servizi agli utenti. La diffusione dell'IoT su così tante aree è la testimonianza di un interesse mondiale da parte di ricercatori appartenenti sia al mondo accademico che a quello industriale. La Ricerca ha portato alla nascita di tecnologie e protocolli progettati per rispondere ai diversi bisogni degli scenari emergenti, rendendo difficile sviluppare applicazioni interoperabili. Il Web of Things (WoT) è nato per rispondere a questi problemi tramite l'adozione degli standard che hanno favorito il successo del Web. Ma un contributo maggiore può venire dal Semantic Web of Things (SWoT). Infatti, i protocolli del Semantic Web permettono identificazione univoca delle risorse e una rappresentazione dei dati tale che le informazioni siano computabili e l'informazione di differenti fonti facilmente aggregabile. Le tecnologie del Semantic Web sono quindi degli interoperability enabler per l'IoT. Questa Tesi analizza come adottare le tecnologie del Semantic Web nell'IoT per realizzare la visione del SWoT di una rete di applicazioni interoperabile. Part I introduce l'IoT, Part II analizza gli algoritmi per supportare il publish-subscribe nei broker semantici e la loro implementazione in Smart-M3 e SEPA. Inoltre, viene presentato il lavoro preliminare verso il primo benchmark per applicazioni SWoT. Part IV discute l'applicazione dei risultati a diversi domini applicativi (mobilità elettrica, domotica, semantic audio ed Internet of Musical Things). Part V presenta le conclusioni sul lavoro svolto. La Ricerca su applicazioni semantiche ha evidenziato carenze negli attuali software di visualizzazione. Quindi, Part III presenta un nuovo metodo di rappresentazione delle basi di conoscenza semantiche basato sull’approccio a grafo che introduce il concetto di Semantic Plane

Advanced Security Analysis for Emergent Software Platforms

Emergent software ecosystems, boomed by the advent of smartphones and the Internet of Things (IoT) platforms, are perpetually sophisticated, deployed into highly dynamic environments, and facilitating interactions across heterogeneous domains. Accordingly, assessing the security thereof is a pressing need, yet requires high levels of scalability and reliability to handle the dynamism involved in such volatile ecosystems. This dissertation seeks to enhance conventional security detection methods to cope with the emergent features of contemporary software ecosystems. In particular, it analyzes the security of Android and IoT ecosystems by developing rigorous vulnerability detection methods. A critical aspect of this work is the focus on detecting vulnerable and unsafe interactions between applications that share common components and devices. Contributions of this work include novel insights and methods for: (1) detecting vulnerable interactions between Android applications that leverage dynamic loading features for concealing the interactions; (2) identifying unsafe interactions between smart home applications by considering physical and cyber channels; (3) detecting malicious IoT applications that are developed to target numerous IoT devices; (4) detecting insecure patterns of emergent security APIs that are reused from open-source software. In all of the four research thrusts, we present thorough security analysis and extensive evaluations based on real-world applications. Our results demonstrate that the proposed detection mechanisms can efficiently and effectively detect vulnerabilities in contemporary software platforms. Advisers: Hamid Bagheri and Qiben Ya